System for automated collection, processing and transmission of medical data

FIELD: information technology.

SUBSTANCE: system for collecting information on health status processes information into a composite numerical value and publishes said value. The system comprises a computer, having a processor, a storage device and encoding modules executed by the processor to carry out the method. The system includes a step of collecting information relating to certain internal and external factors of a user. Weight coefficients are applied to a factor to control the relative effect of each factor on the calculated numerical value associated with the user. A health status estimate is calculated using the processor by merging the weighted factors in accordance with an algorithm. The numerical value is published for a designated group through a portal, while main factors remain private.

EFFECT: enabling publication of a numerical estimate of data relating to the health status of a person in masked form while still allowing comparative evaluation.

24 cl, 13 dwg

CROSS-REFERENCE TO RELATED APPLICATIONS

In this application claimed priority from patent application U.S. No. 61/387906, filed September 29, 2010 and patent application U.S. No. 61/495247, filed June 9, 2011, which are fully incorporated into the present application by reference.

The technical FIELD

The present invention relates to implemented using a computer system for collecting medical data and their processing for diagnostic purposes, a reference comparison, analysis and redistribution. More specifically, the present invention relates to implemented using a computer system and method of data collection, diagnostic, benchmark comparisons, analysis and/or redistribution of medical data.

The LEVEL of TECHNOLOGY

Despite advances in various areas of technology, there are still barriers to the evaluation of the relative health of a person is fast, economical and timely manner. With the increasing cost of health services and the prevalence of diseases associated with an unhealthy lifestyle, such as diabetes and heart disease, it is important to assess the relative health of the people, and this problem has no effective solutions. In some parts of the world access to doctors is limited. Even in developed countries, the working time of the doctor is very expensive, and often there are long the s turns to the doctor, and before a personal visit to the doctor, the patient should take advantage of the referral from the GP to a specialist. In developed countries, the ratio of doctors to population size may be about 1:1000, while in less developed countries this ratio may be 1:100000. There are also price barriers that restrict access to the doctor, because the doctor's visits can be very expensive, especially if the person does not have health insurance or lack of funds. Accordingly, access to other health care professionals to obtain information about the state of health can be very difficult.

Even if the person has access to their medical information, mechanisms for the transfer of this information to other people are insufficient or absent. The privacy laws limit the type of information that can be distributed, and specific ways of its distribution. The privacy laws relating to medical information, are particularly strict regarding distribution of the information. They are designed to protect the person from disclosing its confidential information. Accordingly, the dissemination of information related to health status, generally condemned. Also difficult is most the of information, related to health status, among friends and relatives. Often medical information transmitted by the physician to the patient orally, or paper copies of the results of measurements and laboratory tests give into the hands of the patient. Thus, there is a lack of systems that perform lightweight dissemination to other people, in particular among large groups of people living in geographically remote locations.

Known systems provide a limited type of numerical evaluation, related to health. For example, in patent publication U.S. No. 2009/0105550, Rothman and others, describes a method and system for forming an assessment of health status for the patient. However, these method and system primarily intended for the calculation of the assessment of the health status of the patient in the hospital after surgery, and assessment of health based on medical data measured from the patient (e.g. blood pressure, temperature, breathing, etc). In the specified method is not taken into account the external action of the patient, such as daily physical exercise of the patient. In patent publication U.S. No. 2005/0228692, Hodgdon, described a system that calculates an estimate of the health status on the basis of the measured health the data and gives the patient the possibility of self-examination, which may include a review of habitual exercise of the patient. However, this system takes into account only implied habits of the person, not the actual physical exercises that people perform every day. Accordingly, it is static and does not change relative to the actually performed the exercises.

These known systems are primarily used by healthcare providers to ensure continuity of treatment, and to establish and maintain assessments requires that physicians themselves have introduced data. Since the attention of the attending physician is necessary in situations of emergency and intensive therapy, with consideration of cost and resources it is obvious that such systems are suitable for use only in specified situations, and such systems are not applicable to the General problems described above. In addition, the assessment relates only to the specific point in time, i.e. the time of the last update by the doctor.

DISCLOSURE of INVENTIONS

According to one aspect of the present invention is proposed to be implemented using a computer method of processing related to private health data in the masked numeric rating that is appropriate for the publication, containing the steps are:

take to remember the e device data about the internal health indicators and external indicators of physical activity of the user,

save received data in a storage device,

keep the weights in a storage device,

process the received data by execution by the processor, configures the processor to apply these weights to the internal health indicators and external indicators of physical activity, and these weighting factors for external indicators of physical activity contain aggravating component formed with the possibility of reducing the relative weight of external indicators of physical activity for physical activity based on at least one factor associated with the user,

convert the processed data related to the internal health indicators and external indicators of physical activity, by execution of code by a processor in the masked composite numerical value in which the code is valid for combining the weighted indicators in accordance with the algorithm, and

automatically publish masked composite numerical value assigned to groups through the portal using code executing in the processor and free from human intervention while maintaining the privacy of information collected related to the internal medical pokazatel the m and external indicators of physical activity.

According to an additional aspect of the proposed method, which can be implemented in a particular variant of implementation, the coefficient associated with the user, an age or age range of the user, so aggravating component reduces the relative weight of external indicators of physical activity for the first user with the first age, or first age range, otherwise than for the second user having a second age of or relating to the second age range.

According to an additional aspect of the proposed method, which can be implemented in a particular variant of implementation, average published masked composite numerical value of the user group to determine the group integral numeric values using additional code, executable by the processor.

According to an additional aspect of the present invention proposed implemented computer-based system for tracking health, containing:

a communication unit configured to receive data about the internal health indicators and external indicators of physical activity of the user;

a storage device configured to maintain accepted the data and save the weight coefficients;

the processor is made with the possibility of data processing by execution of the code that configures the specified processor for applying weighting coefficients to the internal health indicators and external indicators of physical activity, and these weighting factors for external indicators of physical activity contain aggravating component made with the possibility of reducing the relative importance of the indicators of physical activity for physical activity based on at least one factor associated with a user;

while the processor is additionally configured to execute the code to convert the processed data related to the internal health indicators and external indicators of physical activity in the masked composite numerical value using the processor by combining the weighted indicators in accordance with a certain algorithm; and

the portal is configured to publish the masked composite numerical value assigned to the group while maintaining the privacy of information collected related to the internal health indicators and external indicators of physical activity.

The proposed system is preferably designed so that the ratio is m, associated with a user, is the age or age range of the user, so aggravating component reduces the relative weight of external indicators of physical activity for the first user with the first age, or first age range, otherwise than for the second user having a second age of or relating to the second age range.

According to one implementation variant of the present invention in accordance with additional aspects of the proposed system further comprises a bidirectional communication channel with gym equipment, configured to:

transfer the processed data or masked composite numerical value fitness equipment;

automatic installation program exercises on the basis of the transferred data or masked composite numerical value; and

receiving at the memory device from gym equipment activity information for inclusion in the external indicators of physical activity.

The system and method according to the options the implementation of the present invention provide a combination of data taken from various medical and non-medical sources, to generate a normalized evaluation that takes into account available data on copper is Ty indicators physical activity and more about the lifestyle (such as diet), in a manner that provides the ability to manage and update it essentially in real time, and which does not require frequent visits to the doctor. Assessment and tendencies of its changes can be used for various purposes, including the filing of warning signals about possible medical problems or repercussions, feedback from user, the automated motivation and/or goal setting, scheduling training, automated referral to a specialist for a medical examination. Among the generated warning signals are signals that are invoked on the basis of tracking a composite assessment of health status, calculated numeric value which can cause feedback to transmit the evaluation to the user (for example, through the portal system, e-mail, SMS etc) as a result of execution processor code, and without human intervention, if you are tracking a detected change in the user's ratings, such as the deterioration of its value in the result of the algorithm, or the reduction of its value due to improper power supply, or when the goals entered into the system by the user or the group that is associated with the specified user the sludge is how the part is not dependent on the specific user target program, carried out by the system for motivating improved health (for example, recommends effective exercise or diet). According to variants of implementation of the present invention apply a weighting factor to relevant data about physical activity and/or lifestyle, so recent events have on the assessment of the greater influence compared to the events that occurred in the distant past.

According to the described variants of implementation of the proposed a unique method of calculating the assessment of health status, which masks the basic statistics for health and at the same time provides a comparative measurement of parameters for different applications. According to a variant implementation of the method of collection and presentation of data related to health status. The method contains the steps that collect information related to some internal health indicators and external indicators of physical activity of the user. The information collected and the weights remain in the storage device. Then the collected information is processed by the execution processor code that configures the processor to apply the weights to the internal health indicators and external indicators of physical activity. Collected in the ormatio, related to the internal health indicators and external indicators of physical activity, transform into masked composite numerical value using the processor by combining the weighted indicators in accordance with a predetermined algorithm. The masked composite numerical value published for the assigned group through the portal, supporting the privacy of information collected related to the internal health indicators and external indicators of physical activity.

