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Using Myoelectric Signals to Manipulate Assisting Robots and Rehabilitation Devices

Using Myoelectric Signals to Manipulate Assisting Robots and Rehabilitation Devices
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Author(s): Mohammadreza Asghari-Oskoei (University of Essex, UK)and Huosheng Hu (University of Essex, UK)
Copyright: 2011
Pages: 20
Source title: Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications
Source Author(s)/Editor(s): Eduardo Alonso (City University, UK)and Esther Mondragón (University College London, UK)
DOI: 10.4018/978-1-60960-021-1.ch008

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Abstract

Myoelectric signal is known as an alternative human-machine interface (HMI) for people with motor disability in dealing with assisting robots and rehabilitation devices. This chapter examines a myoelectric HMI in real-time application and compares its performance with traditional tools. It also studies the manifestation of fatigue in long-term muscular activities and its impact on ultimate performance. The core of applied HMI is built on the support vector machine as a classifier. The experiments confirm that the myoelectric HMI is a reliable alternative to traditional HMI. Meanwhile, they show a significant decline in the dominant frequency of myoelectric signals during long-term applications.

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