Prediction of lower-limb joint kinematics from surface EMG during overground locomotion

Justin A. Brantley, Trieu Phat Luu, Sho Nakagome, Jose L. Contreras-Vidal

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

3 Scopus citations

Abstract

Recent advancements in powered lower limb prostheses have led to the development of neural-machine interfaces for natural control during bipedal locomotion. In particular, electromyography (EMG) patterns recorded from the amputated limb can be leveraged to infer the intended gait pattern of the user. However, the optimal control strategy for translating the EMG patterns to kinematic space remains a challenge. In this study, six able bodied subjects were instrumented for mobile brain-body imaging and asked to walk on a multi-terrain gait course. A non-linear extension of the Kalman filter was used to predict knee and ankle joint kinematics from lower limb muscle activation patterns during overground locomotion. Specifically, muscles of the anterior and posterior thigh were used to predict both the knee and ankle joint position. The results revealed that muscles in the thigh can be used to predict the position of the knee and ankle with high accuracy. The highest mean r-value obtained for each of the six subjects was 0.92, 0.77, 0.38, 0.39, 0.63, and 0.77, with corresponding SNR values of 10.8 dB, 6.7 dB, 5.9 dB, 2.8 dB, 9.1 dB, and 9.2 dB, for each subject, respectively. This study is the first to demonstrate that continuous EMG can be used to predict the joint kinematics of the knee and ankle during overground locomotion. This approach may provide improvements during closed-loop control of a powered lower limb prosthesis when compared to other pattern-recognition based methods.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1705-1709
Number of pages5
ISBN (Electronic)9781538616451
DOIs
StatePublished - Nov 27 2017
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: Oct 5 2017Oct 8 2017

Publication series

Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period10/5/1710/8/17

Keywords

  • Electromyography (EMG)
  • Lower-limb prosthesis
  • Myoelectric
  • Unscented Kalman Filter (UKF)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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