According to preferred variants of implementation of the present invention proposed a normalized rating system, providing assessment of the relative health of a person, which can be used as the basis for impartial comparing with other people with different age, gender, medical condition or lifestyle.

Various features, aspects and advantages of the present invention will be apparent after reading the following description of some options for implementing the present invention and the accompanying drawings.

BRIEF DESCRIPTION of DRAWINGS

Figure 1 schematically shows a block diagram of a system for collecting local health information and communication system according to the first variations is the implementation of the present invention.

On figa shows a network diagram according to another implementation variant of the present invention.

Figure 2 schematically shows a block diagram of a method according to one implementation variant of the present invention.

On figa-3E shows the user interface screens according to one implementation variant of the present invention.

On fig.3f shows the variation over time in the indicators used for assessment of health status, according to one implementation variant of the present invention.

On figa shows the format of data presentation according to one implementation variant of the present invention.

On fig.4b shows the format of data presentation according to one implementation variant of the present invention.

On figs shows the format of data presentation according to one implementation variant of the present invention.

On fig.4d shows the format of data presentation according to one implementation variant of the present invention.

The IMPLEMENTATION of the INVENTION

Further, the present invention is described in detail on the example of a distributed system in which reception, accumulation, preservation and processing of data used to generate point estimates as the basis for determining the relative health of the user.

According to one implementation variant system is 100 mA contains executable computer application to collect parameters, related to the health condition of the user, and the user interface 110 to display the data. Sung by the computer application implemented by the microcontroller 120, which contains a processor 124, a storage device 122 and the executable code for configuring a processor to perform the described in the present application functionality. The memory is designed to store data and instructions suitable for controlling the operation of the processor. Embodiments of the memory may include as an example, but not limitation, random access memory (RAM), hard drive, or a persistent storage device (ROM). One of the components stored in memory, is a program. The program includes instructions that cause performance of the processor stages that implement described in the present application methods. The program can be implemented in the form of a single module or several modules that operate in cooperation with each other. The program is viewed as representing a software component, which can be used in conjunction with any variant of realization of the present invention.

Communication subsystem 125 is used to transfer information from the microprocessor 120 to Elizavetinskaya interface 110, such as an external device (for example, a portable unit or a computer, which is connected via the network communication subsystem 125).

The information can be transmitted to the communication subsystem 125 in a variety of ways, including Bluetooth, WiFi, WiMax, RF transmission, etc. Can be used in different network topologies, such as wired, optical network, 3G network, 4G, etc.

The communication subsystem may be part of the communication electronic device, including for example smartphone or cellular telephone, personal digital assistant (PDA), netbook, laptop, etc. for Example, communication subsystem 125 may be directly connected through a device such as a smartphone such as the iPhone, the phone based on Google's Android OS, pocket PC brand BlackBerry phone based mobile OS version of Microsoft's Windows and the like, or device, such as a monitor for measuring heart rate or blood pressure (such as manufactured by Withings SAS), scales (such as manufactured by Withings SAS), gym equipment or the like. In any case, each device has an interface for connection with a block or block for communication with the subsystem 125, providing an opportunity to exchange information and control signals between the subsystem 125 and external user interfejs the apparatus 110. In sum, the communication subsystem may interact with known communication device or may be part of a device designed to transmit information processed by the microcontroller 120.

If the communication electronic device, such as described above, is used as an external user interface device 110, display device, a processor and a storage device such devices can be used to process information related to health status, to ensure numerical evaluation. In other words, the system 100 may include display device 140, and a storage device 150, which are connected with an external device and used to maintain the connection in real time or in a different mode. In General, the system 100 includes a user interface that may be partially implemented by software modules executed in the processor of the microcontroller 120, or under the control of the external device 130. In particular, the user interface may also include an output device such as display device (e.g., display device 140).

Biopathic 115 can be used to directly collect information about the health condition of the user who send the specified information. The biosensor may be in contact with the user's body to measure vital functions or to receive from a user other relevant health information. For example, the biosensor can be an indicator of the pulse, which when worn is in contact with the user's body so that it can be discovered by the user's heart rate, a heart rate monitor that monitors heart rate, the device for removing the electrocardiogram, a pedometer, a device for monitoring blood glucose or one of many other devices or systems. The biosensor may include a communication unit (for example, communication subsystem 125), so that the biosensor can transmit a wired or wireless way the measured data. The biosensor can transmit measured data to a user interface device, which, in turn, transmits this information to the microcontroller. In addition, the biosensor can directly transmit the measured data to the microprocessor. Using biosensing provides a high degree of reliability of the transmitted data, because it eliminates errors associated with manual, self-transfer of data.

According to another implementation variant, or in addition to this, the user can independently passing is to be related to his health information by manual data entry. Thus, according to another implementation variant, shown in figa, data related to the health condition of the user is entered directly into the computer 160 through network 170 are transferred to the server 180. (All described in this application and server computers include at least one processor and a storage device).

Regardless of the implementation, the system provides a means for assigning a numeric value that represents the relative health of a person. A numeric value described in the present application as "health assessment" and can be used for the evaluation of human health on the basis of information related to health status collected from the user. The health assessment is calculated on the basis of the collected medical information using the algorithm. The user or the communication subsystem 125 to transmit the system information related to health, containing a variety of health indicators. The specified weights are used to assign relative values to each of the indicators that are used to calculate estimates of health status. Then by combining the weighted indicators, calculated in accordance with a specified algorithm assessment is the state of health of the user. For example, indicators can be the level of glucose in human blood and the weight of his body. The weighting coefficient "a" is applied to the data about the level of glucose in the blood, and the weight coefficient "b" can be applied to data on the weight of the human body. If the data on the content of glucose in the blood will be more important indicator in determining the health of a person than the weight of his body, the weight coefficient "a" will have more weight coefficient "b", so that data on the content of glucose in the blood will have a greater impact on the calculated assessment of health status (for example, Assessment of health status = Glucose*a + (Weight/100)*b). According to some variants of realization of the weighting factor has a nontrivial value (for example, is more or less than one, but not equal to one). In the calculation of the assessment of the health status can be enabled or some additional indicators, and can also be included corrective value is added to the result of calculation or subtracted from it, or according to some variants of implementation modifies all the calculation, for example, to account for age or gender as two possible causes; however, the foregoing should be considered as a non-limiting example of the calculation of the assessment of health status. Other parameters that can be measured and used in the calc is lenii, include measurement of blood pressure, height, body mass index, fat content in the body, medical conditions such as diabetes, ventricular hypertrophy, hypertension, irregular heartbeat, and determination of glucose in blood. Missing parameter can be removed from the calculation, or it can be derived from other parameters and/or values obtained from samples from a group of people with similar parameters.

In addition to the internal health indicators when calculating the assessment of the health status of the user is also taken into account his / her physical activity. Physical activity can be monitored by an appropriate sensor, depending on the kind of activity. The sensors can be a GPS, altimeter, depth gauge, pedometer sensor rhythm, speed sensor, heart rate monitor or the like. In the case of gymnastic exercises computerized exercise equipment can be configured to send the data directly on the program made by the user (for example, the so-called elliptical trainer can transmit significantly improved data about the training than the pedometer user etc). Although it is preferable automated collection of indicators related to physical activity, p is Lisovets, it also provides a user interface for manual input of data on physical activity. In this respect, the simulator, such as a treadmill, elliptical trainer, stationary bike or power trainer with a set of weights or springs, may be equipped with a communication interface for communication with the system described in this application, for transmission to the external physical activity indicators in the specified system and receiving data from said system, and may further comprise a processor configured to treatment received from the system data required for automatic regulation of the exercise programs on the simulator, consistent with the goals, loads or other tasks for the specified user. Data on lifestyle, such as diet, Smoking, alcohol consumption, etc. can also be collected and used to calculate estimates of health status. According to one implementation variant of the user can be used barcode scanner bar code or radio frequency identifier (RFID) to collect data on the consumed food, which are then passed to the remote system, such as server 180 or the website associated with the server 180, in the form of indicators, such as daily intake of calories, fat and salt. In particular, the specified system is rather based on the use of these data, transmitted by the user, while other data can be obtained through the data network with the appropriate permissions and access rights.

Data on physical activity and lifestyle are tracked in a long time, and when calculating their impact on the health assessment algorithm deterioration, as described in more detail below. In addition, physical activity that occurred in the distant past, has reduced a positive impact on the health assessment. Preferably, the weighting coefficients used in the algorithm for calculating the assessment of health status, governed for some time in accordance with aggravating component that is used to reduce the relative importance of the indicators used in the calculation. Aggravating component may have a weight value, but may also contain equality that takes into account at least one parameter, in particular related to the user, such as weight or range of the user's weight, age or age range, any medical condition known to the system, and any other indicators that may be known to the system, or curve whose shape reflects these figures, so from this curve could be read mn is an increase as a function of the values delayed along the axis for the specified user. Thus, aggravating component may reduce the relative weighting of the indicators used in calculating the assessment of health status for the first user, otherwise than for the second user, for example, if the first user has a first age, or first age range and the second user has a second age or belongs to the second age range.

