Jun 10, 2022 · This work studies the clinical readiness of a multimodal fusion model that estimates hand force based on the surface electromyography (sEMG) and A-mode ...

Dec 11, 2022 · Compared to high-density sEMG, sparse sEMG consumes fewer computation resources, with the absolute estimation error reaching 2.06 and 2.04% on ...

A multimodal fusion model for estimating human hand force: Comparing surface electromyography and ultrasound signals. Y Zou, L Cheng, Z Li. IEEE Robotics ...

Jul 21, 2024 · A Multimodal Fusion Model for Estimating Human Hand Force: Comparing surface electromyography and ultrasound signals. IEEE Robotics Autom ...

Oct 8, 2023 · This paper presents a multi-modal fusion for hand gesture recognition (MFHG) model, which uses two heterogeneous networks to extract and fuse the features.

A multimodal fusion model for estimating human hand force: Comparing surface electromyography and ultrasound signals. Y Zou, L Cheng, Z Li. IEEE Robotics ...

Zou et al. A Multimodal Fusion Model for Estimating Human Hand Force: Comparing Surface Electromyography and Ultrasound Signals. IEEE Robotics and Automation ...

A Multimodal Fusion Model for Estimating Human Hand Force Comparing Surface Electromyography and Ultrasound Signals By Yongxiang Zou, Long Cheng, and Zhengwei ...

This article demonstrates the potential of A-mode US in automated gesture recognition, and the prospect of sEMG/US fusion for proportional gesture ...

A Multimodal Fusion Model for Estimating Human Hand Force: Comparing Surface Electromyography and Ultrasound Signals. Article. Dec 2022. Yongxiang Zou ...