Development Of Low-power Wearable ECG Monitor

Cardiovascular disease is a common disease which seriously threatens human health.It occupies the first place in all kinds of causes of death.Early detection and early treatment of abnormal electrocardiogram are important ways to reduce mortality.At present,the portable ECG monitoring system has many advantages,such as large volume,high lead and high power consumption,and can not process ECG data in real time.Therefore,the development of light-weight,wearable and real-time ECG monitoring system that can achieve all-weather ECG / heart rate monitoring is of great significance.In this paper,the key technology of low power Wearable ECG monitoring system is studied.The low power consumption strategy and hardware technology are integrated to reduce the power consumption.The combination of analog filtering and digital filtering is used to filter the high frequency noise,low frequency noise and power frequency interference,and the data is transmitted to the hand by low power Bluetooth technology.The client APP processes and displays ECG signals in real time.In view of the weak and easy interference of the ECG signal,the first and two stage amplifying circuits and filter circuits are designed to amplify the ECG signal and suppress the low frequency noise and high frequency noise of the signal.At the same time,we use the remaining resources of MCU to realize integer digital notch filter to remove power frequency interference.According to the demand of power noise and static power,the power supply system is designed by using ADP151 and REF3312 low power chip,thus effectively avoiding the interference of the power noise to the ECG signal and the failure of the RF chip current pulse to the stability of the system.By analyzing the low power condition of hardware,this paper studies the configuration of hardware and wireless protocol parameters,and designs and proposes to use the rate of change of the cache data to indirectly obtain the signal quality strategy of the end device.In the process of sending data,the transmission power is changed and the low power data transmission is realized,and the average current of the transmitted data is reduced to 0.45 m A.The morphological filter is used to adjust the structural elements according to the sampling frequency.The waveform characteristics of the original signal are retained on the premise of filtering the baseline drift,and the distortion of the signal is avoided.The R wave detection algorithm with adaptive threshold is proposed for the change of the single lead ECG waveform characteristics caused by individual difference,and the MLII sample in the MIT-BIH database is tested,the accuracy rate is 99.53%.The algorithm is transplanted to the Android client.By real machine testing,the average threshold adaptive time is 6.4s under static state,and the accuracy of R wave detection is 99.89%.