# System and method for estimating cardiac output

The invention relates to the field of medical technology and is intended for measurement of blood flow of the patient. According to the invention the indicator, preferably heat, is introduced as an input indicator of some form in the blood stream. The preferred form of the signal with pseudo-random binary sequence. The presence of the indicator of the perceived position downstream in the flow area in the form of an output indicator signal. Cardiac output is then measured in two separate devices evaluation: the local device evaluation and device evaluation trend. The device for evaluating the trend is preferably recursive. It generates its assessment on a longer time interval than the local device evaluation. Both devices assess cardiac output on the basis of frequency transfer functions obtained from measurements of the input and output signals. The invention allows to obtain accurate data about the General trend of the cardiac output and the instantaneous state of a thread. 4 C. and 14 C.p. f-crystals, 10 ill. Description text in facsimile form (see graphic part).

Claims

1. The method of estimating emissions CROs is atomnogo signal form the input signal at the position upstream in the flow area; B) the perception of the presence of the indicator in a position downstream in the flow area in the form of an output indicator signal, characterized in that it comprises a step (B) assessments in the form of a predefined function of the input form and output an indicator signal as the local values of ejection of blood during local assessment and trend values of ejection of blood during the evaluation of the trend in which the evaluation of the trend longer than the time the local evaluation to obtain estimated values of blood ejection, relevant and relatively fast and relatively slow changes in ejection of blood.2. The method according to p. 1, characterized in that the step of estimating the output value of the trend contains step recursive estimates of the output values of the trend.3. The method according to p. 2, characterized in that the step of the recursive evaluation contains the Kalman filtering.4. The method according to p. 1, characterized in that the step of estimating a pre-defined function contains the measurement of the frequency transfer function between the input and output signals for each period, and the measured frequency transfer function of the form input signals for local assessment and for assessment of the trend.5. The method according to values of the frequency transfer function between the input and output signals during each period, moreover, the measured frequency transfer function of the form input signals for local assessment and for assessment of the trend; the choice of the parameters of the model to a predefined transfer function linking output indicator input indicator signal; determining the optimal parameters of the local state in the form of a pre-defined function of the optimization model transfer function and the measured values of the transfer function and the estimation of local values of the blood in the form of a pre-defined output functions, at least one of the optimal parameters of the local state; recursive estimation of optimal parameters of the trend via Kalman filtering of the measured values of the frequency transfer function, and evaluation of trend values of the blood in the form of a pre-defined output functions, at least one of the optimal parameters of the local state.6. The method according to p. 5, characterized in that it further includes the step of initializing step of the Kalman filter, using the optimal parameters of the local state.7. The method according to p. 5, characterized in that it further includes the; is) the definition of the autocorrelation values Shh input signal and converting the autocorrelation values Shh in frequency representation; (B) determining cross-correlation values CFS between the input signal and output signal and converting the cross-correlation values of CFS in the frequency representation; D) calculation of the measured values of the transfer function in the form of a predefined function of the relationship between the frequency-converted cross-correlation and autocorrelation values.8. The method according to p. 5, characterized in that it further includes a step exception of any low-frequency noise of trend output indicator signal before the local assessment or evaluation of the trend.9. Method of assessment of ejection of blood through the flow area of the patient's body containing (A) injection of a heat indicator input indicator signal waveform in the form of a pseudo-random binary sequence (PSDP) at a position upstream in the flow area; B) the perception of the presence of the indicator in a position downstream in the flow area in the form of an output indicator signal; C) the exclusion of any low-frequency noise of the trend of the output indicator signal;the offered functions, connecting the output indicator input indicator signal; D) determining the autocorrelation values Shh input signal and converting the autocorrelation values Shh in frequency representation; (E) determining cross-correlation values CFS between the input signal and output signal, and converting the cross-correlation values of CFS in the frequency representation; F) calculation of the measured values of the transfer function in the form of a predefined function of the relationship between the frequency-converted cross-correlation and autocorrelation values; 3) determination of the optimal parameters of the local state in the form of a pre-defined function of the optimization