CN-122004807-A - Physiological data monitoring method, system and wearable device

CN122004807ACN 122004807 ACN122004807 ACN 122004807ACN-122004807-A

Abstract

The application relates to the technical field of data monitoring, and discloses a physiological data monitoring method, a system and wearable equipment, wherein the physiological data monitoring method comprises the steps of acquiring physiological data acquired by a plurality of sampling channels; the method comprises the steps of acquiring data quality parameters corresponding to physiological data, determining the credibility of the corresponding physiological data based on the data quality parameters, acquiring the credibility of the corresponding physiological data for each sampling channel, determining a measurement result based on the credibility of the physiological data, and feeding back the measurement result to a user side. The physiological data monitoring method can remarkably improve the accuracy of physiological data measurement, automatically inhibit the influence of a low-quality sampling channel under common degradation scenes such as motion artifact, wearing looseness, ambient light interference, individual blood vessel difference and the like, and improve the reliability of physiological data measurement results.

Inventors

CAI YONGCONG
Zeng Zexiong
Zhang Ruigen
GUO TIANMIN

Assignees

东莞市漫步者科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260318

Claims (10)

1. A method of physiological data monitoring, comprising: Acquiring physiological data acquired by a plurality of sampling channels; acquiring data quality parameters corresponding to the physiological data; Determining the credibility of the corresponding physiological data based on the data quality parameters, wherein the credibility is the credibility of the corresponding physiological data acquired by each sampling channel; determining a measurement result based on the credibility of the physiological data; And feeding back the measurement result to the user side.
2. The physiological data monitoring method according to claim 1, wherein each of the sampling channels is configured to collect a plurality of physiological data of a same type, the method further comprising: And determining a measurement result of the same type of physiological data based on the credibility of acquiring the physiological data by each sampling channel.
3. The physiological data monitoring method of claim 1, wherein each of the sampling channels is configured to collect a number of different types of physiological data, the method further comprising: based on the credibility of a plurality of the physiological data of each type, a measurement result of the physiological data of each type is determined.
4. The physiological data monitoring method according to claim 1, wherein said determining the trustworthiness of the corresponding physiological data based on the data quality parameters comprises: determining a parameter weight of each data quality parameter, wherein the parameter weight is a contribution intensity coefficient of the data quality parameter to the credibility; And carrying out weighted summation on all the data quality parameters of each physiological data based on the parameter weights to obtain the credibility.
5. The method for monitoring physiological data according to claim 1, wherein the physiological data is a digitized result obtained by sampling and quantizing a physiological data signal, and the acquiring the data quality parameter corresponding to the physiological data includes: acquiring the physiological data signals when each sampling channel acquires the physiological data; the data quality parameter is calculated based on the physiological data signal.
6. The physiological data monitoring method of claim 5, wherein the data quality parameter comprises one or more of a signal-to-noise ratio, a signal peak-to-peak value, a signal effective value, a signal variance, and a signal standard deviation, the calculating the data quality parameter based on the physiological data signal comprising at least one of: calculating the ratio of the signal power spectrum density average value and the noise power spectrum density average value of the physiological data signal to obtain the signal-to-noise ratio; calculating the difference between the maximum alternating current component and the minimum alternating current component in the physiological data signal to obtain the signal peak-to-peak value; calculating the square root of the arithmetic mean value of the square of the alternating current component of each signal sampling point in the physiological data signal to obtain the signal effective value; Calculating an unbiased sample variance of alternating current components of each signal sampling point in the physiological data signal to obtain the signal variance; and calculating the square root of the signal variance to obtain the signal standard deviation.
7. The method of physiological data monitoring according to claim 2, wherein the measurement results include a first measurement result, and the determining the measurement result of the same type of physiological data includes: and comparing the credibility of each physiological data, and taking the physiological data with the largest credibility as the first measurement result.
8. The physiological data monitoring method according to claim 2, wherein the measurement results further comprise a second measurement result, and the determining the measurement result of the same type of physiological data further comprises: Normalizing the credibility of each physiological data to obtain normalized credibility; taking the normalized credibility of each physiological data as the data weight of each physiological data; and carrying out weighted summation on each physiological data based on the data weight of each physiological data to obtain the second measurement result.
9. The wearable device is characterized by comprising a plurality of sampling channels; The wearable device is used for sending physiological data acquired by each sampling channel to the terminal device; the terminal device is configured to perform the physiological data monitoring method according to any of claims 1-8.
10. A physiological data monitoring system is characterized by comprising a terminal device and at least one wearable device; Each wearable device is used for collecting physiological data of a user through a plurality of sampling channels; the terminal device is configured to perform the physiological data monitoring method according to any of claims 1-8.

