Adaptive compression and optimization for real-time energy-efficient wireless EEG monitoring systems
作者： Ramy Hussein , Amr Mohamed , Masoud Alghoniemy
DOI: 10.1109/BMEICON.2013.6687691
关键词:
摘要: Recent technological advances in wireless body sensor networks (WBSN) have made it possible for the development of innovative medical applications to improve health care and quality life. Electroencephalography (EEG)-based lie at heart this promising technologies. However, excessive power consumption may render some these inapplicable. Hence, intelligent energy efficient methods are needed such applications. In work, improved efficiency can be obtained by utilizing smart compression techniques, which reduce airtime over energy-hungry channels; particular, discrete wavelet transform (DWT) compressive sensing (CS) used EEG signals acquisition compression. To achieve low-complexity energy-efficient system, proposed technique makes use receiver feedback order switch between both algorithms based on application needs. Experimental study has shown that algorithm effectively reconfigures utilized parameters a channel feed back signal.
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