Central system, preferably, the database and website, which can be placed in the specified database, for example, the server 180 stores data about each user and the assessment of its health and related indicators and their trends over time. Data storage can be arranged in a known manner, in which sensitive data is stored regardless of the identity of the person.

Then calculated the health assessment for each user is processed depending on the system, group, or individual user profile in the Central system. Depending on the settings of the user profile specified health assessment and related trends can automatically trigger a variety of actions. For example, can be carried out: start the machine the ical alarm; the initiating user feedback, such as the daily update e-mail; sending automated settings of motivation, warnings, and/or goal setting, selected to facilitate the achievement of goals; adjusting the exercise program; or automated referral to a specialist for a medical examination.

Also provided for assessment of the health status of the user to a specified group of recipients via a communication portal. The group of recipients may contain other selected users of the system (for example, friends and family members)to assess the health status of selected users can be compared with the assessment of the health status of members of other groups. According to other variants of implementation, all users can see the evaluating other users, or a group of recipients can be specified as a specific sample for medical insurance, so that could be defined price quotes for individual insurance. Other embodiments of the present invention defined by the scope of protection.

Figure 2 schematically shows a block diagram of the proposed method according to one implementation variant of the present invention, intended for examination of the individual (for example, the patient or the human isolates) to generate an assessment of the state of his health. At step 210, the user initiates the process of collecting, processing and publishing-related health data. For example, a user using a portable electronic device (e.g. smartphone or portable computing device) selects a software application that launches the program, executable by a processor of the specified device, or the user may access a web page on the Internet, codes which are executed by the remote processor and serve requests the user's local device. The identification module prompts the user to identify themselves and confirms the authenticity of his identity. This can be achieved by prompting the user to enter his name and password, or other means, such use of the device to read the fingerprint, the keychain transmitter, encryption, or other mechanism providing the identity of the user. According to another implementation variant, if the user accesses the system via a personal electronic device, identification information may be stored in local memory of the specified device, and the access to confirm the identity of the user can be obtained automatically.

At step 220 executable by the processor module collecting data which may prompt the user to enter relevant health data, the various indicators. According to one implementation variant, at least one indicator is transmitted automatically to the communication subsystem 125. Indicators can contain information about the user's weight, height, age and physical activity. Such measured health indicators are internal indicators of the user. The weight and height of the user is provided with information about the current health of the user. Information about physical activity corresponds to the amount of exercise performed by the user. This information is an example of a measure of physical activity, which is an external indicator of the user. For example, the user can enter information about their daily physical exercises, such as the amount of time spent by the user on the exercise and the type of these physical exercises. If the user, for example, went to the gym and worked out on the stationary bike for thirty minutes, he enters into the system. Information about the physical activity of the user includes information about actions that the user performs to improve their physical condition.

Weight, height, age of the user and information about physical activity what are some of the indicators which may be collected information, while the system may collect and process the numerous other indicators that may indicate the health of the user. For example, these indicators can contain levels of blood glucose, blood pressure, data on the chemical composition of the blood (e.g., hormone levels, levels of important vitamins and minerals, and the like), cholesterol levels, data on immunization, pulse rate, oxygen content in the blood, information on food consumed (e.g., calories, fat, fiber, sodium), body temperature, which are only some of the possible non-limiting examples of indicators that can be collected by the system. To calculate the assessment of human health can be used in a variety of other indicators that indicate the health of a person and that can be reliably measured.

At step 230 retain the collected information on the health status indicators in the storage device. At step 240 the weighing module reads from the storage device weights. These weights can be multipliers, which are used to increase or decrease the relative value of each of the health indicators. Weight is the second factor is assigned to each indicator of health, as shown in the formulae given in this application. Weights are used to control the relative values of indicators of health status. When calculating the assessment of the health of the users some of the indicators of health status are more important than other indicators. Accordingly, the weights applied to the indicators of health status and thus increase or decrease the relative influence that each indicator has on the calculation result of the evaluation of the health status of the user. For example, the current weight of the user's body may be more important than the amount of exercise performed by the user. In this example, the specified measure the weight of the user can be enhanced by assigning high weights. At step 205 weighing module applies a read from the storage device weights to the collected values of indicators of health status to obtain weighted values of indicators of health status. The weighting factor may have a value of zero, if a particular indicator does not affect the health assessment. The weighting factor may have a negative value for use in some algorithms.

After s is taking the weighted indicators on stage 260 calculates the evaluation of the health status of the user using executable by the processor assesses module. Evaluating module combines the weighted indicators in accordance with the algorithm. According to one implementation variant, the health assessment is an average of estimates of health status based on body mass index (BMI) of the consumer assessment of health based on the physical condition of the user minus twice the number of years that a user is under the age of 95 years of age. Below is the formula of the algorithm for this example:

Assessment of health status = ((Assessment of health status based on BMI + health Assessment on the basis of physical condition)/2)-2*(95 - Age).

Assessment of health status on the basis of body mass index user has a value between 0 and 1000. Assessment of health status on the basis of body mass index based on body mass index (BMI) of the user, which is calculated based on the weight of the user and its growth taking into account how the body mass index of the user deviates from the accepted value of body mass index in healthy humans. Chart or formula can be used to normalize the information about the body mass index of the user, so that can be combined heterogeneous information. Then choose the target value of body mass index, which prescribe the maximum value of points (for example,1000). The higher the body mass index of the user deviates from the target value, the less he is awarded the points. Assessment of health status on the basis of the physical condition of the user based on the physical activity or training of a person. According to one implementation variant specified score represents the sum of the hours devoted to physical exercises (i.e. the amount of time during which the user receives physical activity), over the past 365 days, and every hour is linearly added over a specified period of time, so recent physical activity is assessed below. The resulting sum is multiplied by two and is limited to 1000. This normalized information about the physical state can be combined to obtain an estimate of health. Then choose the target daily average value of physical activity and assign it the maximum number of points (for example, 1000). The user is awarded fewer points on the basis of how much less he trained compared with the target value.

According to another implementation variant, the health assessment determined from multiple suboceanic, which are supported in parallel in addition to the evaluation of health status on the basis of body mass index and evaluation of SOS the sustainability of health on the basis of physical condition. Similarly, assessment of health status can be determined using this information in combination algorithm, as described above, using different age adjustments or without the use of age-related adjustments.

Internal medical data are processed to determine a baseline assessment of health status. External indicators, such as, for example, indicators of physical activity, are processed to determine the value that is assigned to pool health and the premium pool. Value, preferably expressed in MET-hours associated with physical activity, is added to the pool of health and to the premium pool. Premium Fund is used daily aggravating factor. Any excessive deterioration, which may not be accepted the award pool is deducted from the pool of health. The amount of the impairment is determined depending on the size of the pool of health and bonus pool, so to maintain a high level pool health and the premium pool requires increased effort. The value of pool health process in combination with the estimate derived from the internal health indicators, to calculate the total value assessment health status. This treatment can be carried out the way, which was used in the above-described embodiments, implementations, or it may include the use of different indicators and weights. According to one implementation variant, the value of the pool's state of health is a logarithm or other aggregate function that is used to accumulate the corresponding values over time, so that only the most recent activity is considered to be fully effective for the pool health/premium pool. The example user interface showing the health assessment, resource health, and some other measured parameters (it should be understood that many of them simply are combined to form estimates, shown in figa and 3b. On figs shown fixed various Sobieski and their trends.

As is commonly believed, MET-hours associated with the consumed calories, divided by the body weight in kilograms, ie, 100 calories expended by a person whose weight is 50 kg, match 2 MET-hours. This figure represents the normalized energy" and allows you to apply the proposed system to users with different weight. According to this method, the pools may have the same size for each person, because the energy expended to normalize is carried out for a specific person on the basis of the weight of his body.

According to one implementation variant, each person is assigned a pool of health of 300 MET-hours and premium Fund of 60 MET-hours.

When someone performs a physical exercise And the pools are updated as follows:

H=min (H+A*alpha, 300),

B=min (B+A*(1-alpha), 60),

where N is the assessment of the pool of health In the assessment of the premium pool, And the number of MET-hours corresponding to the specified physical exercise, and alpha system-wide component (selectable between 0 and 1), which determines the proportion of the contribution of the specified physical exercises in the respective pools.

The contribution of the specified physical activity pool is divided between health status and the award pool. Any excessive physical activity in MET-hours in excess of the ceiling of any pool shall be cancelled. Daily impair the value of D is applied to pools as follows:

D=f(H,)

In=In-D

If<0:

D=D+

In=0

If D<0:

D=0.

