Authors:
Clive Seguna
;
Adrian Von Brockdorff
;
Jeremy Scerri
and
Kris Scicluna
Affiliation:
Department of Electrical and Electronics Engineering, MCAST, Corradino Hill Paola, PLA9032, Malta
Keyword(s):
EMG, Electromyography, Biopotential, Myoelectric.
Abstract:
Researchers commonly use myoelectric signals to study the electrical activity produced by skeletal muscles for the control of prosthetic arms, hands and limb replacement devices. Additionally, to the application in prostheses, a myoelectric control system for multiple finger movements has the potential to develop commercial products including advanced human-computer interfaces. The objective of this work is to implement a set of low-cost active electrodes for the decoding of finger movement via time-domain analysis, with an auto-gain adjustment technique. Different people will have different EMG amplitudes; therefore, it is difficult to determine the gain required prior performing further signal processing. In this work, an auto-adjustable gain amplifier circuit processes the maximum EMG signal amplitude and adjusts the gain stage accordingly, without the need of any user interaction. This ensures that the gain is always automatically adjusted to get the most effective performance fr
om the data acquisition or analogue to digital converter (ADC) module since the signal will be neither too low in amplitude to cause inefficient use of the ADC resolution, nor too high to cause saturation of the signal. Through extensive experiments, the developed low-cost EMG data acquisition system achieves reproducible and repeatable results for the detection and classification of the five finger movements.
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