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Title
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Real -Time Multiple Hand Gesture Recognition based on Surface EMG Signals
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Sub-Title |
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Subject |
Human-Machine Control Interface, Surface Electromyography (SEMG), Classification, Degree of Freedom (DOF), Crosstalking of Biological Signals, Artifacts Removal Techniques
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Author |
Nazo Haroon , Anju N. Malik
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Publish Year |
2016 |
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Diss#. |
DOI: 10.14738/jbhi.31.1738 ©2016 IEEE |
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Text Language |
English |
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Accession |
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Library Section |
Research Article |
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Abstract |
Significance of robotics in serving
the human being is increasing day by day. A large
number of impairments and disabilities in human
body force the researchers to think on the
necessity of simple and natural human-machine
control interface. The idea of the project is the
acquisition of SEMG (Surface Electromyographic)
signals from the forearm and to recognize the
various hand gestures. The resulting classification
is then used to control a two degree of freedom
(DOF) robotic gripper. Muscular activity is sensed
by placing the EMG sensors/electrodes on the
skin. The acquired signal from these electrodes is
very small in amplitude and corrupted by
different artifacts due to positioning and pasting
of electrodes, transmission line and crosstalk with
other biological signals. Pre-amplification is
required to boost up the signal and then filtration
is required to get the desired usable band of
frequency. After that artifact-free EMG signal is
further amplified, which can be fed to the cont
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