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Related papers: Topology of surface electromyogram signals: hand g…

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Objective. In this article, we present data and methods for decoding speech articulations using surface electromyogram (EMG) signals. EMG-based speech neuroprostheses offer a promising approach for restoring audible speech in individuals…

Computation and Language · Computer Science 2025-10-07 Harshavardhana T. Gowda , Zachary D. McNaughton , Lee M. Miller

Upper limb based neuromuscular interfaces aim to provide a seamless way for humans to interact with technology. Among noninvasive interfaces, surface electromyogram (EMG) signals hold significant promise. However, their sensitivity to…

Robust and accurate decoding of gesture from non-invasive surface electromyography (sEMG) is important for various applications including spatial computing, healthcare, and entertainment, and has been actively pursued by researchers and…

Human-Computer Interaction · Computer Science 2026-02-17 Adyasha Dash , Giulia Zappoli , Laya Das , Robert Riener

Surface electromyography (EMG) serves as a pivotal tool in hand gesture recognition and human-computer interaction, offering a non-invasive means of signal acquisition. This study presents a novel methodology for classifying hand gestures…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Abu Saleh Musa Miah , Najmul Hassan , Md. Maniruzzaman , Nobuyoshi Asai , Jungpil Shin

We present a system for decoding hand movements using surface EMG signals. The interface provides real-time (25 Hz) reconstruction of finger joint angles across 20 degrees of freedom, designed for upper limb amputees. Our offline analysis…

Electromyography (EMG) signals are obtained from muscle cell activity. The recording and analysis of EMG signals has several applications. The EMG is of diagnostic importance for treating patients suffering from neurological and…

Systems and Control · Electrical Eng. & Systems 2025-09-18 Vinay C K , Vikas Vazhayil , Madhav rao

Surface electromyography (sEMG) is becoming exceeding useful in applications involving analysis of human motion such as in human-machine interface, assistive technology, healthcare and prosthetic development. The proposed work presents a…

Signal Processing · Electrical Eng. & Systems 2020-05-05 Karush Suri , Rinki Gupta

EMG-based hand gesture recognition uses electromyographic~(EMG) signals to interpret and classify hand movements by analyzing electrical activity generated by muscle contractions. It has wide applications in prosthesis control,…

Machine Learning · Computer Science 2024-11-26 Parshuram N. Aarotale , Ajita Rattani

Surface electromyography (sEMG) is a technology to assess muscle activation, which is an important component in applications related to diagnosis, treatment, progression assessment, and rehabilitation of specific individuals' conditions.…

Surface Electromyography (sEMG) provides vital insights into muscle function, but it can be noisy and challenging to acquire. Inertial Measurement Units (IMUs) provide a robust and wearable alternative to motion capture systems. This paper…

Machine Learning · Computer Science 2025-11-24 Shubhranil Basak , Mada Hemanth , Madhav Rao

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

An accurate classification of upper limb movements using electroencephalography (EEG) signals is gaining significant importance in recent years due to the prevalence of brain-computer interfaces. The upper limbs in the human body are…

Signal Processing · Electrical Eng. & Systems 2023-04-14 Saadat Ullah Khan , Muhammad Majid , Syed Muhammad Anwar

Thumb gestures provide an effective and unobtrusive input modality for wearable and always-available human-machine interaction. Wrist-worn surface electromyography (sEMG) has emerged as a promising approach for compact and wearable…

Human-Computer Interaction · Computer Science 2026-04-07 Wenjuan Zhong , Chenfei Ma , Kianoush Nazarpour

Surface Electromyography (sEMG/EMG) is to record muscles' electrical activity from a restricted area of the skin by using electrodes. The sEMG-based gesture recognition is extremely sensitive of inter-session and inter-subject variances. We…

Machine Learning · Computer Science 2019-12-02 István Ketykó , Ferenc Kovács , Krisztián Zsolt Varga

Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs the body to perform both fine and coarse locomotion. This technique has seen extensive investigation over the…

Human-Computer Interaction · Computer Science 2021-04-06 Mingde Zheng , Michael S. Crouch , Michael S. Eggleston

Upper limb movement classification, which maps input signals to the target activities, is a key building block in the control of rehabilitative robotics. Classifiers are trained for the rehabilitative system to comprehend the desires of the…

Machine Learning · Computer Science 2023-03-10 Zihao Wang , Ravi Suppiah

Decoding brain activity from electroencephalography (EEG) is crucial for neuroscience and clinical applications. Among recent advances in deep learning for EEG, geometric learning stands out as its theoretical underpinnings on symmetric…

Artificial Intelligence · Computer Science 2026-02-27 Haohui Jia , Zheng Chen , Lingwei Zhu , Xu Cao , Yasuko Matsubara , Takashi Matsubara , Yasushi Sakurai

Electromyography (EMG) is a way of measuring the bioelectric activities that take place inside the muscles. EMG is usually performed to detect abnormalities within the nerves or muscles of a target area. The recent developments in the field…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Niloy Sikder , Abu Shamim Mohammad Arif , Abdullah-Al Nahid

Objective: We present magnetomyograms (MMG) of TMS-evoked movement in a human hand, together with a simultaneous surface electromyograph (EMG) and electroencephalograph (EEG) data. Approach: We combined TMS with non-contact magnetic…

Neuromotor decoding from upper-limb electromyography (sEMG) can enhance human-machine interfaces and offer a more natural means of controlling prosthetic limbs, virtual reality, and household electronics. Unfortunately, current sEMG…

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