title: Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review.
abstract: The surface electromyography (sEMG) signal separation and decphompositions has always been an interesting research topic in the field of rehabilitation and medical research. Subtle myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of myoelectric signals to control human-assisting robots or rehabilitation devices. This paper reviews recent research and development in independent component analysis and Fractal dimensional analysis for sEMG pattern recognition, and presents state-of-the-art achievements in terms of their type, structure, and potential application. Directions for future research are also briefly outlined.
authors.affiliation: School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia. ganesh.naik@rmit.edu.au
authors.forename: Ganesh R
authors.initials: GR
authors.lastname: Naik
authors.forename: Sridhar
authors.initials: S
authors.lastname: Arjunan
authors.forename: Dinesh
authors.initials: D
authors.lastname: Kumar
mesh_terms: D004576:Electromyography / Q000379:methods*; D017709:Fractals; D006801:Humans; D009068:Movement / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D012879:Skin Physiological Phenomena