Performance analysis of DWT and FMH in classifying hand motions using sEMG signals

Soft computing and intelligent systems: techniques and applications

“…Using a real-world dataset from the UCI machine learning repository, the proposed framework is evaluated and better results are attained in terms of reliability, efficiency, and accuracy. Another interesting problem is addressed in [19]. It compares the impact of two denoising algorithms (DWT and FMH) on the classification of hand motions from surface electromyogram (sEMG) signals.…”