Title :
Live demonstration: Wireless sensors and systems for body area network (BAN)
Author :
Lin, Richard ; Lemmens, P. ; Peng, Li-Yi ; Chang, Mingchao ; Lin, Alexander ; Jin-Lien Lin
Author_Institution :
IMEC Taiwan Innovation Center, HsinChu, Taiwan
Abstract :
There has been an increasing interest on body area network (BAN) because of the increasing need for long-term monitoring of various health parameters, such as EEG and ECG, in health, wellness and medical applications, and also from the technology advances that make low power sensor systems and miniaturization available for portable use. One of the biggest trends in EEG monitoring has been miniaturized wireless EEG sensor headsets for interfacing between the brain and the machine. In this demo, a wireless EEG headset is made ultra portable and compatible with dry electrodes. The heart of the headset if IMEC´s high-performance and ultra low power readout ASIC, which consumes only 200uW, features high common mode rejection ratio (CMRR) of 120dB, and low noise (55nV/√Hz, input referred). The entire headset system consumes only 3.3mW for continuous recording and wireless transmission of 1 channel, and 9.2mW for 8 channels. A wireless ECG patch not only make use of IMEC´s ultra low power analog front end (AFE) circuitry for extended onthe-go monitoring, but also implements advanced algorithms such as continuous wavelet transform (CWT) and motion artifact removal (MAR) to better process the signals to restore them from an otherwise noise-coupled environment. With such algorithms built-in on ultra low power DSP, this wireless patch is capable of monitoring and processing local signals with ultra low power consumption.
Keywords :
application specific integrated circuits; biomedical electronics; body area networks; body sensor networks; electrocardiography; electroencephalography; medical signal processing; patient monitoring; wavelet transforms; ASIC; Body Area Network Systems; DSP; IMEC; analog front end circuitry; brain; common mode rejection ratio; continuous wavelet transform; dry electrodes; gain 120 dB; health parameters; machine; motion artifact removal; noise-coupled environment; power 200 muW; power 3.3 mW; power 9.2 mW; recording transmission; signal restoration; wireless ECG patch; wireless EEG headset; wireless sensors; wireless transmission; Electrocardiography; Electroencephalography; Headphones; Monitoring; Sensors; Wireless communication; Wireless sensor networks; BAN; ECG; EEG; sensor; wireless;
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2012 IEEE
Conference_Location :
Hsinchu
Print_ISBN :
978-1-4673-2291-1
Electronic_ISBN :
978-1-4673-2292-8
DOI :
10.1109/BioCAS.2012.6418490