A design of neural decoder by reducing discrepancy between Manual Control (MC) and Brain Control (BC)

Young Hwan Chang, Mo Chen, Maryam Shanechi, Jose M. Carmena, Claire Tomlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Brain-Machine Interfaces (BMI) have strong potential to benefit a large number of disabled people but current decoding algorithms suffer from the following shortcomings. First, BMI decoding algorithms are often trained offline, but this paradigm ignores the discrepancy between the Manual Control (MC) and the Brain Control (BC) modes of operation. Second, the standard neural decoder, the Kalman filter, does not explicitly take into account the control of movements by neural activity. To address these problems, we propose a biologically motivated neural decoder structure by explicitly adding a control signal and unmeasureable neural activity. Since the parameter estimation problem is underdetermined, we propose a new parameter estimation method that minimizes the discrepancy between the MC and BC. We demonstrate the effectiveness of our methods by synthesizing MC and BC data in a Linear Quadratic (LQ) optimal control setting with a partial loss of neural control in BC, and show that the proposed decoder is more robust to a partial loss of neural control than a standard Kalman filter that does not utilize any reparameterizations.

Original languageEnglish (US)
Title of host publication2014 European Control Conference, ECC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages516-521
Number of pages6
ISBN (Electronic)9783952426913
DOIs
StatePublished - Jul 22 2014
Event13th European Control Conference, ECC 2014 - Strasbourg, France
Duration: Jun 24 2014Jun 27 2014

Publication series

Name2014 European Control Conference, ECC 2014

Other

Other13th European Control Conference, ECC 2014
CountryFrance
CityStrasbourg
Period6/24/146/27/14

ASJC Scopus subject areas

  • Control and Systems Engineering

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    Chang, Y. H., Chen, M., Shanechi, M., Carmena, J. M., & Tomlin, C. (2014). A design of neural decoder by reducing discrepancy between Manual Control (MC) and Brain Control (BC). In 2014 European Control Conference, ECC 2014 (pp. 516-521). [6862547] (2014 European Control Conference, ECC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECC.2014.6862547