Low Power Wearable Wireless ECG System for Long-Term Homecare [thesis]

Yishan Wang, Stefan Heinen, Steffen Leonhardt
This thesis has proposed a novel wearable wireless ECG system. With the consideration of long-term homecare application, it strives to control the size and power consumption of the sensor node. As a result, this thesis is devoted in three aspects: new electrode placements design, wireless ECG system design and multiple power control technologies.In the new electrode placements investigation, an experiment was designed to investigate the best limb electrode placements. The experiment compared 14
more » ... different placements for limb electrodes. The detected signals of different placements were compared with the standard lead system. The best placements for four limb electrodes were selected according to the correlation coefficients between the standard and new placements.In the wireless ECG system design, a low noise analog frontend was implemented for the ECG signals, considering practical issues like dc offset caused by body motion, EMI coupled from the power line and electrode impedance mismatch. The measurement result showed excellent performance even under body motion. With the new electrode placements and the low noise analog front end, two wireless ECG systems were implemented with ZigBee and BLE. The sizes of both sensor nodes were controlled in 5.5 cm x 2.5 cm, with which the sensor node was able to be conveniently worn on the body without affecting user's mobility. The ECG signals were displayed on PC or smartphone in real time.This work applied multiple power control technologies in both analog and digital ways to extend the battery life. Firstly, adjustable power mode control was operated in the ZigBee and BLE sensor nodes with battery lives of 52 hours and 55hours respectively. Secondly, dynamic transmission power control in ZigBee system was utilized to adjust the Tx output power dynamically according to the received signal strength indicator. It saved 20% - 30% power during regular movements. Thirdly, Compressed Sensing (CS) was applied to reduce the size of the transmitted data. Digital CS was firstly impl [...]
doi:10.18154/rwth-2017-02015 fatcat:bgqu4ghdcfhg5ca3d3whvcnti4