model transfer function and the measured values of the transfer function and the estimation of local values of the blood in the form of a pre-defined output functions, at least one of the optimal parameters of the local state; And) recursive estimation of optimal parameters of the trend via Kalman filtering of the measured values of the frequency transfer function and the estimation of trend values of the blood in the form specified output function of at least one the current patient's body, containing (A) means for injection for injection of indicator input indicator signal form the input signal at the position upstream in the flow area; B) the means of perception indicator for the perception of the presence of the indicator in a position downstream in the flow area in the form of an output indicator signal, characterized in that it further contains (B) the assessment tool, including a local device evaluation to assess for local evaluation the local values of the blood in the form of a predefined function of the input form and the output indicator signal and a device for evaluating the trend to estimate the trend values of ejection of blood during the evaluation of the trend in which the evaluation of the trend longer than the time the local evaluation to obtain estimated values of blood ejection, corresponding to relatively fast and relatively slow changes in ejection of blood.11. The system under item 10, wherein the assessment tool includes a recursive device evaluation to estimate the output value of the trend.12. System on p. 11, wherein the recursive device evaluation is a Kalman filter.13. The system under item 10, characterized in that more is at the input and output signals during each period, moreover, the measured frequency transfer function of the form input signals for the local device evaluation and assessment device trend.14. System on p. 11, characterized in that the means of measuring the transfer function is designed to measure the values of the frequency transfer function between the input and output signals during each period, and the measured frequency transfer function of the form input signals for local assessment and for assessment of the trend; the local unit assessment is designed to determine the optimal parameters of the local state in the form of a pre-defined function of the optimization model transfer function and the measured values of the transfer function and estimation of local values of the blood in the form of a pre-defined output functions, at least one of the optimal parameters of the local state; the device for evaluating the trend represents the Kalman filter recursive estimation of the optimal parameters of the trend via Kalman filtering of the measured values of the frequency transfer function and estimation of the trend values of the blood in the form of a predefined vichas fact, what local device evaluation connected with a device for evaluating the trend, and the optimal parameters of the local state form parameters initialization state for the Kalman filter.16. The system under item 14, characterized in that A) the form of the input signal is a pseudo-random binary sequence (PSDP); B) a means of measuring the transfer function of the addition is intended 1) to determine the autocorrelation values Shh input signal and convert the autocorrelation values Shh in frequency representation; 2) to determine the cross-correlation values CFS between the input signal and output signal, and converting the cross-correlation values of CFS in the frequency representation; 3) to calculate the measured values of the transfer function in the form of a predefined function of the relationship between the frequency-converted cross-correlation and autocorrelation values.17. The system under item 5, characterized in that it contains means of pre-filtering to eliminate any low frequency noise of the trend of the output indicator signal before the local assessment or evaluation of the trend.18. System for the evaluation of ejection of blood through about the ideal input indicator signal waveform in the form of a pseudo-random binary sequence (PSDP) at a position upstream in the flow area; B) a means of thermistor for the perception of the presence of the indicator in a position downstream in the flow area in the form of an output indicator signal; B) a means of pre-filtering to eliminate any low frequency noise of the trend of the output indicator signal, characterized in that it further comprises D) a means of measuring the transfer function of 1)to calculate the autocorrelation values Shh input signal and convert the autocorrelation values Shh in frequency representation; 2) to calculate the cross-correlation values CFS between the input signal and output signal, and converting the cross-correlation values of CFS in the frequency representation; 3) to calculate the measured values of the transfer function in the form of a predefined function of the relationship between the frequency-converted cross-correlation and autocorrelation values; D) a local assessment to determine the optimal parameters of the local state in the form of a pre-defined function of the optimization model transfer function and the measured values of the transfer function and estimation of local values of the blood in the form of a pre-defined output for recursive estimation of the optimal parameters of the trend via Kalman filtering of the measured values of the frequency transfer function and estimation of trend values of the blood in the form of a pre-defined output functions, at least one of the optimal parameters of the local state.

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