Table 4 A summary of other hybrid soft computing techniques applied to EMG analysis
From: Hybrid soft computing systems for electromyographic signals analysis: a review
Reference | Task | Techniques | Results |
|---|---|---|---|
[99] | Classification: 7 limb motions | ACO + DE | Accuracy: 94.73% (validation), 93.39% (test), better than ULDA and PCA |
[100] | Classification: 7 limb motions | FL + LDA + DE | Accuracy: 93.75% (time domain feature), 94.71% (wavelet feature) |
[101] | Classification: 7 limb motions | FL + LDA + PSO | Accuracy: Similar to ANTDE in [102], better than FLDA, ULDA, OLDA, and PCA |
[102] | Modelling: EMG-force | GA + FL | RMS error: 12.4% |