CN114515147A - Physiological monitoring system based on BCG signal and PPG signal fusion - Google Patents
Physiological monitoring system based on BCG signal and PPG signal fusion Download PDFInfo
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Abstract
The invention relates to a physiological monitoring system based on BCG signal and PPG signal fusion, comprising: the BCG signal acquisition system is used for acquiring BCG signals of a human body; the PPG signal acquisition system is used for acquiring PPG signals of a human body; and the upper computer is used for receiving the BCG signal acquired by the BCG signal acquisition system and the PPG signal data acquired by the PPG signal acquisition system, analyzing the two signal data and fusing the analysis result in a nonlinear fitting mode to obtain final physiological parameter information. The invention can improve the monitoring accuracy.
Description
Technical Field
The invention relates to the technical field of physiological monitoring, in particular to a physiological monitoring system based on BCG signal and PPG signal fusion.
Background
The pumping of blood by the heart during the beating cycle causes a corresponding movement of the body, which is picked up by a highly sensitive sensor and traced into a waveform called a Ballistocardiogram (BCG). Since the BCG signal records the body movement synchronized with the heart beat caused by the pumping of the heart, the BCG signal indirectly reflects the heart dynamics and movement state. Analysis of the BCG signal allows for the acquisition of vital signs or physiological parameters associated therewith and possibly the prediction, diagnosis or follow-up monitoring of the associated disease.
In the last two decades, with the rapid development of sensors, electronics, signal processing and analysis and other technologies, the BCG signal detection becomes more convenient, the measurement precision is greatly improved, and the BCG technology has the advantages of being noninvasive, non-contact, capable of continuously monitoring for a long time and the like, so that the BCG signal is applied to qualitative and quantitative research and clinical application in the aspects of heart rate, sleep structure analysis, heart function monitoring and evaluation and the like, and certain research results are obtained.
Photoplethysmography (PPG) is a non-invasive optical bio-monitoring technique that records the change in blood volume in the microvascular tissue under the skin caused by the diastolic activity of the heart by means of a photoelectric technique, and has the characteristics of simple use, no wound, portability, accuracy, real time, repeatability, and the like. With the continuous development of the photoelectric technology, the applications of PPG in the medical field are also increasingly widespread. The PPG waveform not only can collect relevant physiological and pathological parameters such as heart rate, blood pressure, respiration, pulse blood oxygen saturation and the like, but also can be used for evaluating cardiac output, blood volume, whether arteriosclerosis or stenosis exists in an artery, hypertension, diabetic microangiopathy, cardiovascular risk factors and the like.
However, the acquisition of both BCG and PPG signals is disturbed by external factors, such as: although some studies have obtained considerable results by using different algorithms to eliminate interference of individual factors, random control experiments and data support of large samples are required in disease monitoring and diagnosis. In addition, the physiological parameters analyzed by the single BCG signal and the PPG signal have low correlation with the actual physiological parameters, so that the problem of inaccurate qualitative judgment exists.
Disclosure of Invention
The invention aims to solve the technical problem of providing a physiological monitoring system based on the fusion of a BCG signal and a PPG signal, which can improve the monitoring accuracy.
The technical scheme adopted by the invention for solving the technical problems is as follows: a physiological monitoring system based on BCG signal and PPG signal fusion is provided, which comprises:
the BCG signal acquisition system is used for acquiring BCG signals of a human body;
the PPG signal acquisition system is used for acquiring PPG signals of a human body;
and the upper computer is used for receiving the BCG signal acquired by the BCG signal acquisition system and the PPG signal data acquired by the PPG signal acquisition system, analyzing the two signal data and fusing the analysis result in a nonlinear fitting mode to obtain final physiological parameter information.
The BCG signal acquisition system comprises: the piezoresistive sensor is used for acquiring an original BCG signal; the BCG preprocessing module is used for preprocessing the original BCG signal; the BCG signal acquisition chip is used for acquiring the preprocessed BCG signals; and the BCG signal data interface is used for transmitting the BCG signals acquired by the BCG signal acquisition chip to the upper computer.
The BCG preprocessing module comprises: a BCG signal amplifier for amplifying the original BCG signal; and the BCG signal filter is used for filtering the amplified original BCG signal.
