A Low-power wireless multi-channel surface EMG sensor with simplified ADPCM data compression

The ubiquitous real-time monitoring and recording of surface electromyography (sEMG) signal is essential to several rehabilitation applications, such as muscle recovery analysis. We present an inexpensive wireless sEMG sensor using a commercial off-the-shelf wireless microcontroller unit (MCU) incorporating a simplified adaptive differential pulse code modulation (ADPCM) routine for real-time data compression. In single-channel configuration, the presented approach reduces power consumption of a transmission subsystem by up to 69%, leading to longer operation life expectancy. Due to the excessive amount of data as well as the limited processing power of embedded MCUs, multi-channel configurations would normally not be feasible. However, the proposed compression method makes a multi-channel EMG sensor possible. The distortion induced by this approach on EMG signal is on the order of 1%. Test results from in vivo trials with humans are presented.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  D. F. Lovely,et al.  Errors associated with the use of adaptive differential pulse code modulation in the compression of isometric and dynamic myo-electric signals , 2006, Medical and Biological Engineering and Computing.

[3]  S. Farshchi,et al.  Acquiring High-Rate Neural Spike Data with Hardware-Constrained Embedded Sensors , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Jung Kim,et al.  Development of a compact-size and wireless surface EMG measurement system , 2009, 2009 ICCAS-SICE.

[5]  Aleksey Pesterev,et al.  Bi-Fi: An Embedded Sensor/System Architecture for Remote Biological Monitoring , 2007, IEEE Transactions on Information Technology in Biomedicine.

[6]  Joung Hwan Mun,et al.  Development of a Preamplifier and a Wireless Surface EMG , 2007 .

[7]  F.-S. Jaw,et al.  Microcontroller-based wireless recorder for biomedical signals , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[8]  J. F. Norris,et al.  Real-time compression of myoelectric data utilising adaptive differential pulse code modulation , 1995, Medical and Biological Engineering and Computing.

[9]  A. Ahmed,et al.  Design and Implementation of a Wireless (Bluetooth®) Four Channel Bio-Instrumentation Amplifier and Digital Data Acquisition Device with User-Selectable Gain, Frequency, and Driven Reference , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Corinne Mailhes,et al.  On the choice of an electromyogram data compression method , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[11]  Hiroyuki Kobayashi,et al.  Development of an EMG acquisition system of universal bio-signal interface for high-quality life , 2010, Proceedings of SICE Annual Conference 2010.

[12]  Hiroyuki Kobayashi.  Intelligent wireless EMG/ECG electrode employing ZigBee technology , 2011, SICE Annual Conference 2011.