Description

Physiological data monitoring method, system and wearable device Technical Field The present application relates to the field of data monitoring technologies, and in particular, to a physiological data monitoring method, system and wearable device. Background With the continuous improvement of health consciousness of people, detection and management of personal physiological data are increasingly emphasized. Currently, there are a variety of physiological data monitoring devices on the market, mainly relying on PPG (Photoplethysmography ) technology. However, PPG technology has some disadvantages in the physiological data monitoring device and application fields, such as poor signal quality caused by weak wearing, easy interference of ambient light, motion artifact, blood vessel difference and the like, and influences accuracy of physiological data measurement, which directly leads to significant deviation of key health indexes, and is difficult to meet accurate monitoring requirements of health indexes. Disclosure of Invention In view of the above, the embodiment of the application provides a physiological data monitoring method, a physiological data monitoring system and wearable equipment, which can effectively solve the problems of inaccurate monitoring of key health indexes, obvious deviation and the like. In a first aspect, an embodiment of the present application provides a physiological data monitoring method, including: Acquiring physiological data acquired by a plurality of sampling channels; acquiring data quality parameters corresponding to the physiological data; Determining the credibility of the corresponding physiological data based on the data quality parameters, wherein the credibility is the credibility of the corresponding physiological data acquired by each sampling channel; determining a measurement result based on the credibility of the physiological data; And feeding back the measurement result to the user side. In a first possible embodiment of the first aspect, each of the sampling channels is for acquiring a number of physiological data of the same type, the method further comprising: And determining a measurement result of the same type of physiological data based on the credibility of acquiring the physiological data by each sampling channel. In a second possible embodiment of the first aspect, each of the sampling channels is for acquiring a number of different types of physiological data, the method further comprising: based on the credibility of a plurality of the physiological data of each type, a measurement result of the physiological data of each type is determined. In a third possible embodiment of the first aspect, the determining the trustworthiness of the corresponding physiological data based on the data quality parameter includes: determining a parameter weight of each data quality parameter, wherein the parameter weight is a contribution intensity coefficient of the data quality parameter to the credibility; And carrying out weighted summation on all the data quality parameters of each physiological data based on the parameter weights to obtain the credibility. In a fourth possible embodiment of the first aspect, the physiological data is a digitized result obtained by sampling and quantizing a physiological data signal, and the obtaining a data quality parameter corresponding to the physiological data includes: acquiring the physiological data signals when each sampling channel acquires the physiological data; the data quality parameter is calculated based on the physiological data signal. In a fifth possible embodiment of the first aspect, the data quality parameter comprises one or more of a signal-to-noise ratio, a signal peak-to-peak value, a signal effective value, a signal variance, and a signal standard deviation, the calculating the data quality parameter based on the physiological data signal comprises at least one of: calculating the ratio of the signal power spectrum density average value and the noise power spectrum density average value of the physiological data signal to obtain the signal-to-noise ratio; calculating the difference between the maximum alternating current component and the minimum alternating current component in the physiological data signal to obtain the signal peak-to-peak value; calculating the square root of the arithmetic mean value of the square of the alternating current component of each signal sampling point in the physiological data signal to obtain the signal effective value; Calculating an unbiased sample variance of alternating current components of each signal sampling point in the physiological data signal to obtain the signal variance; and calculating the square root of the signal variance to obtain the signal standard deviation. In a sixth possible embodiment of the first aspect, the measurement results comprise first measurement results, and the determining the measurement results of the same type of physiological da