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April 29, 2026CCF Transactions on Pervasive Computing and InteractionOpen Access

A Multimodal benchmark of EMG and 3D hand motion for gesture recognition and biometric authentication

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Authors

WAWejdan Al-Mari HAHamda Al-Marri SASheyma Al-Jaber

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Overview

Experimental results demonstrate multimodal fusion improves biometric authentication and gesture recognition, highlighting the role of EMG and skeleton data.

Key Points

This research aims to enhance biometric authentication and gesture recognition using multimodal data fusion.
Developed a novel dataset combining EMG and 3D hand motion data.
Participants performed three gestures (wave, fist, thumbs-up).
Evaluated classifier performance for authentication and recognition tasks with accuracy metrics.
Unimodal EMG and skeleton classifiers achieved accuracies of 95.6% and 92.5%, respectively.
Classifier-level fusion yielded a 99.4% accuracy for authentication.
Skeleton modality alone reached 99.16% accuracy for gesture recognition.

Cite This Study

Al-Mari et al. (2026) studied this question.

synapsesocial.com/papers/69f154a4879cb923c4944c4b https://doi.org/10.1007/s42486-026-00232-4

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April 29, 2026CCF Transactions on Pervasive Computing and InteractionOpen Access

A Multimodal benchmark of EMG and 3D hand motion for gesture recognition and biometric authentication

View Full Paper

Ask AI

Bookmark

Authors

WAWejdan Al-Mari HAHamda Al-Marri SASheyma Al-Jaber

Discussion

Member takes

Overview

Experimental results demonstrate multimodal fusion improves biometric authentication and gesture recognition, highlighting the role of EMG and skeleton data.

Key Points

This research aims to enhance biometric authentication and gesture recognition using multimodal data fusion.
Developed a novel dataset combining EMG and 3D hand motion data.
Participants performed three gestures (wave, fist, thumbs-up).
Evaluated classifier performance for authentication and recognition tasks with accuracy metrics.
Unimodal EMG and skeleton classifiers achieved accuracies of 95.6% and 92.5%, respectively.
Classifier-level fusion yielded a 99.4% accuracy for authentication.
Skeleton modality alone reached 99.16% accuracy for gesture recognition.

Cite This Study

Al-Mari et al. (2026) studied this question.

synapsesocial.com/papers/69f154a4879cb923c4944c4b https://doi.org/10.1007/s42486-026-00232-4

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