The PPG signal acquisition system comprises: a PPG probe for acquiring a raw PPG signal; the PPG preprocessing module is used for preprocessing the original PPG signal; the PPG signal acquisition chip is used for acquiring the preprocessed PPG signal; and the PPG signal data interface is used for transmitting the PPG signal acquired by the PPG signal acquisition chip to the upper computer.
The PPG preprocessing module comprises: a PPG signal amplifier for amplifying the raw PPG signal; and the PPG signal filter is used for filtering the amplified original PPG signal.
The host computer includes: the BCG signal data interface is used for receiving the BCG signals acquired by the BCG signal acquisition system; a PPG signal data interface, configured to receive a PGG signal acquired by the PPG signal acquisition system; the data synchronization module is used for carrying out time level synchronization and data format level synchronization on the received PPG signal and the BCG signal; the BCG data analysis module is used for analyzing the BCG signals subjected to synchronous processing to obtain first physiological parameter information, and specifically comprises the following steps: detecting the position of a BCG peak J wave on the waveform of the BCG signal, and determining the interval time of adjacent J waves in the waveform of the BCG signal; the PPG data analysis module is used for analyzing the PPG signals subjected to synchronous processing to obtain second physiological parameter information, and specifically comprises: detecting the position of a peak A wave on the waveform of the PPG signal, and determining the interval time of adjacent peak-valley values in the waveform of the PPG signal and the interval time of a peak J wave in the waveform of the BCG signal and a peak A wave in the waveform of the adjacent PPG signal; a nonlinear fitting model module, configured to perform nonlinear fitting on the first physiological parameter information and the second physiological parameter information, specifically: and calculating physiological parameters according to the interval time of adjacent J waves in the wave form of the BCG signal and the interval time of adjacent peak-valley values of the wave form of the PPG signal and according to the interval time of the peak J wave of the wave form of the BCG signal and the interval time of the peak A wave in the wave form of the adjacent PPG signal.
When the physiological parameter is blood pressure, the nonlinear fitting model module calculates according to the interval time of the peak J wave of the waveform of the BCG signal and the waveform peak A wave of the adjacent PPG signal, and the nonlinear fitting form is as follows: and BP _ MEAN-b JATD + c, wherein BP _ MEAN is the calculated blood pressure data, a, b, c and e are calibration coefficients, and JATD is the interval time between the peak J wave of the BCG signal waveform and the peak A wave in the adjacent PPG signal waveform.
When the physiological parameter is heart rate, the nonlinear fitting model module calculates according to the interval time of adjacent J waves in the waveform of the BCG signal and the interval time of adjacent peak-valley values in the waveform of the PPG signal, and the nonlinear fitting form is as follows: HR0+ (MIN (HR _ BCG, HR _ PPG) -HR0) × MAX (BCG _ ER, PPG _ ER)/ALL _ ER + (MAX (HR _ BCG, HR _ PPG) -HR0) × MIN (BCG _ ER, PPG _ ER)/ALL _ ER, where HR is calculated heart rate data, HR0 is the last heart rate measurement, HR _ BCG is the heart rate derived from the interval time of adjacent J-waves in the waveform of the BCG signal, HR _ PPG is the heart rate derived from the interval time of adjacent peak-valley values in the waveform of the PPG signal, BCG _ ER is the absolute value of the difference between HR _ and HR0, PPG _ ER is the absolute value of the difference between HR _ and HR0, and ALL _ ER is the sum of BCG _ ER and PPG _ ER.
The host computer still includes: and the data display module is used for displaying the physiological parameters output by the nonlinear fitting model module.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects: the BCG signal and the PPG signal are simultaneously acquired, the physiological parameter information obtained by single analysis of the BCG signal and the PPG signal is subjected to nonlinear fitting to obtain the final physiological parameter information, and the problem of low reliability of the physiological parameter information obtained after the single signal is interfered is solved.
