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MagnetoMyoGraphy (MMG) is a method of studying muscle function via weak magnetic fields generated from human active organs and tissues. The correspondence between MMG and electromyography means directly derived from the Maxwell-Amp\`ere…

Systems and Control · Electrical Eng. & Systems 2021-04-06 Siming Zuo , Kianoush Nazarpour , Dario Farina , Philip Broser , Hadi Heidari

This study proposes an exercise fatigue detection model based on real-time clinical data which includes time domain analysis, frequency domain analysis, detrended fluctuation analysis, approximate entropy, and sample entropy. Furthermore,…

Machine Learning · Statistics 2018-03-22 Ming-Yen Wu , Chi-Hua Chen , Chi-Chun Lo

Exercise-induced fatigue resulting from physical activity can be an early indicator of overtraining, illness, or other health issues. In this article, we present an automated method for estimating exercise-induced fatigue levels through the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Manuel Lage Cañellas , Constantino Álvarez Casado , Le Nguyen , Miguel Bordallo López

Muscle contraction is often detected via EMG in prosthetics. However, signal disturbances due to electrode motions can lead to misinterpretations. Therefore, alternative measurement approaches are desired to increase the reliability of the…

Medical Physics · Physics 2020-09-17 Roman Kusche , Martin Ryschka

Surface electromyography is a valid tool to gather muscular contraction signals from intact and amputated subjects. Electromyographic signals can be used to control prosthetic devices in a noninvasive way distinguishing the movements…

Machine Learning · Computer Science 2015-11-25 Francesca Giordaniello

Varying contraction levels of muscles is a big challenge in electromyography-based gesture recognition. Some use cases require the classifier to be robust against varying force changes, while others demand to distinguish between different…

Human-Computer Interaction · Computer Science 2019-09-04 Ali Moin , Andy Zhou , Simone Benatti , Abbas Rahimi , Luca Benini , Jan M. Rabaey

While electromyography (EMG) and magnetomyography (MMG) are both methods to measure the electrical activity of skeletal muscles, no systematic comparison between both signals exists. Within this work, we propose a systemic in silico model…

Tissues and Organs · Quantitative Biology 2021-08-12 Thomas Klotz , Leonardo Gizzi , Oliver Röhrle

Surface electromyography provides a practical way to infer human movement intention from wearable muscle recordings, but models trained under a single acquisition setting often lose reliability when the user, session, electrode layout, or…

Machine Learning · Computer Science 2026-05-26 Zhenghao Huang , Huilin Yao , Kaikai Wang

In this study, we developed a method to estimate the relationship between stimulation current and volatility during isometric contraction. In functional electrical stimulation (FES), joints are driven by applying voltage to muscles. This…

Human-Computer Interaction · Computer Science 2021-01-21 Tomoya Kitamura , Yuu Hasegawa , Sho Sakaino , Toshiaki Tsuji

Fatigue is one of the key factors in the loss of work efficiency and health-related quality of life, and most fatigue assessment methods were based on self-reporting, which may suffer from many factors such as recall bias. To address this…

Machine Learning · Computer Science 2020-08-19 Yang Bai , Yu Guan , Wan-Fai Ng

This study investigates the impact of electrode shift and sensor reapplication on common surface electromyography (sEMG) features in lower limb muscles, factors which have, thus far, precluded clinicians from being able to attribute…

Signal Processing · Electrical Eng. & Systems 2025-09-19 Fraser Douglas , Mona Pei , Calvin Kuo

Predicting and understanding the changes in cognitive performance, especially after a longitudinal intervention, is a fundamental goal in neuroscience. Longitudinal brain stimulation-based interventions like transcranial direct current…

Human-Computer Interaction · Computer Science 2024-02-01 Akash K Rao , Shashank Uttrani , Vishnu K Menon , Darshil Shah , Arnav Bhavsar , Shubhajit Roy Chowdhury , Varun Dutt

Musculoskeletal models are pivotal in the domains of rehabilitation and resistance training to analyze muscle conditions. However, individual variability in musculoskeletal parameters and the immeasurability of some internal biomechanical…

Medical Physics · Physics 2025-02-21 Xi Wu , Chenzui Li , Kehan Zou , Ning Xi , Fei Chen

Objective: The main goal of the athletes who undergo anterior cruciate ligament reconstruction (ACLR) surgery is a successful return-to-sport. At this stage, identifying muscular deficits becomes important. Hence, in this study, three…

Medical Physics · Physics 2023-03-14 Mehran Hatamzadeh , Ali Sharifnezhad , Reza Hassannejad , Raphael Zory

The present study analyzes the changes in acceleration produced by swimmers before and after fatiguing effort. The subjects (n=15) performed a 25-meter crawl series at maximum speed without fatigue, and a second series with fatigue. The…

Medical Physics · Physics 2008-01-21 V. Tella , J. L. Toca-Herrera , J. E. Gallach , J. Benavent , L. M. Gonzalez , R. Arellano

Surface electromyography (sEMG) signals exhibit substantial inter-subject variability and are highly susceptible to noise, posing challenges for robust and interpretable decoding. To address these limitations, we propose a discrete…

Signal Processing · Electrical Eng. & Systems 2026-03-02 Yuepeng Chen , Kaili Zheng , Ji Wu , Zhuangzhuang Li , Ye Ma , Dongwei Liu , Chenyi Guo , Xiangling Fu

The probability density function (pdf) of surface Electromyography (sEMG) signals follows any one of the standalone standard distributions: the Gaussian or the Laplacian. Further, the choice of the model is dependent on muscle contraction…

Signal Processing · Electrical Eng. & Systems 2023-01-04 Durgesh Kusuru , Anish C. Turlapaty , Mainak Thakur

Natural gestures are crucial for mid-air interaction, but predicting and managing muscle fatigue is challenging. Existing torque-based models are limited in their ability to model above-shoulder interactions and to account for fatigue…

Human-Computer Interaction · Computer Science 2024-06-14 Yi Li , Benjamin Tag , Shaozhang Dai , Robert Crowther , Tim Dwyer , Pourang Irani , Barrett Ens

The electromyography (EMG) signal is the electrical manifestation of a neuromuscular activation that provides access to physiological processes which cause the muscle to generate force and produce movement. Non invasive prostheses use such…

Machine Learning · Computer Science 2015-11-20 Mara Graziani

Purpose: Critical torque (CT) and work done above it (W') are key predictors of exercise performance associated with neuromuscular fatigue. The aim of the present study was to understand the role of the metabolic cost of exercise in…

Tissues and Organs · Quantitative Biology 2023-03-09 Guillaume Ducrocq , Simon Al Assad , Nabil Kouzkouz , Thomas Hureau