A Key Power Trade-off in Wireless EEG Headset Design

The development of wireless ambulatory EEG is crucial in enabling the longer term monitoring of a patient in their everyday environment. The analysis presented here will aid the designer of a wireless EEG headset in improving the ratio of battery lifetime to battery size, with the aim of minimising the size and weight of the device. Data compression is proposed as a method to reduce the power used by the wireless transceiver, shown to dominate the system power budget. Graphs are presented which show the power available to perform varying degrees of compression in order to achieve the required lifetime or battery volume

[1]  Julián Cárdenas-Barrera,et al.  A wavelet-packets based algorithm for EEG signal compression , 2004, Medical informatics and the Internet in medicine.

[2]  Reid R. Harrison,et al.  A low-power, low-noise CMOS amplifier for neural recording applications , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[3]  D.C. Yates,et al.  An Ultra Low Power Low Noise Chopper Amplifier for Wireless BEG , 2006, 2006 49th IEEE International Midwest Symposium on Circuits and Systems.

[4]  Doris Schmitt-Landsiedel,et al.  A 0.5V, 1µW successive approximation ADC , 2002 .

[5]  C. Binnie,et al.  Modern electroencephalography: its role in epilepsy management , 1999, Clinical Neurophysiology.

[6]  E. Waterhouse,et al.  New horizons in ambulatory electroencephalography , 2003, IEEE Engineering in Medicine and Biology Magazine.

[7]  Jens Sauerbrey,et al.  A 0.5-V 1-μW successive approximation ADC , 2003, IEEE J. Solid State Circuits.

[8]  P. Tonella,et al.  EEG data compression techniques , 1997, IEEE Transactions on Biomedical Engineering.

[9]  Anamitra Makur,et al.  A High Performance Scheme for EEG Compression Using a Multichannel Model , 2002, HiPC.

[10]  Jan M. Rabaey,et al.  Power Sources for Wireless Sensor Networks , 2004, EWSN.