title: Ranking hand movements for myoelectric pattern recognition considering forearm muscle structure.
abstract: Previous pattern recognition algorithms using surface electromyography (sEMG) have been developed for subsets of predefined hand movements without considering muscle structure. In order to decode hand movements, it is important to know which movements are appropriate for PR due to the different independence of movements between individuals and the high correlated characteristics of sEMG patterns between movements. This paper proposes a method to personally rank the order of hand movements from subsets (31 finger flexion, 31 finger extension, and 4 wrist movements in this paper). The movements were sorted into a ranked order with respect to the locations of the electrodes on the proximal forearm and the distal forearm. We evaluated the classification error as the number of desired movements (Nm) changed. The maximum Nmwith an error lower than 10% was 20 for the proximal forearm and 10 for the distal forearm from ranked movements of individuals. Our method could help to identify the optimized order of hand movements considering the personal characteristics of each individual.
authors.affiliation: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
authors.forename: Youngjin
authors.initials: Y
authors.lastname: Na
authors.affiliation: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
authors.forename: Sangjoon J
authors.initials: SJ
authors.lastname: Kim
authors.affiliation: School of Computing, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. shjo@cs.kaist.ac.kr.
authors.forename: Sungho
authors.initials: S
authors.lastname: Jo
authors.affiliation: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. jungkim@kaist.ac.kr.
authors.forename: Jung
authors.initials: J
authors.lastname: Kim
mesh_terms: D000328:Adult; D004576:Electromyography / Q000379:methods*; D005260:Female; D005542:Forearm / Q000502:physiology*; D006225:Hand / Q000502:physiology*; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Hand movement; Pattern recognition; Rank order; Surface electromyography