Donnelly, Mark, Davies, Richard and Nugent, Christopher (2005) Intelligent Analysis of EMG Data for Improving Lifestyle. In: Personalised Health Management Systems: The Integration of Innovative Sensing, Textile, Information and Communication Technologies. IOS Press, pp. 229-234. ISBN 978-1-58603-565-5 [Book section]
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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.
|Item Type:||Book section|
|Keywords:||Electromyography, Artificial Hand, Signal Processing, Neural Networks|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Smart Environments
|Deposited By:||Dr Mark Donnelly|
|Deposited On:||01 Feb 2010 10:53|
|Last Modified:||14 Mar 2013 09:12|
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