Literature DB >> 24613794

A configurable realtime DWT-based neural data compression and communication VLSI system for wireless implants.

Yuning Yang1, Awais M Kamboh2, Andrew J Mason3.   

Abstract

This paper presents the design of a complete multi-channel neural recording compression and communication system for wireless implants that addresses the challenging simultaneous requirements for low power, high bandwidth and error-free communication. The compression engine implements discrete wavelet transform (DWT) and run length encoding schemes and offers a practical data compression solution that faithfully preserves neural information. The communication engine encodes data and commands separately into custom-designed packet structures utilizing a protocol capable of error handling. VLSI hardware implementation of these functions, within the design constraints of a 32-channel neural compression implant, is presented. Designed in 0.13μm CMOS, the core of the neural compression and communication chip occupies only 1.21mm(2) and consumes 800μW of power (25μW per channel at 26KS/s) demonstrating an effective solution for intra-cortical neural interfaces.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Communication protocol; Discrete wavelet transform; Neural compression; VLSI

Mesh:

Year:  2014        PMID: 24613794     DOI: 10.1016/j.jneumeth.2014.02.009

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  1 in total

1.  An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.

Authors:  Alexander J Casson
Journal:  Sensors (Basel)       Date:  2015-12-17       Impact factor: 3.576

  1 in total

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