Abstract
One of the greatest challenges of using a myoelectric prosthetic hand in daily life is to conveniently measure stable myoelectric signals. This study proposes a novel surface electromyography (sEMG) sensor using polypyrrole-coated nonwoven fabric sheet as electrodes (PPy electrodes) to allow people with disabilities to control prosthetic limbs. The PPy electrodes are sewn on an elastic band to guarantee close contact with the skin and thus reduce the contact electrical impedance between the electrodes and the skin. The sensor is highly customizable to fit the size and the shape of the stump so that people with disabilities can attach the sensor by themselves. The performance of the proposed sensor was investigated experimentally by comparing measurements of Ag/AgCl electrodes with electrolytic gel and the sEMG from the same muscle fibers. The high correlation coefficient (0.87) between the two types of sensors suggests the effectiveness of the proposed sensor. Another experiment of sEMG pattern recognition to control myoelectric prosthetic hands showed that the PPy electrodes are as effective as Ag/AgCl electrodes for measuring sEMG signals for practical myoelectric control. We also investigated the relation between the myoelectric signals' signal-to-noise ratio and the source impedances by simultaneously measuring the source impedances and the myoelectric signals with a switching circuit. The results showed that differences in both the norm and the phase of the source impedance greatly affect the common mode noise in the signal.
Highlights
Robotic prosthetic hands have benefitted from significant improvements due to the quick advance of robotics and biomedical engineering in the last decade
This study introduces a surface electromyogram (sEMG) electrode made of polypyrrole-coated nonwoven fabric sheet (PPy electrode) that can be customized to any person and can be worn onehanded for stable measurement of sEMG signals
We have proposed a sEMG sensor using PPy electrodes for practical myoelectric control of prosthetic hands in daily life
Summary
Robotic prosthetic hands have benefitted from significant improvements due to the quick advance of robotics and biomedical engineering in the last decade. In regard to the human interface, electromyography (EMG) signals associated with sEMG Sensor for Prosthetic Hand residual muscle contraction, from which the user’s motion volition is recognized according to the remnant muscle activity, have been studied (Asghari Oskoei and Hu, 2007). Despite the significant improvement of the mechanics and the EMG analysis methods, most of the currently commercially available myoelectric prosthetic hands used by amputees are still controlled by very simple algorithms that process the surface electromyogram (sEMG) to control 1◦C of freedom (DoF) at a time. The main problem for applying advanced algorithms to control dexterous prosthetic hands in real life is the difficulty of measuring stable myoelectric signals. In real-life applications, the differences caused by analysis algorithms are less than those caused by measurement methods, since the quality of the EMG signal determines the usability and the stability of the myoelectric control
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