A Noise-Power-Area Optimized Biosensing Front End for Wireless Body Sensor Nodes and Medical Implantable Devices

作者：Bhamra Hansraj^*; Lynch John; Ward Matthew; Irazoqui Pedro

来源：IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2017, 25(10): 2917-2928.

DOI：10.1109/TVLSI.2017.2714171

• Analog front end (AFE)
• biopotentials
• biosensing acquisition
• implantable devices
• low noise
• low power
• wireless body sensor node (WBSN)

In this paper, we present a noise, power, and area efficient biosensing front-end application specified integrated circuit (ASIC) for the next-generation wireless body sensor nodes and implantable devices. We identify the key design parameter tradeoffs in the biomedical recording systems and carry out a thorough analysis and optimization to maximize them. Based on our analysis and optimization of the front end, we propose a design methodology for the recording channel that is applicable to various biomedical applications. The ASIC is implemented in a 0.18-mu m CMOS process to validate our optimization methodology. The ASIC is reconfigurable to accommodate various biopotentials with the high-pass and low-pass cutoff frequencies being 0.5-300 Hz and 150 Hz-10 kHz, respectively. The low-pass cutoff is provided by an ultralow power Gm-C low-pass filter, which also acts as an antialiasing filter for the switching-optimized 10-b successive approximation register (SAR) analog-to-digital converter (ADC). The analog front end (AFE) gain is also programmable from 38 to 72 dB. A comprehensive power management unit provides the power supply, multiple reference voltages, and bias currents to the entire chip. The AFE and ADC dissipate only 5.74 mu W and 306 nW from the on-chip regulators, respectively. The measured input-referred noise is 2.98 mu Vrms, resulting in the noise efficiency factor and power efficiency factor equals 2.6 and 9.46, respectively. The active area of the AFE is 0.0228 mm(2). We verify the chip functionality in a number of in vivo and ex vivo biological experiments.

• 出版日期2017-10