Generalizability of EMG decoding using local field potentials

A. Krasoulis, T.M. Hall, S. Vijayakumar, A. Jackson, K. Nazarpour

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

Abstract

Motor cortical local field potentials (LFPs) have been successfully used to decode both kinematics and kinetics of arm movement. For future clinically viable prostheses, however, brain activity decoders will have to generalize well under a wide spectrum of behavioral conditions. This property has not yet been demonstrated clearly. Here, we provide evidence for the first time, that an LFP-based electromyogram (EMG) decoder can generalize reasonably well across two different types of behavior. We implanted intracortical microelectrode arrays in the primary motor (M1) and ventral pre-motor (PMv) cortices of a rhesus macaque, and recorded LFP and EMG activity from arm and hand muscles of the contralateral forelimb during a two-dimensional (2-D) centre-out isometric wrist torque task (TT), and during free reach and grasp behavior (FB). Selected temporal and spectral features of the LFP signals were used to train EMG decoders using data from both types of behavior separately. We assessed the decoding performance for both within- and across-task cases. The average achieved generalization score was 65 ± 20%, while in many cases individual scores reached 100%.
Original languageEnglish
Title of host publicationEngineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1630-1633
Number of pages4
DOIs
Publication statusPublished - 1 Aug 2014
EventEngineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE - Sheraton Chicago Hotel and Towers, Chicago, IL, United States
Duration: 26 Aug 201430 Aug 2014

Conference

ConferenceEngineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Country/TerritoryUnited States
CityChicago, IL
Period26/08/1430/08/14

Keywords

  • biomechanics
  • biomedical electrodes
  • brain
  • decoding
  • electromyography
  • feature extraction
  • feature selection
  • generalisation (artificial intelligence)
  • kinematics
  • learning (artificial intelligence)
  • medical signal processing
  • microelectrodes
  • neurophysiology
  • prosthetics
  • sensor arrays
  • signal classification
  • spectral analysis
  • EMG activity recording
  • EMG decoder training
  • EMG decoding generalizability
  • LFP recording
  • LFP signal feature selection
  • LFP-based electromyogram decoder
  • across-task cases
  • arm movement kinematic decoding
  • arm movement kinetic decoding
  • arm muscles
  • average generalization score
  • behavioral conditions
  • brain activity decoders
  • contralateral forelimb
  • decoding performance assessment
  • free reach behavior
  • grasp behavior
  • hand muscles
  • intracortical microelectrode array implantation
  • local field potentials
  • motor cortical LFP
  • prosthesis
  • rhesus macaque primary motor cortices
  • rhesus macaque ventral premotor cortices
  • spectral feature selection
  • temporal feature selection
  • two-dimensional centre-out isometric wrist torque task
  • within-task cases
  • Decoding
  • Educational institutions
  • Electromyography
  • Kinematics
  • Muscles
  • Neuroscience
  • Wrist

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