Document Type : Research Paper
Authors
Computer Engineering Department, University of Technology-Iraq, Baghdad Iraq
Abstract
Recent advances in the control applications based on hand nerve
signals are able to meet the needs of users who suffer from restrictions in limb
movement and also provide high performance control for those paralyzed
people. These signals are represented as Electromyography (EMG) signals,
which are biomedical ones, used for clinical/biomedical applications. In this
work, a control signals generation system is proposed based on hand EMG
measurements. The process of acquisition and processing of EMG signals is
performed by only one channel surface EMG electrodes with one EMG
processing unit as a muscle sensor. In this work, Arduino UNO is adopted as an
analog to digital converter for these hand nerve signals to be easily analyzed in
the classification process. These signals are measured from the skin surface of
forearm and biceps muscles in two suggested case studies to be used in
generating signals based on ten muscles movements. The main features that
crystallized this research is building a smart control algorithm which increases
the flexibility of generating precise control signals based on contracted hand
movements with high simplicity of use and the low cost. The obtained results are
compared to other systems results to show the ability of achieving 93.81%
classification rate or accuracy among other systems.
Keywords
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