The deterioration is fully applied to the premium pool, and if the bonus pool is empty, the remainder is applied to the pool of health. According to this implementation variant none pool is not reduced to zero.

The system comes to an equilibrium, if And equal to f (N, V), i.e. if the average daily activity corresponds to a mean value of daily deterioration. Function (N, In) is highly nonlinear relatively N. and B. essentially, you want cullinane less effort to maintain a small pool, and superlinear more effort to maintain a large pool. You must ensure that the average person will be able to support, for example, pranabananda pool health status (150 that corresponds to the estimate 500), while to maintain full pool health status (300, which corresponds to the evaluation of 1000) will require far more work (which is usually on the shoulder only professional trained athlete). On fig.3f model shown buffered pool and life assessment of health status in a time-dependent, reflecting physical activity, changing in the range of 11.5-16 MET-hours per day, with two free days per week. To support the evaluation of 1000 full resource health will require physical activity of 30 MET-hours per day, as can be seen from the plot of the graph in the upper right corner on fig.3f.

Preferably, evaluation of health status based on a weighted combination of the coefficients of the health status and the list of exercises for a particular person for some time. Factors health can evenly be updated by the user. For example, after each event, the user may led information related to health, which monitors and processes the system. The user can update this information after a meal, after exercise, after weighing, etc. In case of registration of physical activity/event sensor, portable device or the like, captured/calculated values can be automatically loaded and used to generate an updated assessment of the health status. For example, can be used for feedback, showing the effect of specific exercises while running or exercise of the user on the fitness equipment, and the like, according to some variants of realization of the specified feedback can be provided to a system administrator, such as an instructor, and in this case, the instructor determines that the user has exceeded a certain threshold (which due to various health conditions of the user can be different in relation to the assessment of the health status of a specific user or in relation to other available data). Respectively, related to health data can be updated in near real time.

The user can also update twice a day, once a day or with another frequency. In addition, assessment of health the article can be based on the average information for a certain period of time. Physical activity, for example, can be averaged over time (e.g. week, month, or year). Averaging the data over time reduces the noise assessment of the health status caused by the scatter of the data. The periods in which the data was unusually high (for example, if a particular person has successfully completed a number of exercises in a short period of time) or atypical low (for example, if a person due to illness did not receive any physical activity during the week), does not have a significant impact on the health assessment when it is averaged over a certain period of time. Information related to health status, can be stored in a storage device or in a database accessible to the processor.

Stored data can also be used to predict future assessments of health status for the user. The prognostic module can analyze past data (for example, preferences associated with exercise, eating habits, etc.) for extrapolating the prognostic assessment of health status on the basis of the assumption that the user will continue to act in the predicted way. For example, if the data indicates that the user performed the exercise for one hour every day during the previous thirty days, the prognostic module in accordance with the prediction algorithm may predict that the user will continue the execution of the specified exercise one hour during each of the next three days. Accordingly, the evaluating module can calculate the predicted health assessment at the end of the next three days on the basis of information received from the prediction module. It also may improve the prognosis in other activities. For example, the system may offer a more intense level of physical activity or exercise to the user, which has a high health assessment, but based on past experience may recommend to skip a few days to recover. In addition, the system may encourage the user to maintain the rate of physical activity or to change behavior. For example, the system may send the user a message indicating that if the user increases physical activity for a certain amount of time, the health assessment may be increased. This may provide an opportunity for goal setting for the user, aimed at improving health.

Use of estimates health enables relative comparisons of the health status of the user with the health drugog of man even though what each person can have their own individual characteristics that, in General, very difficult a direct comparison. For example, the first user (User 1) may have a completely different body shape or to perform completely different physical exercises compared with the second user (User 2), resulting in a direct comparison of the relative health of each user is inconvenienced. Use of estimates health allows you to do a comparison of these two users with relative ease. In one example, the User 1 has a weight slightly greater than normal, resulting in the evaluation of the health status of the User 1 is reduced. However, the User 1 together with that has a large number of physical exercises and thus increases the overall evaluation of all health. In contrast, User 2 has the ideal body weight, which contributes to improving the assessment of health status, but it runs very small amount of physical exercise and thus reduces the assessment of their health status. User 1 and User 2 are completely different from the point of view of their health status indicators. Accordingly, it would be very difficult to evaluate and compare the relative who passed the health of the User 1 and User 2. According to the present invention, the information related to some of the health indicators collected from the User 1 and User 2, is used to calculate a generalized assessment of health status. Comparison of assessments of the health status of the User 1 and User 2 facilitates the examination and comparison of the health status of these two users even though they are completely different people and have different habits. Thus, assessment of health status is of great importance because it provides the ability to compare the relative health of the members of some group to other parties (such as employers, insurers in the health insurance) to assess the health of a person. On fig.3d and 3E show examples in which presents a table (current) and graphics (historical, current and predicted) evaluation of different users. As shown in figa, Catherine may exceed user (Andre) estimates that, if he won't change his way of life and will not improve their performance. On fig.3d shows the effect of the algorithm deterioration affecting the assessment of the health status of the given user ("Andre") and the people he identifies as his friends. As can be seen from the drawing, the current health assessment uses the user Andre is set to 669, therefore it is between friends Irene (health assessment is 670) and Halley (health assessment is 668). The algorithm deterioration affects all estimates of health status, shown in the screenshot on fig.3d, as indicated in column "Δ1 Day." More specifically, most of the friends Andre have assessment of health status, reduced by 1 point because of the "lack of physical activity". No entered data is for the processor the basis for the execution of the algorithm deterioration to define "inactive" status for a given user. Day action specified status as per shown on the drawing algorithm of degradation for the majority of users leads to a decrease of 1 point per day and reduce by 5 points per week. In addition, the algorithm deterioration may have narrowed, nonlinear effects on the overall health assessment.

As shown in the drawing, the user Andre showed moderate activity, registered in the storage device to which the system has access. The result indicated moderate activity is processed and leads to daily change (Delta), which is positive and which counteracts the effect of the algorithm deterioration. Consequently, Andre can wee the et, like his friends, who have access to its published assessment of health status that it has increased its score from 667 to 669 in one day and from 662 to the current value in the past seven days in the "moderate activity". In addition, the forecast is calculated using the basic algorithm and data extrapolation on the basis of new information (i.e. received data) to increase the assessment for another 5 points. On the other hand, due to the low physical activity, but through proper diet Halley during the same time period decreased their score by 1 point in the last day and a total of 1 point in the last 7 days, in addition, it forecast in danger of losing even one point, if this trend will continue. Also, Halley provided feedback through the execution of the algorithm and output through data provided by the system, which may encourage increased physical activity. On the other hand, Irene exhibits no physical activity and does not comply with proper diet, which leads to rapid changes in its current state assessment of health and long-term predicted impact on its valuation. In addition, the specified feedback can be provided to users and their friends or members of a user group that is United by a common test, etc. for POPs, the project of individual and group motivation, aimed at exercise, proper nutrition, etc.

In addition, assessment of health status indicates the relative health of a person, without disclosing the underlying data used for its calculation, which may constitute confidential information. For example, the user may be awkward to disclose information about their weight, age or the amount of time they spend on physical exercise, other people or communities. People can embarrass the possibility of sharing information about their weight or the fact that they don't actually go to the gym. However, due to the fact that the health assessment is formed by multiple factors, the main data used for the calculation of the evaluation, remain private. This feature facilitates the collective use of the health status of a specific user, because individual users are not required to disclose personal information about yourself. For example, a person may weigh a bit more than normal, but he frequents the gym. Accordingly, this person can get a relatively good assessment of health status. Despite the fact that particular person may not wish to disclose the information the Oia about weight however, it may disclose your health assessment, which provides information about the relative health without describing specific details. Internal medical data (e.g., weight, height etc) and external indicators of physical activity (e.g., duration of exercise, the frequency, intensity, and so on) are converted to the masked composite numerical value. Masked numeric value is published, while the information collected related health indicators and external indicators of physical activity remains private. The main internal health indicators and external indicators of physical activity is protected in such a way that a third party cannot determine these figures are based on the numeric value assessment health status. This approach ensured due to the fact that the figures can be changed in many different ways, and yet the numeric value assessment health status may be the same (for example, people who have a lot of weight, which is often visited a gym, can have the same assessment of the health status of people, the weight of which does not exceed the norm, but not very often exercise). Thus, knowledge of only one numeric value is in the evaluation of health does not disclose exact figures, related to the health of a particular person. Accordingly, despite the fact that the basic statistical data on the health status of masked, however, the health assessment can be used as a comparative evaluation to indicate the status of human health in a variety of applications.

After calculating an estimating module estimates the health of the user at step 270 publication module reads from the storage device assigned to a group of recipients, which permitted assessment of health status. The group of recipients may include friends or relatives of the user, fellow sports team, employers, insurers, etc. On stage 280 publication module informs the assessment of the status of health assigned to the group. If information must be disseminated in a group of friends, it can be published in the portal of the social network based on the Internet, where access to data is limited only by the appointed members of the specified group.