Drawings
FIG. 1 is an overall system block diagram of an embodiment of the present invention;
fig. 2 is a block diagram of a BCG signal acquisition system in an embodiment of the invention;
fig. 3 is a block diagram of a PPG signal acquisition system according to an embodiment of the present invention;
FIG. 4 is a block diagram of an upper computer in an embodiment of the present invention;
FIG. 5 is a graphical waveform diagram of the data output from the data synchronization module according to the embodiment of the present invention;
FIG. 6 is a graph comparing the results of heart rate monitoring experiments on subjects;
fig. 7 is a graph comparing the results of blood pressure monitoring experiments of subjects.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
The embodiment of the invention relates to a physiological monitoring system based on BCG signal and PPG signal fusion, as shown in figure 1, comprising: a BCG signal acquisition system 11 for acquiring BCG signals of a human body; a PPG signal acquisition system 12 for acquiring PPG signals of the human body; and the upper computer 10 is used for receiving the BCG signal acquired by the BCG signal acquisition system and the PPG signal data acquired by the PPG signal acquisition system, analyzing the two signal data and fusing the analysis result in a nonlinear fitting mode to obtain final physiological parameter information.
As shown in fig. 2, the BCG signal acquisition system 11 includes: the piezoresistive sensor 111 is used for acquiring an original BCG signal; the BCG preprocessing module is used for preprocessing the original BCG signal; a BCG signal acquisition chip 114 for acquiring the preprocessed BCG signal; and a BCG signal data interface 115 for transmitting the BCG signal acquired by the BCG signal acquisition chip to the upper computer. Wherein, BCG preliminary treatment module includes: a BCG signal amplifier 112 for amplifying the original BCG signal; a BCG signal filter 113 for filtering the amplified original BCG signal.
The BCG signal acquisition system 11 in this embodiment reflects the BCG signal by using the piezoresistive sensor 111 to measure the corresponding movement signal generated by the body caused by the blood pumping of the heart in the beating cycle of the heart, and since the signal quantity of the originally acquired BCG signal is small, the originally acquired BCG signal needs to be transmitted into the BCG signal amplifier 112, and the BCG signal amplifier 112 is used for amplifying the originally acquired BCG signal. Because the BCG signal is greatly influenced by the human body micromotion, the amplified BCG signal has inevitable noise signals due to environmental factors, and needs to be transmitted into the BCG signal filter 113, and the BCG signal filter 113 is used for filtering the noise signals mixed in the BCG signal. The amplified and filtered BCG signal has satisfied the acquisition requirements, and the BCG signal acquisition chip 114 is used to acquire the amplified and filtered BCG signal and convert it into signal data. The BCG signal data interface 115 is used for transmitting the signal data converted by the BCG signal acquisition chip 114 into the upper computer 10 for subsequent data analysis and display.
As shown in fig. 3, the PPG signal acquisition system 12 comprises: a PPG probe 121 for acquiring raw PPG signals; the PPG preprocessing module is used for preprocessing the original PPG signal; a PPG signal acquisition chip 124, configured to acquire a preprocessed PPG signal; and the PPG signal data interface 125 is used for transmitting the PPG signal acquired by the PPG signal acquisition chip to the upper computer. Wherein the PPG preprocessing module comprises: a PPG signal amplifier 122 for amplifying the raw PPG signal; and a PPG signal filter 123 for filtering the amplified raw PPG signal.
The PPG signal acquisition system 12 in this embodiment reflects the PPG signal by using the PPG probe 121 to record the change in blood volume in the microvascular tissue under the skin caused by the diastolic activity, and since the amount of the originally acquired PPG signal is small, the originally acquired PPG signal needs to be transmitted into the PPG signal amplifier 122, and the PPG signal amplifier 122 is used for amplifying the originally acquired PPG signal. Because the PPG signal is greatly affected by the ambient light environment, the amplified PPG signal carries unavoidable noise signals due to environmental factors, and needs to be transmitted into the PPG signal filter 123, and the PPG signal filter 123 is used for filtering out the noise signals mixed in the PPG signal. The amplified and filtered PCG signal has satisfied the acquisition requirement, and the PCG signal acquisition chip 124 is configured to acquire the amplified and filtered PCG signal and convert it into signal data. The PCG signal data interface 125 is configured to transmit the signal data converted by the PCG signal acquisition chip 124 to the upper computer 10 for subsequent data analysis and display.
