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Kang, Sang Hoon
Robotics and Rehab. Engineering Lab (R2EL)
Research Interests
  • Rehabilitation Robotics & Mechatronic Tools, Biomechanics for Rehabilitation, Human Limb Impedance Estimation, Assistive and Healthcare robotics, Robust Motion/Force Control


EMG-Based Real-Time Linear-Nonlinear Cascade Regression Decoding of Shoulder, Elbow and Wrist Movements in Able-Bodied Persons and Stroke Survivors

DC Field Value Language Liu, Jie ko Ren, Yupeng ko Xu, Dali ko Kang, Sang Hoon ko Zhang, Li-Qun ko 2019-08-22T01:59:32Z - 2019-08-21 ko 2020-05 ko
dc.identifier.citation IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, v.67, no.5, pp.1272 - 1281 ko
dc.identifier.issn 0018-9294 ko
dc.identifier.uri -
dc.description.abstract Objective: This study aimed to decode shoulder, elbow and wrist dynamic movements continuously and simultaneously based on multi-channel surface electromyography signals, useful for electromyography controlled exoskeleton robots for upper-limb rehabilitation. Methods: Ten able-bodied subjects and ten stroke subjects were instructed to voluntarily move the shoulder, elbow and wrist joints back and forth in a horizontal plane with an exoskeleton robot. The shoulder, elbow and wrist movements and surface electromyography signals from six muscles crossing the joints were recorded. A set of three parallel linear-nonlinear cascade decoders was developed to continuously estimate the selected shoulder, elbow and wrist movements based on a generalized linear model using the anterior deltoid, posterior deltoid, biceps brachii, long head triceps brachii, flexor carpi radialis, and extensor carpi radialis muscle electromyography signals as the model inputs. Results: The decoder performed well for both healthy and stroke populations. As movement smoothness decreased, decoding performance decreased for the stroke population. Conclusion: The proposed method is capable of simultaneously and continuously estimating multi-joint movements of the human arm in real-time by characterizing the nonlinear mappings between muscle activity and kinematic signals based on linear regression. Significance: This may prove useful in developing myoelectric controlled exoskeletons for motor rehabilitation of neurological disorders. ko
dc.language 영어 ko
dc.publisher Institute of Electrical and Electronics Engineers ko
dc.title EMG-Based Real-Time Linear-Nonlinear Cascade Regression Decoding of Shoulder, Elbow and Wrist Movements in Able-Bodied Persons and Stroke Survivors ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-85083954994 ko
dc.identifier.wosid 000530299200005 ko
dc.type.rims ART ko
dc.identifier.doi 10.1109/tbme.2019.2935182 ko
dc.identifier.url ko
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