title: Intelligent analysis of EMG data for improving lifestyle.
abstract: In the tragic situation when a person loses his or her hand, they are usually faced with only one option if they wish to regain a good level of mobility; learn to control an artificial hand. It has been suggested that our brain stores a "body map" of the different parts in our body. Thus, if a person loses a hand, their "body map" remains intact and produces phantom sensations that permit the person to feel like they still have their hand. Some discomfort is felt during these sensations; nevertheless, there is a positive side to them as they enable patients to control prosthetic replacements. Sensations experienced can be measured using a method known as Electromyography (EMG) and can be acquired and processed to control an artificial hand. This research involved the acquisition, analysis and classification of EMG signals through construction of a recording device and the development of classification models based on heuristic approaches and Artificial Intelligence classifiers based on Neural Networks to control artificial hands.
authors.affiliation: School of Computing and Mathematics, Faculty of Engineering, University of Ulster at Jordanstown, Northern Ireland.
authors.forename: Mark
authors.initials: M
authors.lastname: Donnelly
authors.forename: Richard
authors.initials: R
authors.lastname: Davies
authors.forename: Chris
authors.initials: C
authors.lastname: Nugent
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001186:Artificial Limbs; D001698:Biomedical Engineering / Q000295:instrumentation; D004576:Electromyography; D006225:Hand; D006801:Humans; D011788:Quality of Life; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D014584:User-Computer Interface