As shown in fig. 4, the upper computer 10 includes: a BCG signal data interface 101 for receiving the BCG signal acquired by the BCG signal acquisition system 11; a PPG signal data interface 102, configured to receive a PGG signal acquired by the PPG signal acquisition system 12; a data synchronization module 103, configured to perform time level synchronization and data format level synchronization on the received PPG signal and the BCG signal; a BCG data analysis module 104, configured to analyze the synchronously processed BCG signals to obtain first physiological parameter information; the PPG data analysis module 105 is configured to analyze the PPG signals subjected to the synchronous processing to obtain second physiological parameter information; a nonlinear fitting model module 106, configured to perform nonlinear fitting on the first physiological parameter information and the second physiological parameter information; and the data display module 107 is used for displaying the physiological parameters output by the nonlinear fitting model module.
Specifically, the BCG signal data interface 101 is configured to receive BCG signal data acquired by the BCG signal acquisition system 11, and the PPG signal data interface 102 is configured to receive PPG signal data acquired by the PPG signal acquisition system 12. During the signal data acquisition and transmission process, a data loss or error may occur, which may cause that the received BCG signal data and the PPG signal data cannot be synchronized in time, so that two signal data need to be transmitted into the data synchronization module 103, and the data synchronization module 103 is used to synchronize the two transmitted signal data in time and format. The specific operation of time synchronization is to correct the signal stamps of two signal data, and for the data frames with the signal stamps having deviation, the data synchronization module can identify the serial numbers of the data frames, delete the serial numbers appropriately, and correct the signal stamps so as to achieve the synchronization of the data time. The format synchronization specifically comprises the steps of calibrating the transmission frame formats of two signal data frames, identifying the numbers of the data frames by a data synchronization module for the data frames with deviation formats, aligning the formats to achieve format synchronization, transmitting the synchronized BCG data to a BCG data analysis module 104, carrying out data analysis on the single BCG data by the BCG data analysis module 104, and outputting a first physiological parameter which is obtained by carrying out data analysis on the single BCG data and is related to human physiological sign information. The synchronized PPG data is transmitted to the PPG data analysis module 105, and the PPG data analysis module 105 is configured to perform data analysis on the single PPG data and output a second physiological parameter related to the human body physiological sign information obtained by performing data analysis on the single PPG signal data. Because the human physiological parameters obtained by the single BCG signal and the PPG signal data are not accurate, the obtained first physiological parameter and the second physiological parameter need to be transmitted into the nonlinear fitting model module 106, and the nonlinear fitting model module 106 is used for performing nonlinear fitting on the human physiological parameters obtained by the single BCG signal and the PPG signal data to obtain the physiological parameters related to the human physiological sign information with higher correlation and more accuracy. According to a specific experiment, the correlation degree between the physiological parameter and the actual physiological parameter finally obtained by the nonlinear fitting model is higher than that obtained by a single model, the data display module 107 is used for displaying the physiological parameter output by the nonlinear fitting model 106, and the specific display medium can be in the form of a display screen, printing paper and the like.
Fig. 5 shows a graphical waveform representation of the data output by the data synchronization module according to the present embodiment, including waveform 21 of the BCG signal and waveform 22 of the PPG signal.
Wherein, the predetermined continuous marked J wave 210 of the waveform 21 of the BCG signal and the predetermined continuous marked A wave 220 of the waveform 22 of the PPG signal are used for the inference of the physiological sign information (average blood pressure and heart rate numerical value).
The BCG data analysis module 104 is configured to detect the position of the BCG peak J wave 210 on the waveform 21 of the BCG signal, and simultaneously analyze to obtain JJTD231, where JJTD231 is the interval time between adjacent J waves 210 in the last of the waveform 21 of the BCG signal.
The PPG data analysis module 105 is configured to detect the position of the peak a-wave 220 on the waveform 22 of the PPG signal, and analyze the detected position to obtain AATD232 and JATD 233. AATD233 is the interval between adjacent peak and valley values in waveform 23 of the PPG signal, and JATD233 is the interval between the peak J wave in waveform 21 of the BCG signal and the peak a wave in waveform 22 of the adjacent PPG signal.
