The Study Of Respirate-rate Real-time Monitoring Based On Mobile Terminal

With the development of society and the accelerated pace of life,the incidence of chronic respiratory diseases increased year by year,the health and economic losses caused by the disease is increasing with each passing year.One of the important items in the prevention and control of chronic respiratory diseases is the monitoring of respiratory.The monitoring method of respiratory signal is the direct monitoring method,such as temperature sensor,pressure sensor,CO₂ measurement.These monitoring methods need wear separate signal acquisition sensors and corresponding signal conditioning systems,which greatly increased the burden and inconvenience of the users.PhotoPlethysmoGraphy?PPG?has been successfully applied in the clinical detection of blood oxygen saturation and pulse signal,the study also showed that the PPG signal contains not only the blood oxygen saturation and pulse signal but also the human body respiratory signal.If the respiratory signal could be acquisited from PPG,there need not to increase the respiratory signal acquisition sensor and the system to achieve the human respiratory monitoring.So,it needn't to be monitored by the additional physiological and economic burden.Based on the characteristics and requirements of long-term monitoring of chronic diseases,respiratory signal monitoring can be combined with the popularity of intelligent terminals to achieve mobile monitoring of respiratory signals.The main research work of this paper is to achieve the respiratory rate monitoring work using the PPG signal based on the Android mobile platform.Firstly,the experimental data for the study of the algorithm were collected utilizing OEM blood oxygen module acquisition of PPG signals.At the same time,the respiratory signal for comparative analysis was collected using XSY2001 D instruments.Then,the algorithm research was investigated according to the characteristics of the health care system to achieve respiratory safety,accurate and rapid monitoring based on the mobile platform.In this paper,the respiratory monitoring signal is measured indirectly based on PPG.It will not lead to any safety issues to the human body.When the wavelet transform algorithm,an existing algorithm for the analysis of respiratory monitoring with high accuracy,was adopted to analyze the collection data.The results show that there was less accurate with the experimental data extracted from PPG at sampling frequency 50 Hz.It could be due to the decrease of the sampling frequency that leads to the reduction of the identifiable respiratory wave.This paper adopted an novel algorithm to strengthen the useful signal,and used the signal feature spreading method to extract the respiratory frequency.The results show that the proposed method significantly enhanced the respiration signal recognition rates.It achieves the desired effect.The results show that the maximum error rate of the proposed algorithm is 9.28%.Reducement of the sampling frequency greatly reduces the amount of computation per unit of time.Thus it improves the system analysis and processing speed.And it is conducive to the realization of mobile real-time respiratory monitoring.Otherwise,this paper conducted the monitoring system design based on the Android mobile intelligent terminal.The monitor can be monitored at any time and anywhere on the mobile intelligent terminal?such as smart phones?to learn their own breathing parameters.When an exception occurs,the intelligent terminal will give an alarm and send messages to friends and relatives or medical personnel at the same time.It achieves the purpose of real-time monitoring of human respiratory movement.