Data on health status indicators and health assessment can persist for a long time in storage device or another database, so the user can track their progress. User can generate charts for the Tserovani progress and analysis with the aim of improving lifestyle.

In addition, can be identified trends that contribute to the diagnosis in case of medical problems and/or to improve nutrition. For example, if a person's weight continues to increase despite equivalent or increased physical activity, the system can encourage or offer some medical examination (for example, examination of the thyroid gland, the presence of pregnancy) to determine the cause of an increase in body weight.

According to some variants of the implementation of a large part of the system is located remotely from the user, and the user accesses the system via the local user interface unit. For example, the system can be made on the basis of the Internet, and the user interacts with the local user interface device (e.g., a personal computer or a mobile electronic device)which is connected to the Internet (for example, through a wired/wireless communication network, to exchange data with the specified system based on the Internet. The user through the local interface device gains access to the system based on the Internet, in which a storage device and software modules remotely manage and communicate with the local device is through the Internet. The local device is used to transmit data to a remote processor and a storage device in which data is remotely stored, processed, converted to a health assessment and then communicated groups are assigned by the Internet portal with restricted access. According to another implementation variant, the system can be mainly located in the local unit in which the data is locally stored, processed and converted to a health assessment, which is then passed to distribute data portal for remote publishing among designated groups.

The system can be made in the form of platform social network, which executes software modules stored in the storage device and executable by the processor. The system can be implemented in the form of a separate, stand-alone medical-themed" social network or in the form of an application that can be integrated into an existing social network (e.g., Facebook, MySpace etc). The user accesses the home page where he can enter information to specify which information to publish to assigned groups, and to manage the membership of the assigned groups. In the start page, the user is prompted to enter information, unosawa the Xia to the health, for each of the different indicators. The user can specify its own weight, date of birth, height, physical activity and other information related to health status. Then calculates the evaluation of the health status of the user. Found calculated the health assessment report assigned to other users, if they are allowed access to this information. In addition, the user can view information related to the assessment of the health status of other group members. Accordingly, the user can compare your overall health with the health of other members of the group. Comparison of assessments of health with other members of the group can form the members of the specified group motivation for competition to improve assessments of their health status. In the home page can also be represented by other information, such as recommendations aimed at improving health, medical news, information about medications, local events in the sphere of physical culture, medical services, advertising and information about discounts on medical and/or health products and services, the publication of advances in the field of healthy lifestyle or improve health.

According to other variants of the implementation of the health assessment may be SOS is awnym object including evaluation Metric model of health status and evaluation of the Model quality of life. The Association estimates, based on various models, provides a more holistic examination of the health status of the user. Evaluation Metric model of health assesses the health status of the user based on the relatively easily measured indicators (e.g., age, sex, weight, etc. and compare their numerical values with acceptable models of population studies. Model evaluation the quality of life focused on self-assessment by user, quality of life, measured on the basis of responses obtained in the process of the questionnaire (i.e. the system takes into account a private examination by the user of their health and quality of life), because there is a correlation between how people "feel" their own lives and the real measured by the state of his health. The combination of estimates based on these two models, which will be described in detail below, forms a more meaningful and comprehensive picture of health.

Evaluation Metric model of health based on medical information of a user, such as its history, external signs, physiological parameters and information about the mod who see life, transferred into the system. For example, the system may prompt the user questionnaire to elicit responses (type: Yes/no, choice, numeric input, and the like) or to enable the user to fill in the questionnaire form. Information about the medical history may include the history of medical indications of the user and/or the prevalence of medical conditions in the family user.

Examples of information about the history of the disease may include information such as, for example, hurts if the user is diabetic, are there in his family diabetics, tolerated if the user or his family members heart attack, angina, stroke, or transitional ischemic attack, atrial fibrillation, or irregular heartbeat, whether the user or the members of his family high blood pressure requiring treatment, whether the user or the members of his family hypothyroidism, rheumatoid arthritis, chronic renal disease, liver disease, left ventricular hypertrophy, chronic heart failure, regular intake of steroids, etc.

Evaluation Metric model of health can also be based on the inherent characteristics of the user. The characteristics may include age, gender, ethnicity, height, weight, waist size, etc. in Addition, the evaluation Metric model sosteniendola may be formed on the basis of physiological parameters of the user. Examples of physiological parameters may include systolic blood pressure, complete serum cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides, high-sensitivity C-reactive protein, glucose levels in the fasting and the like, the Entered data may also contain indicators of the lifestyle of the user. For example, indicators of lifestyle can include information about whether the user is a smoker (smoked in past, current, intensity, area and so on), how much exercise performed by the user (frequency, intensity, type, and so on), type of diet (vegetarian, high-protein diet, low fat diet, rich in fiber diet, a diet of fast food, restaurant, home cooking, processed and pre-packaged foods, portion size, meal frequency, and so on). Below are some examples of indicators that can be used for comparison of health indicators of the user models the probability of survival to calculate the evaluation Metric model of the health status of the user.

Predictive models of the probability of survival to a certain age can be used to predict the likelihood that people will strad shall be at least one serious illness during this period of time.

Mathematical models can evaluate the specified probability on the basis of observable population characteristics. Using the observed data on the number of clearly serious diseases, such as stroke or myocardial infarction, these models can generate the probability that a person will suffer one of these diseases during this period of time, based on the number of measurement markers or prognostic factors inherent in these diseases (for example, information about the medical history of the user, characteristics, physiological characteristics, lifestyle, etc. as described above). The time interval between time of measurement of prognostic factors and the target event that is generated by these models is called the probability of survival, although it is implied that not all target events that are assumed, certainly are fatal.

The models of the probability of survival is usually derived from studies generally large populations observed in a long time, usually more than ten years, and statistical data collected during the monitoring target event, summarize and generalize, using mathematical methods. Numerous such models are verified and validated on a large scale and phase is designed periodic updates of their performance using the new data. Examples of well-known models may include: a subset of models, developed and supported by Framinghammer the study of the heart (an extensive bibliography on the results obtained during Remengesau studies of the heart, see: www.framinghamheartstudy.org/biblio); the subset of models, developed and supported by Nottingham University and QResearch (see, for example, J. Hippisley-Cox and others, Predicting the risk of cardiovascular diseases in England and Wales: prospective abstraction and validation of QRISK2, BMJ 336: 1475 doi: 10.1136/bmj.39609.449676.25 (Published June 23, 2008)), the model ASSIGN, developed by the University of Dundee (see, for example, N. Tunstall-Pedoe, and others, Comparison of the prediction by 27 different factors of coronary heart disease and death in men and women according to a Study of heart health in Scotland (SHHC): cohort study; BMJ 1998; 316: 1881), the model of Reynolds (see, for example, the RM Ridker and others, C-reactive protein and improve the prediction of total cardiovascular risk in family history: risk Assessment according to Reynolds for men. Edition 2008; 118; 2243-2251, and Development and validation of improved algorithms for examination of total cardiovascular risk in women, JAMA, February 14, 2007-Vol 297, No. 6), the PROCAM model of münster study of cardiovascular risk (see, for example, a Simple calculation for you is ilenia risk of acute coronary attacks, based on 10-year prospective study of cardiovascular disease in münster (program PROCAM), Edition 2002; 105: 310-315), and the SCORE model (see, for example, Conroy RM, etc., Determining the risk of cardiovascular disease based on the 10-year period in Europe: the SCORE project, European heart journal (2003) 24, 987-1003).

Can also be obtained other risk models. In addition, can also be used in the predecessor model. Model predecessors predict the development of the first condition (e.g. high blood pressure), and the development of the first status is prognostic for the development of the second state (e.g., heart disease). Known models that, for example, generate estimates of the probability of developing diabetes or high blood pressure, which are two important indicators of lethality. For example, a high probability of developing diabetes within five years independently increases the likelihood of serious cardiovascular disease in the next ten years. Can be used several of these models predecessors, and the use of which leads to a more accurate metric risk models, but more importantly, also leads to a possible decrease in the risk of mortality by a clear modifiable aspects of lifestyle./p>

The traditional model of the probability of survival have some initial limitations that arise from the procedures used for their construction. When deriving such models, researchers find a compromise between accuracy and ease of use. Inductive model, i.e. the model obtained directly from the data, with labor includes all possible indicators. The reason for this partly lies in the fact that all indicators of a particular disease is known, but also partly in the fact that the measurement of some well-known indicators may be difficult or costly. In fact, some well-known markers of risk, such as genetic factors, often not included in these models. Thus, some potential and known prognostic indicators can be excluded as covariate when building this model survivor.