The nonlinear fitting model module 106 performs the heart rate calculation based on the interval time (JJTD) of adjacent BCG signal peak J waves 210 and the interval time (AATD) of adjacent PPG signal peak a waves. The non-linear fit of the heart rate data is of the form:
HR_BCG＝60/JJTD (1)
HR_PPG＝60/AATD (2)
BCG_ER＝|HR_BCG-HR0| (3)
PPG_ER＝|HR_PPG-HR0| (4)
ALL_ER＝BCG_ER+PPG_ER (5)
HR＝HR0+(MIN(HR_BCG,HR_PPG)-HR0)*MAX(BCG_ER,PPG_ER)/ALL_ER+ (MAX(HR_BCG,HR_PPG)-HR0)*MIN(BCG_ER,PPG_ER)/ALL_ER (6)
wherein, HR _ BCG is heart rate calculated according to JJTD data, and HR _ PPG is data calculated according to AATD data. HR is data after nonlinear fitting. HR0 is the last heart rate measurement (HR 0 equals half of the sum of HR _ BCG and HR _ PPG at the first time). BCG _ ER is the absolute value of the difference between HR _ BCG and HR 0. PPG _ ER is the absolute value of the difference between HR _ PPG and HR 0. ALL _ ER is the sum of BCG _ ER and PPG _ ER.
The nonlinear fitting model module 106 performs the calculation of blood pressure according to the interval time (JATD) between the BCG signal peak J wave 210 and the adjacent PPG signal peak a wave. The non-linear fit of the blood pressure data is of the form:
BP_MEAN＝a*e-b*JATD+c (7)
wherein a, b, c and e are calibration coefficients.
Fig. 6 shows the heart rate experiment results of the subject. According to the present embodiment, the PPG signal is acquired from the finger of the subject, the BCG signal is acquired from the sole of the subject through piezoresistive sensors, and the heart rate is obtained as a reference value using a commercial digital oscillometric blood pressure meter. The BCG heart rate test data 31 is the heart rate derived from JJTD data in the BCG waveform. The PPG heart rate test data 32 is the heart rate derived from AATD data in the PPG waveform. The linear fit heart rate and nonlinear fit heart rate test data 33 are the results of data fit comparisons made from the BCG heart rate and the PPG heart rate. The linear fitting heart rate takes the form of an average. As can be seen from fig. 6, the error of the non-linear fitting heart rate is compared with the original BCG heart rate test data, the PPG heart rate test data and the linear fitting heart rate, and the difference between the original BCG heart rate test data, the PPG heart rate test data and the linear fitting heart rate is minimal, so that the stability and the accuracy are better.
Fig. 7 shows the results of the blood pressure test of the subject. According to the present embodiment, the PPG signal is acquired from the finger of the subject, the BCG signal is acquired from the sole of the subject through piezoresistive sensors, and the blood pressure is obtained as a reference value using a commercial digital oscillometric sphygmomanometer. 41 is the result of the non-linear fitting, formula BP _ MEAN-473.4E-0.01502 JATD +50.63, and the sum variance with the actual MEAN blood pressure signal is 12.23. 42 is the result of a common linear fit, with the formula BP _ MEAN ═ -0.6174 × JATD +194.4, and the sum variance with the actual MEAN blood pressure signal is 51.37. It can be seen that the nonlinear fitting method has a better blood pressure monitoring function.
The method and the device can acquire the BCG signal and the PPG signal simultaneously, perform nonlinear fitting on the physiological parameter information obtained by single analysis of the BCG signal and the PPG signal to obtain the final physiological parameter information, and avoid the problem of low reliability of the physiological parameter information obtained after the single signal is interfered.
Claims (9)
1. A physiological monitoring system based on BCG signal and PPG signal fusion, comprising:
the BCG signal acquisition system is used for acquiring BCG signals of a human body;
the PPG signal acquisition system is used for acquiring PPG signals of a human body;
and the upper computer is used for receiving the BCG signal acquired by the BCG signal acquisition system and the PPG signal data acquired by the PPG signal acquisition system, analyzing the two signal data and fusing the analysis result in a nonlinear fitting mode to obtain final physiological parameter information.
2. The physiological monitoring system based on fusion of BCG signals and PPG signals of claim 1 wherein the BCG signal acquisition system comprises:
the piezoresistive sensor is used for acquiring an original BCG signal;
the BCG preprocessing module is used for preprocessing the original BCG signal;
the BCG signal acquisition chip is used for acquiring the preprocessed BCG signals;
and the BCG signal data interface is used for transmitting the BCG signals acquired by the BCG signal acquisition chip to the upper computer.
3. The physiological monitoring system based on fusion of BCG signals and PPG signals of claim 2, wherein the BCG preprocessing module comprises: a BCG signal amplifier for amplifying the original BCG signal; and the BCG signal filter is used for filtering the amplified original BCG signal.
