arXiv Machine Learning June 24, 2026 By Nia Touko, Matthew O A Ellis, Cristiano Capone, Alessio Burrello, Elisa Donati, Luca Manneschi

Lightweight Test-Time Adaptation for EMG-Based Gesture Recognition

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arXiv:2601. 04181v2 Announce Type: replace Abstract: Reliable long-term decoding of gestures from surface electromyography (EMG) is hindered by signal drift caused by electrode displacement, muscle fatigue, and/or posture changes.

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arXiv Machine Learning

Sep 23

EMGBlend: Heterogeneity-Aware Self-Supervised Pretraining for Gesture and Force Decoding

arXiv:2609.25582v1 Announce Type: new Abstract: Public surface electromyography (EMG) datasets vary widely in electrode layout, channel count, frequency support, and size. Simply mixing them for pret...

By Yuwei Jia, Cheng Zhong, Jinyang Yu, Zhe Cui

arXiv Machine Learning

Jul 31

Recognition and Label-Free Adaptation Across Recording Sessions in Surface-EMG Gesture Decoding

arXiv:2607. 27568v1 Announce Type: new Abstract: Recognition accuracy obtained during a recording session does not persist when a user puts on the electrodes again after the electrodes had previously been removed.

By Jethro Odeyemi, W. J. Zhang

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arXiv AI

Jul 1

PGUDA: Pressure-Guided Unsupervised Domain Adaptation with Cross-Modal Knowledge Distillation for sEMG-Based Gesture Recognition

arXiv:2606. 31349v1 Announce Type: cross Abstract: Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction.

By Yurui Liu, Xiao-Cong Zhong, Qisong Wang, Xuefu Wang, Dan Liu, Jinwei Sun

fine-tuning efficiency multimodal benchmarks

arXiv AI

Jul 28

Multimodal Surface EMG Hand Gesture Recognition Using Query-Based Transformers for Prosthetic Control

arXiv:2607. 22779v1 Announce Type: cross Abstract: Hand gesture recognition via surface electromyography (sEMG) is fundamental to prosthetic control.

By Federico Del Pup, Elisa Tentori, Manfredo Atzori

llms multimodal benchmarks

arXiv Machine Learning

Jul 7

Conservative Subject Invariant EMG-based Gesture Recognition

arXiv:2607. 03783v1 Announce Type: new Abstract: Cross-subject generalization remains a fundamental challenge in surface electromyography (sEMG)-based gesture recognition.

By Hamed Rafiei, Ali Mousavi

benchmarks safety

arXiv Machine Learning

Jul 7

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

arXiv:2607. 04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic control and motor rehabilitation.

By Sofia Gilardini, Chenfei Ma, Kianoush Nazarpour

rag multimodal

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EMGBlend: Heterogeneity-Aware Self-Supervised Pretraining for Gesture and Force Decoding

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