Construction of models of the probability of survival exercise using data collected from some population, and thus summarize and generalize the parameters of morbidity and mortality for the population examined. However, such a model can be contradictory when compared with risk estimates derived from other populations. If the model is applied to a population that differs from the population, on the basis of the research is Finance which was built the model, she often underestimates or overestimates a particular risk, because often considered only a few indicators, and also because other relevant indicators, which are absent in this model, could show significant differences between these two groups.

Considering the above, along with the main probabilistic logic, suitable combination of models built for several different populations, will generate improved prediction of risk compared to a single randomly selected model, and therefore will be more reliable in assessing the risks for the population as a whole. In addition, from the point of view of mathematics, in accordance with the General assumptions, some ways of combining models, called strengthening of predictors can improve the accuracy of composite models. In fact, the increased number of models with the correct application allows you to build a model with accuracy, which at least corresponds to the most accurate model in the strong set.

Accordingly, the evaluation Metric model of health can be calculated by comparing information about health indicators user models the probability of survival. Evaluation, preferably in the range from 0 to 1000, with an upper limit corresponding to a wonderful comprising the human health and a lower limit, denoting a weak state of health, can be obtained from two-stage process. First, the total probability of survival is obtained from the combination of the probabilities of survival generated by individual models of the probability of survival as described above. Secondly, the resulting probability of survival, which is a numerical value in the range from 0 to 1, convert using parametric nonlinear displaying functions in the range from 0 to 1000. Parametric mapping function is configured in such a way that it was linear and had a great inclination in the region typical of the probabilities of survival and asymptotically oposals in the low and high ends of the distribution of the probability of survival. Display function is designed for the harsh reactions to changes in the typical region of the probability of survival.

As described above, the health assessment can be made from estimates of the Metric model of health, and assessment of Model quality of life. Assessment according to the Model of quality of life is formed based on the user's answers to a series of questions of the questionnaire. The system can contain several different questionnaire questionnaires, generally containing a small number of questions. The type of questionnaire the questionnaires and the type of questions presented to the user, m is able to be made on the basis of indicators of the health status of the user (i.e. the age of the user, other data from the medical history of the user, and the like). A specific questionnaire the questionnaire can be generated and presented to the user based on the user information, which is known to the system. Questions may be accompanied by appropriate choice questions, which the user may enter/mark on the form without entering a user in any form of additional text that facilitates the choice of answers. Can be used with other types of responses (e.g., in the form of evaluation by the user in the range from 1 to 10 the truth of a certain proposition). In the following list provides sample questions (in random order)related to the number associated with the health condition of the parties, the quality of life that can be used in the questionnaire questionnaire system.

Sample questions:

- How do you rate the quality of your life?

- How do you rate your overall health?

- How much do you enjoy life?

- To what extent do you feel your life is complete?

- How well are you able to concentrate?

- How safe do you feel in your daily life?

- How healthy is your physical environment?

- Are you satisfied with your appearance?

- To what extent you have the ability to carry the Oia their leisure time?

- How much do you need any medical care, in order to properly conduct its daily life?

- How long has your physical activity been restricted because of your General disorders or health problems?

- You need help with your individual needs because of problems with health?

- You need assistance with the realization of your daily needs because of problems with health?

- You are limited in any way in any activities because of any of the main deterioration or problems with health?

How true or false is each of the following statements:

- It seems I get sick a little easier than other people;

I also as healthy as any other person I know;

I feel that my health will deteriorate;

- My health is excellent,

- Do You suffer from any of the following common ailments or health problems that limit your physical activity?

Arthritis or rheumatism;

- Pain in the neck or back;

Cancer;

- Depression, anxiety or any emotional problem;

- Blurred vision;

- Fractures, damage to bones/joints;

- Hearing impairment;

- Respiratory impairment;

- Difficulty in walking;

For the past 30 days, on how many days:

- Your physical health not good?

The pain prevented you to do the usual activities such as self-care, work or recreation?

- Did you feel the longing, sadness or depression?

- Did you feel the anxiety, tension or irritation?

- You felt that not enough rest or sleep?

- Have you felt very healthy and full of energy?

You been very nervous?

- You felt so depressed that nothing could cheer you up?

- Have you felt calm and serenity?

- You felt a lot of effort?

- You could feel dismal and sad?

- Did you feel tired?

You felt happy?

- Did you feel tired?

- How satisfied are you with:

Is your sleep?

Their ability to perform their daily activities?

Is your health?

- Being?

- Your personal relationships?

Is your sex life?

- The support of their friends?

- The conditions of your home?

- Access to health care?

- Own transport?

You were limiting any of the following because of his health?

- Vigorous activities such as running, lifting tagaste is, participation in sporting competitions;

Moderate activities such as moving a table, pushing a vacuum cleaner, bowling or playing Golf;

- Lifting or carrying store-bought products;

- The rise of several staircases;

- Climb one flight of stairs;

- Bending, kneeling, or shear;

- Walk to a distance greater than one mile;

- Walk at a distance of several blocks:

- Walk around one quarter;

- Taking a bath/shower or dressing.

The list contains only examples of questions that can be offered to the user. The user's answers to the questions assigned to the specified values. For example, each of the selected responses may be set to a specific value, and on the basis of the full response can be generated assessment. In addition, different questions and different answers can be weighted differently, because some of the issues or the importance of the answers may be obvious predictors of health status of the user. The system can also assign a value based on the user's response to a combination of issues, as some combinations can be predictive in relation to health. Accordingly, when evaluating the user's answers to the questionnaire the respondents which can be obtained evaluation Model of quality of life. Preferably, the evaluation Model of quality of life is a numeric value in the range from 0 to 1000.

The health assessment is calculated as a weighted average of the evaluation Metric model of health status and evaluation of a Model of quality of life. The health assessment can be presented to the user. The health assessment can be presented for example in the form of numeric values in a graphical form (i.e. in the form of a meter, gauge or slider) or in the form of their combinations. As shown in figa, assessment of health status is represented by a combination of numerical evaluation 302 and the slider 304. On the scale can also be applied to color coded to indicate the evaluation of the position of the slider 306 indicates the user's assessment.

One advantage of the view of assessing health is that there is no need to provide probabilities of survival and initial measurements to the user. Instead, users provide a standardized assessment. Preferably this applies to the evaluation of the Metric model and the estimated Model of quality of life, but it also applies to the corresponding input parameters for the models. This is done mainly for the standardization of all output parameters, in the sense that users do not necessarily know n is how good or bad the maximum value of the specific input parameters; in any case, the high evaluation of any input values lead to higher overall values of the estimates of health status, and low estimates of the input variables lead to a lower overall value assessment health status.

In addition, another advantage of standardized assessments of health is that users can compare their assessments of the health status with the assessments of other users. This provides a comparative basis (for comparison with friends, staff, etc) relative to other users. Such comparative assessments can be part of a gaming system component, in which the user competes with other users, as will be described in more detail below. Aspects of the system can be used to motivate the user of this system, for example, comparing scores among selected by the user groups, the comparison of individual assessments within the configurable distributions of subpopulations, tracking estimates over time and across tinukoy purposes, among other things. As shown in figv, numerical estimation 302 and graphical evaluation 306 users in combination with the range of estimates 308 group (for example, around the world), so that the user can see his score is compared with other estimates in the specified group. The user is teli can extend's incentives to enable comparison of estimates of health status between users, which may differ substantially at least one of several specific input parameters, such as age, weight, and pre-condition risk. The system marks the improvement of changing parameters of the user, in particular components of lifestyle, and these improved estimates stimulate the user. This ensures fair competition between users, for example, parents and children by assessing their health status. According to one aspect of the health assessment provides adjustment between users with different characteristics, and thus creates a kind of handicap in some types of sports. As shown in figs, evaluation 306 of the user is compared with estimates 310a-e members of the selected user group or his friends. As shown in fig.4D, private medical data of the user (for example, medical data, presented as part of the Metric model of health), can be compared with those of other users in graphical form without disclosure of the main actual value. The graph 312 shows the levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL)cholesterol, systolic blood pressure (sBP), diastolic blood pressure (dBP), body mass index (BMI) and level of the glucose on the blood of fasting (fBG). Assessment of the user represented by line 314, each of the estimates of the friends of the user is represented by a single point 316, and also shows a block 318 distribution for a large group of the population (for example, for the population of Switzerland). Thus, the user can compare their own performance with a group of friends and an average value for a large group of the population.

Users can enter data into the system during the event (i.e. during exercise, food intake, blood pressure, etc. and to see the resulting update of the assessment of their health status in real-time. The system may enable the drill-down function, providing the opportunity to observe various aspects of the evaluation component of health, including monitoring for a long time and trends of all assessments; this system also provides the ability to set goals for a variety of estimates.

