GDL

Journal from gdlhub / 2020-01-09 11:30:00
By : Triwiyanto Triwiyanto, I Putu Alit Pawana, Bambang Guruh Irianto, Tri Bowo Indrato, I Dewa Gede Hari Wisana, Telkomnika
Created : 2020-01-09, with 1 files

Keyword : electromyography, embedded system, exoskeleton, feature extraction, zero crossing
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/issue/view/640
Document Source : web

A major problem in an exoskeleton based on electromyography (EMG) control with pattern

recognition-based is the need for more time to train and to calibrate the system in order able to adapt for

different subjects and variable. Unfortunately, the implementation of the joint prediction on an embedded

system for the exoskeleton based on the EMG control with non-pattern recognition-based is very rare.

Therefore, this study presents an implementation of elbow-joint angle prediction on an embedded system

to control an upper limb exoskeleton based on the EMG signal. The architecture of the system consisted of

a bio-amplifier, an embedded ARMSTM32F429 microcontroller, and an exoskeleton unit driven by a servo

motor. The elbow joint angle was predicted based on the EMG signal that is generated from biceps.

The predicted angle was obtained by extracting the EMG signal using a zero-crossing feature and filtering

the EMG feature using a Butterworth low pass filter. This study found that the range of root mean square

error and correlation coefficients are 8°-16° and 0.94-0.99, respectively which suggest that the predicted

angle is close to the desired angle and there is a high relationship between the predicted angle and

the desired angle.

Keywords: electrom

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