4. The physiological monitoring system based on fusion of BCG signals and PPG signals of claim 1 wherein the PPG signal acquisition system comprises:
a PPG probe for acquiring a raw PPG signal;
the PPG preprocessing module is used for preprocessing the original PPG signal;
the PPG signal acquisition chip is used for acquiring the preprocessed PPG signal;
and the PPG signal data interface is used for transmitting the PPG signal acquired by the PPG signal acquisition chip to the upper computer.
5. The physiological monitoring system based on fusion of BCG signals and PPG signals of claim 1 wherein the PPG pre-processing module comprises: a PPG signal amplifier for amplifying the raw PPG signal; and the PPG signal filter is used for filtering the amplified original PPG signal.
6. The physiological monitoring system based on fusion of BCG signals and PPG signals of claim 1 wherein the upper computer comprises:
the BCG signal data interface is used for receiving the BCG signals acquired by the BCG signal acquisition system;
a PPG signal data interface for receiving a PGG signal acquired by the PPG signal acquisition system;
the data synchronization module is used for carrying out time level synchronization and data format level synchronization on the received PPG signal and the BCG signal;
the BCG data analysis module is used for analyzing the BCG signals subjected to synchronous processing to obtain first physiological parameter information, and specifically comprises the following steps: detecting the position of a BCG peak J wave on the waveform of the BCG signal, and determining the interval time of adjacent J waves in the waveform of the BCG signal;
the PPG data analysis module is used for analyzing the PPG signals subjected to synchronous processing to obtain second physiological parameter information, and specifically comprises: detecting the position of a peak A wave on the waveform of the PPG signal, and determining the interval time of adjacent peak-valley values in the waveform of the PPG signal and the interval time of a peak J wave in the waveform of the BCG signal and a peak A wave in the waveform of the adjacent PPG signal;
a nonlinear fitting model module, configured to perform nonlinear fitting on the first physiological parameter information and the second physiological parameter information, specifically: and calculating physiological parameters according to the interval time of adjacent J waves in the wave form of the BCG signal and the interval time of adjacent peak-valley values of the wave form of the PPG signal and according to the interval time of the peak J wave of the wave form of the BCG signal and the interval time of the peak A wave in the wave form of the adjacent PPG signal.
7. The physiological monitoring system based on fusion of BCG signals and PPG signals according to claim 6, wherein when the physiological parameter is blood pressure, the nonlinear fitting model module calculates according to the interval time of the peak J wave of the waveform of the BCG signal and the peak A wave of the waveform of the adjacent PPG signal, and the nonlinear fitting form is as follows: and BP _ MEAN-b JATD + c, wherein BP _ MEAN is the calculated blood pressure data, a, b, c and e are calibration coefficients, and JATD is the interval time between the peak J wave of the BCG signal waveform and the peak A wave in the adjacent PPG signal waveform.
8. The physiological monitoring system based on fusion of a BCG signal and a PPG signal according to claim 7, wherein when the physiological parameter is heart rate, the nonlinear fitting model module calculates according to the interval time of adjacent J waves in the waveform of the BCG signal and the interval time of adjacent peak-valley values of the waveform of the PPG signal, and the nonlinear fitting form is as follows: HR0+ (MIN (HR _ BCG, HR _ PPG) -HR0) × MAX (BCG _ ER, PPG _ ER)/ALL _ ER + (MAX (HR _ BCG, HR _ PPG) -HR0) × MIN (BCG _ ER, PPG _ ER)/ALL _ ER, where HR is calculated heart rate data, HR0 is the last heart rate measurement, HR _ BCG is the heart rate derived from the interval time of adjacent J-waves in the waveform of the BCG signal, HR _ PPG is the heart rate derived from the interval time of adjacent peak-valley values in the waveform of the PPG signal, BCG _ ER is the absolute value of the difference between HR _ and HR0, PPG _ ER is the absolute value of the difference between HR _ and HR0, and ALL _ ER is the sum of BCG _ ER and PPG _ ER.
9. The physiological monitoring system based on fusion of BCG signals and PPG signals according to claim 6, wherein the upper computer further comprises: and the data display module is used for displaying the physiological parameters output by the nonlinear fitting model module.
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