A Comparative Study of Wavelet Denoising for Multifunction Myoelectric Control

By Angkoon Phinyomark, Chusak Limsakul, Pornchai Phukpattaranont. International Conference on Computer and Automation Engineering, 2009

60 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/1182fd34ed22d9de0d96097c3764ed55eefd1393

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Pornchai Phukpattaranont
2. Angkoon Phinyomark
3. Chusak Limsakul

In Computer Vision and Pattern Recognition

1. Pornchai Phukpattaranont
2. Angkoon Phinyomark
3. Chusak Limsakul

In Mechanics of Materials

1. Pornchai Phukpattaranont
2. Angkoon Phinyomark
3. Chusak Limsakul

Citations in the corpus

• A Novel Feature Extraction for Robust EMG Pattern Recognition (2009, methodology): “Generally, white Gaussian noise (WGN) is used to represent the random noise in sEMG signal analysis [5-6].”
• Surface Electromyography Signal Processing and Classification Techniques (2013, methodology): “Wavelet de-noising algorithms can effectively remove these noises [44].”