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February 27, 2026IEEE Transactions on Neural Systems and Rehabilitation Engineering0 citationsOpen Access

A Lightweight Hybrid Encoder-decoder Framework for Multiple Degree of Freedom Muscle Force Estimation

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YZYang ZhengYLYixin LiHZHaixiong Zhang

Key Points

  • The aim is to develop a hybrid encoder-decoder framework for estimating muscle forces in dexterous movements.
  • Developed a lightweight hybrid encoder-decoder model.
  • Applied the model to predict muscle forces for finger movements.
  • Evaluated the model's performance against existing methods.
  • The hybrid framework showed improved accuracy in force estimation.
  • It reduced computational load compared to traditional models.
  • The method indicates potential for practical human machine interfaces.

Abstract

Further development of the proposed method could potentially provide a robust human machine interface for dexterous finger force prediction in realistic applications.

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Cite This Study

Zheng et al. (2026) studied this question.

synapsesocial.com/papers/69a1344fed1d949a99abe1dchttps://doi.org/10.1109/tnsre.2026.3667588
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