Fig 1.
Distribution of participants’ BMI values.
Table 1.
Typical feature list of sEMG and ACC signals.
Fig 2.
Flowchart of LFAM for feature fusion.
Fig 3.
A. Channel attention mechanism. B. Neuron attention mechanism.
Fig 4.
Structure diagram of sEMG and ACC fatigue prediction classification model.
Table 2.
Model parameter settings.
Table 3.
Hardware models and software versions.
Fig 5.
The training process of each classification model.
Fig 6.
Model recognition performance in different pseudo-artifact environments.
A. Accuracy, B. Precision, C. Recall, D. F1-score.
Table 4.
Computational analysis of each model.
Table 5.
Comparison of statistical parameters of different methods.