As a usage example, after registration in the system (for example, when the initial use of the system) the user is prompted to enter the details of his medical history. The user is also requested to answer questions complete a Questionnaire about quality of life, selected by the system for this user on the basis of its history and entries of the user is. After registration, users periodically offer short subsets (3-5 questions), individualizing questionnaire about quality of life, to update their responses and tracking changes. Users can enter the data for the Metric model of health at any time, and the system prompts the user for values that have not been updated for some time. Entered data for the Metric model of health can be obtained automatically by the system by accessing a range of digital measuring devices integrated into the system (for example, the system may include a mobile electronic communication device, such as a smartphone, which is connected in a wireless manner with a measuring device such as a device for continuous monitoring of glucose in the blood, so that the indicators can be measured, transmitted and stored by the system). The data may contain the weight, the content of glucose in the blood, physical activity and other indicators. The system may also include a monofunctional or multifunctional digital measuring device. In the case of health indicators, which are using a home measuring device is associated with great difficulties, such as the concentration of lipid savor the TCA blood, users are invited to inform the relevant data only during system configuration (for example, once a year, and together with regular physical medical examination user).

To eliminate false estimates system may contain several algorithms that determine the validity of user input. How validation can be selected within a wide range, from simple detection of statistical outliers and until MDX formulas likelihood estimates. When the system detects a possible incorrect value, it indicates this and asks the user to confirm the entered value or enter a new one.

The system can generate all their assessments, even in case of loss of at least one of the entered parameter. It corrects the error by adding the missing value or multiple values using various statistical methods that range from simple obsentities techniques to use sophisticated statistical models, embedded computing platform. However, whenever the entered data include imputed values, the system clearly marks all fixed assessment and periodically warns the user about the need to introduce the missing Yes the data. The system may also provide for the establishment of a valuation model in which the user can temporarily adjust their performance, so he can see how the change of some indicators (for example, when lowering the weight) affects the final score.

The system may also submit recommendations to users to perform certain actions, aimed at improving the assessment of their health status. These guidelines can be extremely individual, if any input parameter is in the area of critical values, and more General, if any input parameter is out of its optimal range.

As described above, the health assessment can be used as part of the game or competition aspect of the system. The competitive aspect increases the exciting side of the system for the user and encourages the tendency of the user to the continued use of this system. The competitive aspect may be in the form of higher levels on the basis of achievement, competition with other users (for example, in some categories), and/or perform difficult exercises. "Level" is a General lack of progress, the Levels can gradually increase and increase as you receive points for the activity.

Points for activity is ü can be obtained for performing numerous actions, for example, for the time spent on exercise (e.g., training)for improving the assessment of health status, improved body mass index, participation in the deliberations of the system (for example, the system may be a social network based on the Internet platform, and participants can be prompted discussions or classes to learn the skills to maintain the physical form). The user level can be shown in the user's profile and on the forums, so other users can see the level of each other. The status level of the user may also provide access to specific topics, the distinctive features of the system and functional means or awards (e.g., brand labeling).

Users can also compete within the League system. League formed from groups of users, and users within the League can compete with each other (as part of a team or individually). The League can compete for a limited period (e.g. monthly), and the League can be assigned based on the user level (user level as described above), type of exercise performed in the League, and geographic area. For example, some particular League may be "bronze" (the level of the HB) "mountain-bike" (sport) League of the "Big Zurich" (region), and the success of the user in the particular League is measured by the distance and height (measured values). Thus, users bronze level living in Great Zurich who are interested in mountain Biking, can compete with each other in this League. Restriction League specific regions allows users to feel when they take joint participation in a common event, and, in addition, it additionally provides users the opportunity to meet each other (for example, joint group training). One problem associated with a single huge international League, is that this League can appear to some users faceless crowd, participation in which is meaningless (some members of the League are competing with other members of the same League and live on opposite continents and separated by language barriers any group or team activity). Limitation leagues concrete framework levels arranges the playing field for users with specific skill levels. Values that need to be measured to characterize League, for example, may include the distance (horizontal, vertical) and the duration is made f the physical exercises. Users can also form groups inside the League.

Team League work the same way as the League above, but they are ranked on the basis of their common characteristics. Team reinforce the collective aspect of participation in physical activity. Teams may be of a fixed size (for example, 2, 3, 5, 10, etc. users).

The system can also prompt users to perform difficult exercises or tests. For these exercises can be specified run time. The aim of testing can be, for example, improvement in the scores (normalized) state of health, the achievement of certain performance sports activity (e.g., total distance, total ascent and the like), or perform a sports activity in a specified period of time (for example, passage of a given route at a speed of six miles per minute). The test may be open, in which you can participate any user, or limited within a group (e.g. friends, colleagues, social groups, etc). For example, a particular outdoor test can be run on roller skates in new York city on the route along the outer lanes of Central Park and time spent on execution of the specified exercise. Public tests can be generated automatically and the system or system administrators. Group tests can be selected by the members of the group. Tests provide strong's dynamic, stimulating users to exercise. To perform difficult exercises (usually) allocated less time compared to the competition in the League. The choice of route can be arranged by the Council of the organizers. In the first stage, the Council organizers can publish routes on the system platform (for example, website types of social networks); in the second stage, the system chooses the most popular routes (i.e. routes with high user activity) as a weekly test. Validation of the route is carried out by tracking system using GPS. The test site can be limited by a protective fence to prevent dangerous actions while passing the test, such as the passage of the mountain-bike trails with dangerous steep slopes.

The League system and tests provide the user with the opportunity to achieve recognition for his achievements.

Evidence of the achievements of the user can be collected and shown in his profile.

Certificate of achievement in General can be a trophy, medal or award, awarded to the user at the completion of testing and/or for success in the League. Can be used different is Shrine achievements, such as a large number of friends, which was bought by the user in the system (open part), achievements related to time, intensity and amount of exercise performed by the user (the level of participation in physical exercise), achievements, specific sport actions (e.g., distance travelled), achievements related to the frequency with which the user measures its performance (e.g., weight) to improve the system, the amount of reduction in body weight or, for example, the ability to maintain their body mass index. The following list represents a sample set of achievements and actions necessary to get a promotion:

Example list of achievements:

- Applicant: to participate in the public test.

- Experienced candidate to Take part in the 10 public testing.

- Champion: Win the challenge.

- Champion in several sports: Win public test in two different sports.

International applicant. To participate in the public test in two different countries.

- International champion: Win public test in two different countries.

Is a global contender: to participate in the public test on every continent.

- World champion: You is the line public test on every continent.

Other aspects of the systems testing and leagues are that these systems can be linked with marketing. For example, prizes for the winners of the trials can be sponsored by trade organizations. The prize may be relevant to this test (for example, a gift certificate for assessing diet food for the winner of the competition of weight loss). In addition, the routes of the competition can be chosen in such a way as to guide users in some regions for tourism development, or may begin/end at selected locations (e.g., bike race starts in front of the sporting goods store).

One advantage of this system is that it provides users and groups of users reference comparing. These functions allow other groups, such as insurers or employers, to assess the relative health status to identify the risks associated with the health status of each person. Accordingly, users can compare yourself with other people to assess their comparative level of health, for example in the group of friends. Insurance companies may use information about the assessments of health to determine the insurance premium for the a ne or group of people (for example, employees of the company). According to other variants of the implementation of valuing health States can be generated for a group based on an assessment of the health status of the members of the specified group. For example, the health assessment can be calculated for the entire company based on the estimated state of health of its employees, so the insurance company may set the insurance premium on the basis of the evaluation of the health status of the entire company compared to other companies. According to other variants of the implementation of the health assessment can be used to assess health professional athletes to determine the actual market value of the specified athlete. Professional sports in athletes invested considerable amounts of money and resources at all levels. For the most part investment decision in a particular athlete take on the basis of past performance the indicated athlete. Other factors may include a history of past physical injuries and the athlete is subjected to a medical examination before it completed the transaction. The health assessment can be used as an indicator of the current health status of the athlete and as a prognostic factor in the future performance of the athlete. If an assessment is and the health of the athlete was low, this may mean that an athlete can get injured or that his physical indicators deteriorated. Accordingly, the health assessment can form the basis for a decision about whether the meaning of the investment in this athlete. Assessment of health status can also be used as a prognostic factor in the outcome of competition between two teams. For example, assessment of the health status of individual team members can be connected to a common assessment of the health team. Comparison of estimates of health status command may indicate the likely outcome of competition between these two teams (for example, the team with the higher score health has a high probability of victory). Such information can be used in game contexts, such as imaginary sports team, or to determine the odds in sports betting. The health assessment can be used for competitions between clubs (for example, competition for the improvement of group health, as well as advertising on the basis of the evaluation of human health, games, TV/Internet etc).

