Literature DB >> 15825873

An ultra-low-power programmable analog bionic ear processor.

Rahul Sarpeshkar1, Christopher Salthouse, Ji-Jon Sit, Michael W Baker, Serhii M Zhak, Timothy K T Lu, Lorenzo Turicchia, Stephanie Balster.   

Abstract

We report a programmable analog bionic ear (cochlear implant) processor in a 1.5-microm BiCMOS technology with a power consumption of 211 microW and 77-dB dynamic range of operation. The 9.58 mm x 9.23 mm processor chip runs on a 2.8 V supply and has a power consumption that is lower than state-of-the-art analog-to-digital (A/D)-then-DSP designs by a factor of 25. It is suitable for use in fully implanted cochlear-implant systems of the future which require decades of operation on a 100-mAh rechargeable battery with a finite number of charge-discharge cycles. It may also be used as an ultra-low-power spectrum-analysis front end in portable speech-recognition systems. The power consumption of the processor includes the 100 microW power consumption of a JFET-buffered electret microphone and an associated on-chip microphone front end. An automatic gain control circuit compresses the 77-dB input dynamic range into a narrower internal dynamic range (IDR) of 57 dB at which each of the 16 spectral channels of the processor operate. The output bits of the processor are scanned and reported off chip in a format suitable for continuous-interleaved-sampling stimulation of electrodes. Power-supply-immune biasing circuits ensure robust operation of the processor in the high-RF-noise environment typical of cochlear implant systems.

Mesh:

Year:  2005        PMID: 15825873     DOI: 10.1109/TBME.2005.844043

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  A Digitally Programmable Cytomorphic Chip for Simulation of Arbitrary Biochemical Reaction Networks.

Authors:  Sung Sik Woo; Jaewook Kim; Rahul Sarpeshkar
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2018-04       Impact factor: 3.833

2.  Finding a roadmap to achieve large neuromorphic hardware systems.

Authors:  Jennifer Hasler; Bo Marr
Journal:  Front Neurosci       Date:  2013-09-10       Impact factor: 4.677

3.  A glucose fuel cell for implantable brain-machine interfaces.

Authors:  Benjamin I Rapoport; Jakub T Kedzierski; Rahul Sarpeshkar
Journal:  PLoS One       Date:  2012-06-12       Impact factor: 3.240

4.  Reconstruction of audio waveforms from spike trains of artificial cochlea models.

Authors:  Anja T Zai; Saurabh Bhargava; Nima Mesgarani; Shih-Chii Liu
Journal:  Front Neurosci       Date:  2015-10-13       Impact factor: 4.677

Review 5.  Self-Sustainable Biomedical Devices Powered by RF Energy: A Review.

Authors:  Hussein Yahya Alkhalaf; Mohd Yazed Ahmad; Harikrishnan Ramiah
Journal:  Sensors (Basel)       Date:  2022-08-24       Impact factor: 3.847

Review 6.  A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors.

Authors:  Anup Vanarse; Adam Osseiran; Alexander Rassau
Journal:  Front Neurosci       Date:  2016-03-29       Impact factor: 4.677

7.  Energy-efficient waveform for electrical stimulation of the cochlear nerve.

Authors:  Marcus Yip; Peter Bowers; Victor Noel; Anantha Chandrakasan; Konstantina M Stankovic
Journal:  Sci Rep       Date:  2017-10-19       Impact factor: 4.379

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.