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