Thus, in a broad aspect, the method according to the present invention can be understood as the collection of information and, related to health status, the processing of such information in the health assessment and publication of the evaluation of health status. The system for implementing the above method may include a computer containing a processor, storage device, and encoding modules, executed by the processor, for collecting, processing and publishing information. The information collected represents the health of the user, in particular as the internal value related to the measured health indicators at least one person, and external values related to physical activity each person (people), such as the operation performed, the type of work activity performed by the specified person, and the amount of physical work associated with the specified employment (for example, sedentary work, office work, in contrast, active, manual labor-intensive), and/or consumed calories/food. Weighting factors applied to specific health indicators to control the relative impact of each indicator on the computed evaluation of the health status of the user. The health assessment is calculated using the processor by combining the indicators in accordance with some is that algorithm. Assessment of health status reported assigned to the group through the portal. According to one implementation variant specified portal is a distributes the information to the forum, created on the basis of the Internet.

In addition, the present invention may differ in the following stages of the method of collection and reporting related to the health of the data on which:

collect information about the health status indicators user,

retain the collected information in a storage device,

keep the weights in a storage device,

process the information gathered by the execution processor code that configures the processor to apply the weights to the indicators related to health,

calculate the valuation of health status using the processor by combining the weighted indicators in accordance with the algorithm, and

reported assessment of health status assigned to the group using the portal.

Proposed in this application the methods described with reference to block diagrams that facilitate the understanding of the basic processes; however, some blocks can be used in arbitrary order, in which event guide the process of program execution, such as object-oriented p is ogramme. Accordingly, the block diagram should be interpreted as examples, so that the software blocks can be used in various different order from that shown on the drawings.

Although the present invention is described on the example of some of the implementation options, it is not limited to the described variants of implementation, but, on the contrary, more broadly defined by the enumeration at any points of the applied formulas and cash equivalents.

1. Implemented using a computer method of processing related to private health data in the masked numeric rating that is appropriate for the publication, containing the steps are:
take in the data storage device, and the received data represent at least one internal medical record and at least one external measure of physical activity of the user,
save received data in a storage device,
keep the weights in a storage device,
process the received data by execution by the processor, configures the processor to
the appropriate application of these weighting coefficients of at least one internal health indicator and at least one external measure of physical activity,
application of whutcha is the future component to the processed at least one external measure of physical activity to reduce the relative weight of the processed at least one external indicators of physical activity physical activity based on at least one factor associated with the user,
convert these processed data obtained by executing additional code processor, and the processed received data is converted into the masked composite numerical value by combining the weighted indicators in accordance with the algorithm, and
automatically publish masked composite numerical value assigned to groups through the portal using code executing in the processor and free from human intervention while maintaining the privacy of received data representing the specified at least one internal medical record and the specified at least one external measure of physical activity.

2. The method according to claim 1, whereby at least one coefficient associated with the user, an age or age range of the user, so aggravating component reduces the relative weight of the processed at least one external measure of physical activity for the first user with the first age, or first age range, otherwise than for the second user having a second age of or relating to the second age range./p>

3. The method according to claim 1, additionally containing a stage, where the average published masked composite numerical value of the user group to determine the group integral numeric values using additional code, executable by the processor.

4. The method according to claim 1, further comprising stages, which are:
take in a storage device data representing at least one external indicator of the lifestyle of the user,
moreover, at the stage of data processing is also performed in the processor code that configures the processor to
application of relevant indicators of weight indicators to the specified at least one external indicator lifestyle, and
application of aggravating component to reduce the relative weight of the specified at least one external indicator lifestyle depending on the specified at least one parameter or at least one coefficient associated with the user,
at this stage of the transformation of the processed received data also includes the execution processor code that configures the processor to merge the specified at least one processed internal medical record, the specified at least one of processing the aqueous external measure of physical activity and the specified at least one processed external indicator lifestyle in accordance with a specified algorithm.

5. The method according to claim 1, whereby the stages of processing, transformation, and publishing do essentially automatically after admission any of the received data.

6. The method according to claim 5, further comprising stages, which are:
transmit the processed received data or masked composite numerical value to the fitness equipment and on this basis automatically set exercise program and
passed from gym equipment in the storage device activity information for inclusion in the specified at least one external measure of physical activity.

7. The method according to claim 1, additionally containing a stage on which track an integral numeric value and provide initiating feedback through execution of code by the processor and without human intervention.

8. The method according to claim 7, according to which feedback is used to alarm the user to initiate physical activity or changes in planned physical activity.

9. The method according to claim 7, whereby the feedback contains a warning signal is sent to the specified person.

10. The method according to claim 7, whereby the phase of the tracking monitor is in time and initiate a warning signal depending on the change specified the CSO value over time.

11. The method according to claim 7, whereby at the stage of initiation feedback send an e-mail message destined to a user, containing instructions about the changes in physical activity and/or lifestyle of the user, to improve the masked composite numerical value.

12. The method according to claim 7, additionally containing a stage where by the execution of additional code in the processor calculates predictive masked composite numerical value that indicates the forecast of the future state, based on past data, using the received user information in accordance with the predictive algorithm and cause initiation of predictive feedback.

13. The method according to claim 1, whereby the step of processing the received at least one external measure of physical activity:
take in the storage device, the measurement results of the number of calories expended during physical activity, and
performed by the processor in the code that configures the processor to:
converting the measured amount of calories in the value of metabolic equivalent load by dividing by the body weight of the user,
dividing the value specified metabolic equivalent load across a pool of state is of health and premium pool moreover, the specified bonus pool has a fixed size, and any split is the metabolic equivalent load exceeding the size of the prize pool, assign a pool of health, and
use daily worsening component to the bonus pool,
at the stage of converting the processed data combine the specified processed at least one internal medical record and the weighted value of the pool of health in accordance with a specified algorithm.

14. System for tracking health, containing:
a communication unit configured to receive data regarding at least one internal medical record and at least one external measure of physical activity of the user;
storage device, configured to save the received data and save weighting coefficients;
the processor is made with the possibility of data processing by execution of the code that configures the specified processor
applying appropriate weights to the specified at least one internal medical record and the specified at least one external measure of physical activity,
application of aggravating component, the implementation of the military with the ability to reduce the relative weight of the specified processed at least one measure of physical activity for physical activity based on at least one factor associated with a user;
while the processor is additionally configured to execute the code to convert the processed received data in the masked composite numerical value using the processor by combining the weighted indicators in accordance with the algorithm; and
the portal is configured to publish the masked composite numerical value assigned to the group while maintaining the privacy of information collected relating to at least one internal health indicator and at least one external measure of physical activity.

15. System 14, in which at least one coefficient associated with a user, is the age or age range of the user, so aggravating component reduces the relative weight of the processed at least one external measure of physical activity for the first user with the first age, or first age range, otherwise than for the second user having a second age of or relating to the second age range.

16. System 14, in which the communication unit is additionally configured to receive data at least one external indicator of the lifestyle of the user, and rocessor made with the ability to execute code for:
applying appropriate weights to the specified at least one external indicator lifestyle,
application of aggravating component to reduce the relative weight of the at least one external indicator lifestyle based on at least one factor associated with the user, and
converting the processed data by combining the specified at least one processed internal medical record, the specified at least one external measure of physical activity and the specified at least one external indicator lifestyle in accordance with the algorithm.

17. System 14, in which the processor is configured to automatically perform the specified processing after receipt of any of the received data.

18. System 17, further containing a remote device of a user, the system is configured to communicate with a remote device of a user during physical activity to receive at least selected indicators from the specified at least one external measure of physical activity.

19. System 14 additionally containing a tracking unit configured to track a compound of numeric values and launched the Oia feedback upon detection of a specified event, associated with tracked integral numeric values.

20. The system according to claim 19, in which feedback is made with the possibility of changing the configuration program to set the planned physical activity for a user or job planned physical activity for the user.

21. The system according to claim 19, in which the monitoring unit is configured to provide transmission of the electronic message to the user with instructions about changes in physical activity and/or lifestyle of the user, to improve the masked composite numerical value.

22. The system according to claim 19, in which the processor is additionally configured to execute the code that configures the processor to calculate a prognostic masked composite numerical value that indicates the future of predictive condition based on past data, using the received user data in accordance with the predictive algorithm, and the specified tracking unit is made with the possibility of initiating a prediction feedback.

23. System 14, in which the processor is configured to processing the received at least one external measure of physical activity performed by the I code, which configures the processor to perform the steps are:
get the results of measurement of the number of calories expended during physical activity,
convert a measured quantity of calories in the value of metabolic equivalent load by dividing by the body weight of the user,
divide the value specified for the metabolic equivalent load across a pool of health and bonus pool, and the specified bonus pool has a fixed size, and any split is the metabolic equivalent load exceeding the size of the prize pool, assign a pool of health, and
apply daily worsening component to the bonus pool,
convert the processed data by combining the weighted inner health indicators and the weighted pool of health in accordance with a specified algorithm.

24. System 14 additionally containing a bidirectional communication channel with gym equipment, performed with the opportunity to:
transfer the processed data or masked composite numerical value fitness equipment;
automatic installation program exercises on the basis of the transferred data or masked composite numerical value; and
receiving at the memory device from the training is the main equipment activity information for inclusion in at least one external measure of physical activity.