Literature DB >> 19366647

An ultra low-power CMOS automatic action potential detector.

Benoit Gosselin1, Mohamad Sawan.   

Abstract

We present a low-power complementary metal-oxide semiconductor (CMOS) analog integrated biopotential detector intended for neural recording in wireless multichannel implants. The proposed detector can achieve accurate automatic discrimination of action potential (APs) from the background activity by means of an energy-based preprocessor and a linear delay element. This strategy improves detected waveforms integrity and prompts for better performance in neural prostheses. The delay element is implemented with a low-power continuous-time filter using a ninth-order equiripple allpass transfer function. All circuit building blocks use subthreshold OTAs employing dedicated circuit techniques for achieving ultra low-power and high dynamic range. The proposed circuit function in the submicrowatt range as the implemented CMOS 0.18- microm chip dissipates 780 nW, and it features a size of 0.07 mm(2). So it is suitable for massive integration in a multichannel device with modest overhead. The fabricated detector succeeds to automatically detect APs from underlying background activity. Testbench validation results obtained with synthetic neural waveforms are presented.

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Year:  2009        PMID: 19366647     DOI: 10.1109/TNSRE.2009.2018103

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

Review 1.  Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

Authors:  Elliot Greenwald; Matthew R Masters; Nitish V Thakor
Journal:  Med Biol Eng Comput       Date:  2016-01-11       Impact factor: 2.602

2.  A Fully Implantable, Programmable and Multimodal Neuroprocessor for Wireless, Cortically Controlled Brain-Machine Interface Applications.

Authors:  Fei Zhang; Mehdi Aghagolzadeh; Karim Oweiss
Journal:  J Signal Process Syst       Date:  2011-06-15

3.  Wavelet transform for real-time detection of action potentials in neural signals.

Authors:  Adam Quotb; Yannick Bornat; Sylvie Renaud
Journal:  Front Neuroeng       Date:  2011-07-15

Review 4.  Recent advances in neural recording microsystems.

Authors:  Benoit Gosselin
Journal:  Sensors (Basel)       Date:  2011-04-27       Impact factor: 3.576

5.  0.6 V, 116 nW Neural Spike Acquisition IC with Self-Biased Instrumentation Amplifier and Analog Spike Extraction.

Authors:  Jong Pal Kim; Hankyu Lee; Hyoungho Ko
Journal:  Sensors (Basel)       Date:  2018-07-30       Impact factor: 3.576

  5 in total

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