Continuous Kalman Estimation Method for Finger Kinematics Tracking from Surface Electromyography

Journal article


Zhang, H., Peng, B., Tian, L., Samuel, O. and Li, G. 2024. Continuous Kalman Estimation Method for Finger Kinematics Tracking from Surface Electromyography. Cyborg and Bionic Systems. pp. 1-11. https://doi.org/10.34133/cbsystems.0094
AuthorsZhang, H., Peng, B., Tian, L., Samuel, O. and Li, G.
Abstract

Deciphering hand motion intention from surface electromyography (sEMG) encounters challenges posed by the requisites of multiple degrees of freedom (DOF) and adaptability. Unlike discrete action classification grounded in pattern recognition, the pursuit of continuous kinematics estimation is appreciated for its inherent naturalness and
intuitiveness. However, prevailing estimation techniques contend with accuracy limitations and substantial computational demands. Kalman estimation technology,
celebrated for its ease of implementation and real-time adaptability, finds extensive application across diverse domains. This study introduces a continuous Kalman estimation
method, leveraging a system model with sEMG and joint angles as inputs and outputs. Facilitated by model parameter training methods, the approach deduces multiple DOF
finger kinematics simultaneously. The method's efficacy is validated using a publicly accessible database, yielding a correlation coefficient (CC) of 0.73. With over 45,000
windows for training Kalman model parameters, the average computation time remains under 0.01 seconds. This pilot study amplifies its potential for further exploration and
application within the realm of continuous finger motion estimation technology.

KeywordsFinger Kinematics Tracking; hand motion intervention ; surface electromyography (sEMG) encounters
Year2024
JournalCyborg and Bionic Systems
Journal citationpp. 1-11
PublisherAmerican Association for the Advancement of Science
ISSN2692-7632
Digital Object Identifier (DOI)https://doi.org/10.34133/cbsystems.0094
Web address (URL)https://spj.science.org/doi/10.34133/cbsystems.0094
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Output statusPublished
Publication dates
Online12 Jan 2024
Publication process dates
Deposited12 Feb 2024
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