Session 9 – Honolulu Suite

Medical Electronics

Thursday, June 14, 8:05 a.m.

Chairpersons: J. Gealow, MediaTek Wireless, Inc.

C.-Y. Lee,National Chiao Tung University

9.1 - 8:05 a.m.

A 0.6V 2.9µW Mixed-Signal Front-End for ECG Monitoring, M. Yip, J.L. Bohorquez*, A.P. Chandrakasan, Massachusetts Institute of Technology, *Convergence Medical Devices

This paper presents a mixed-signal ECG front-end that uses aggressive voltage scaling to maximize power-efficiency and facilitate integration with low-voltage DSPs. 50/60Hz interference is canceled using mixed-signal feedback, enabling low-voltage operation by reducing dynamic range requirements. Analog circuits are optimized for ultra-low-voltage, and a SAR ADC with a dual-DAC architecture eliminates the need for a power-hungry ADC buffer. Oversampling and ΔΣ-modulation leveraging near-VT digital processing are used to achieve ultra-low-power operation without sacrificing noise performance and dynamic range. The fully-integrated front-end is implemented in a 0.18µm CMOS process and consumes 2.9µW from 0.6V.

9.2 - 8:30 a.m.

A 700μW 8-Channel EEG/Contact-impedance Acquisition System for Dry-electrodes, S. Mitra, J. Xu, A. Matsumoto*, K.A.A. Makinwa**, C. Van Hoof, R.F. Yazicioglu, imec, *Panasonic Corporation, **Delft University of Technology

A 700μW 8-channel active-electrode (AE) based EEG monitoring system is presented. The complete system consists of 9 AEs and a back-end analog signal processor. It is capable of continuously recording EEG signals and electrode-tissue contact impedance (ETI). The EEG channels have 1.2GOhm input impedance, 1.75µVrms noise (0.5-100Hz), 84dB CMRR, and can reject ±250mV of electrode offset, while consuming less than <87μW (including ETI). The system facilitates ambulatory use and patient comfort, while delivering high quality EEG signals.

9.3 - 8:55 a.m.

A Wirelessly Powered Log-based Closed-loop Deep Brain Stimulation SoC with Two-way Wireless Telemetry for Treatment of Neurological Disorders, H.-G. Rhew, J. Jeong, J. Fredenburg, S. Dodani, P. Patil, M.Flynn, University of Michigan

A log-based closed-loop Deep Brain Stimulation system detects and processes low-frequency brain field signals to optimize stimulation parameters. The fully self-contained single-chip system incorporates LNAs, a log-ADC, digital log-filters, a log-DSP with a PI-controller, current stimulators, a two-way wireless transceiver, a clock generator, and an RF energy harvester. The 2x2mm2 180nm CMOS prototype consumes 468μW for recording and processing neural signals, stimulation, and for two-way wireless communication.

9.4 - 9:20 a.m.

A Fully-Integrated 10.5μW Miniaturized (0.125mm²) Wireless Neural Sensor, D. Yeager, W. Biederman, N. Narevsky, E. Alon, J. Rabaey, University of California, Berkeley

A wirelessly powered 0.125mm2 65nm CMOS IC for BMI applications integrates four 1.5μW amplifiers (6.5μVrms input-referred noise for a 10kHz bandwidth) with power conditioning and communication circuitry. The multi-node backscatter FDMA communication scheme frequency locks to a wireless interrogator. The full system, verified wirelessly with MATLAB generated neural data, consumes 10.5μW, and operates at 1mm in air with 50mW transmit power.