Comparison of online adaptive learning algorithms for myoelectric hand control

Yue Zhang, Zheng Wang, Zhuo Zhang, Yinfeng Fang, Honghai Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Pattern recognition (PR) based myoelectric hand control has become a research focus in the field of rehabilitative engineer and intelligent control. However, the state of the art method is hardly adopted for clinical use because of signal interfered by shift, fatigue and user-unfriendly of retraining. The aim of this study is to evaluate the performance of different kinds of online algorithms in classifying the myoelectric hand motions, and reveal the key factors to classification accuracy of online learning algorithms. Two groups of experiments on intra-session and inter-session were designed to evaluate the classification and recognition performance of overall methods. The comparison results show that the second-order online learning algorithms outperformed the first-order algorithms in classification and recognition. Soft confidence-weighted learning performs best with 99% classification rate in same session and over 85% recognition rate in different session. This paper uncovers the online learning with large margin and confidence weight can always acquire a good property. In addition, online learning algorithms retrain the classification model by incorporating the testing data to the previous model by measuring the changes between the predicted label and true label which can improve the performance in long-term use.
Original languageEnglish
Title of host publication2016 9th International Conference on Human System Interactions (HSI)
PublisherIEEE
Pages69-75
Number of pages7
ISBN (Electronic)978-1509017294
ISBN (Print)978-1509017300
DOIs
Publication statusPublished - 4 Aug 2016
Event9th International Conference on Human System Interactions: HSI 2016 - University of Portsmouth, Portsmouth, United Kingdom
Duration: 6 Jul 20168 Jul 2016

Conference

Conference9th International Conference on Human System Interactions
Abbreviated titleHSI 2016
Country/TerritoryUnited Kingdom
CityPortsmouth
Period6/07/168/07/16

Keywords

  • surface electromyography
  • pattern recognition
  • online learning algorithm
  • hand motion

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