Examination of Interlimb Coordination of Human Asymmetrical Gait

Khoo, Akingson Chun Yep; Yap, Yi Ting; Gouwanda, Darwin; Gopalai, Alpha Agape

doi:10.1109/iecbes.2018.8626691

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…Therefore, how to accelerate recovery from stroke and restore walking ability has become a research focus in stroke treatment [2]. Many stroke patients suffer from foot pronation, foot drop, and lower limb spasm due to the reduced lower-limb muscle strength, and asymmetrical gaits can often be observed when they are walking [39]. Therefore, improving asymmetrical gaits is a major focus of rehabilitation and patients' top goal [36].…”

Section: Introductionmentioning

confidence: 99%

Multi-Channel FES Gait Rehabilitation Assistance System Based on Adaptive sEMG Modulation

Lu,

Ge,

Tang

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Functional electrical stimulation (FES) can be used to stimulate the lower-limb muscles to provide walking assistance to stroke patients. However, the existing surface electromyography (sEMG)-based FES control methods mostly only consider a single muscle with a fixed stimulation intensity and frequency. This study proposes a multi-channel FES gait rehabilitation assistance system based on adaptive myoelectric modulation. The proposed system collects sEMG of the vastus lateralis muscle on the non-affected side to predict the sEMG values of four targeted lower-limb muscles on the affected side using a bidirectional long short-term memory (BILSTM) model. Next, the proposed system modulates the real-time FES output frequency for four targeted muscles based on the predicted sEMG values to provide muscle force compensation. Fifteen healthy subjects were recruited to participate in an offline model-building experiment conducted to evaluate the feasibility of the proposed BILSTM model in predicting the sEMG values. The experimental results showed that the R 2 value of the best-obtained prediction result reached 0.85 using the BILSTM model, which was significantly higher than that using traditional prediction methods. Moreover, two patients after stroke were recruited in the online assisted-walking experiment to verify the effectiveness of the proposed walking-assistance system. The experimental results showed that the activation of the target muscles of the patients was higher after FES, and the gait movement data were significantly different before and after FES. The proposed system can be effectively applied to walking assistance for stroke patients, and the experimental results can provide new ideas and methods for sEMG-controlled FES rehabilitation applications.

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Section: Introductionmentioning

confidence: 99%

Multi-Channel FES Gait Rehabilitation Assistance System Based on Adaptive sEMG Modulation

Lu,

Ge,

Tang

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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High-dimensional Time-series Gait Analysis using a Full-body Wireless Wearable Motion Sensing System and Convolutional Neural Network

Gresham

Torres

Britton

et al. 2022

2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)

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Instantaneous Segmental Energy Symmetry Index as Gait Compensation Indicator in Asymmetrical Walking

Yap

Gouwanda

Gopalai

et al. 2019

IJIE

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Understanding the energy expenditure of human loco motion has been an area of great interest in gait analysis [1]. Energy expenditure can be determined either by quantifying the metabolic or mechanical energetic cost. The first o ne is the most direct approach. It is derived fro m the prediction of metabolic function of the body th rough proxies such as the body demand for adenosine triphosphate (ATP) during an activ ity, wh ich is reflected in the change in volumetric rate of oxygen consumption. The rate of o xygen consumption signifies the rate of cellu lar respiration, which is directly proportional to the intensity of the activity [1]. However, th is method only measures how much energy is expended by

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Examination of Interlimb Coordination of Human Asymmetrical Gait

Cited by 4 publications

References 14 publications

Multi-Channel FES Gait Rehabilitation Assistance System Based on Adaptive sEMG Modulation

Multi-Channel FES Gait Rehabilitation Assistance System Based on Adaptive sEMG Modulation

High-dimensional Time-series Gait Analysis using a Full-body Wireless Wearable Motion Sensing System and Convolutional Neural Network

Instantaneous Segmental Energy Symmetry Index as Gait Compensation Indicator in Asymmetrical Walking

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