Adaptive Energy-aware Encoding for DWT-Based Wireless EEG Monitoring System

摘要: Wireless Electroencephalography (EEG) tele-monitoring systems performing encoding and streaming over energy-hungry wireless channels are limited in energy supply. However, excessive power consumption either or radio channel may render some applications inapplicable. Hence, efficient methods needed to improve such applications. In this work, an embedded EEG system should be able adjust its computational complexity, hence, according the variations. To analyze distortion-compression ratio (PRD-CR) behavior of under constraints, both transmission taken into consideration. paper, we propose a power-distortion- compression (P-PRD-CR) framework, which extends traditional PRD-CR P-PRD-CR model. We complexity for typical discrete wavelet transform (DWT)-based system. Using our developed encoder effectively reconfigures control parameters match constraints while retaining maximum reconstruction quality. Results show that using proposed can obtain higher accuracy same constrained-portable device.