Research
Neural
The grip force prediction model established using dual-channel sEMG signals achieved an R2 of 0.9215.
This high R2 value indicates reliable grip force predictions, useful for training and rehabilitation.
StrongSupportsmedium confidence
the performance of the grip force prediction algorithm had an R2 of 0.9215.
Why this rating
The model's performance is quantitatively assessed.
Source
A Surface Electromyography (sEMG) System Applied for Grip Force Monitoring
Dantong Wu et al. · Sensors · 2024
otherCited 11×
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