Low Power Asynchronous Data Acquisition Front End for Wireless Body Sensor Area Network

Wireless body sensor area networks (WBAN) is one of the key technologies to solve the rising healthcare costs through early detection, and point-of-care diagnosis and health management. However there is a stringent power requirement on individual sensor nodes in such networks. Consequently traditional signal chain of amplify-digitize-transmit generates large amounts of data that cannot be sustained due to limited energy and bandwidth. In this paper we propose an asynchronous data acquisition platform that provides inherent digitization and compression at the source. The proposed implementation consists of low noise front-end amplifier (AFE) with tunable bandwidth and an asynchronous clockless analog-to-digital converter (ADC). Data compression is achieved by the inherent signal dependent sampling of the asynchronous architecture. The AFE and ADC were fabricated in a 0.18μm CMOS technology and consume a total of 79μW. Measured results for asynchronous ECG signal acquisition are presented.

[1]  R. R. Harrison,et al.  A low-power low-noise CMOS amplifier for neural recording applications , 2003, IEEE J. Solid State Circuits.

[2]  Gilles Sicard,et al.  A new class of asynchronous A/D converters based on time quantization , 2003, Ninth International Symposium on Asynchronous Circuits and Systems, 2003. Proceedings..

[3]  Jerker Delsing,et al.  Level-Crossing ADC Performance Evaluation Toward Ultrasound Application , 2009, IEEE Transactions on Circuits and Systems I: Regular Papers.

[4]  T. R. Viswanathan,et al.  A new signal acquisition technique , 1992, [1992] Proceedings of the 35th Midwest Symposium on Circuits and Systems.

[5]  Sameer R. Sonkusale,et al.  A 0.8 V asynchronous ADC for energy constrained sensing applications , 2008, 2008 IEEE Custom Integrated Circuits Conference.

[6]  Kenneth L. Shepard,et al.  Continuous-time digital signal processors , 2005, 11th IEEE International Symposium on Asynchronous Circuits and Systems.

[7]  S. Sonkusale,et al.  Direct Analog-to-QRS detection front-end architecture for wearable ECG applications , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.