Design of Health Detection System for Elderly Smart Watch Based on Biosignal Acquisition

Abstract

The health monitoring of the elderly has attracted increasing attention of researchers. Based on the biosignal acquisition method, this paper proposes a design structure of the health detection system for smart watches for the elderly and realizes the effective detection of health signals by analyzing the Lipschitz exponent of the maximum value column of the transform. The multiphysiological parameter acquisition and monitoring system of the wearable smart watch designed in this paper can continuously monitor the physiological parameters of the elderly such as body temperature, pulse, and respiration for a long time and solve the problem of the accuracy of the health detection of the elderly. In the simulation process, based on the performance of the synchronization source and the difference of the network path, the model applies the multivariate and multiscale biological signals to collect the human gait acceleration. The experimental results show that, compared with the international recognition rate obtained for this data set, the highest recognition rate obtained by the method in this paper reaches 96.5%, which can provide a calibration accuracy of 1 ~ 50 ms, and the synchronized system time and the national time service center network are given. The error obtained by comparing the published time is within 50 ms, which meets the accuracy requirements of the time protocol. The results fully prove that the algorithm in this paper can effectively extract the biosignal features of the elderly’s health detection and has good statistical features and classification accuracy.