Intelligent Analysis of EMG Data for Improving Lifestyle

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


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.
Original languageEnglish
Title of host publicationPersonalised Health Management Systems: The Integration of Innovative Sensing, Textile, Information and Communication Technologies
PublisherIOS Press
ISBN (Print)978-1-58603-565-5
Publication statusPublished (in print/issue) - 1 Mar 2005


  • Electromyography
  • Artificial Hand
  • Signal Processing
  • Neural Networks


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