Prosthetic Robotic Arm Control System Using Emg Signal Detection

Utama, Jana and Barry Husein, Abdul (2015) Prosthetic Robotic Arm Control System Using Emg Signal Detection. ICo-ApICT 2015.

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This research presents robotic arm control which controlled using EMG signal detection. Based on the characteristics of EMG, these signals have a voltage range between 0-10 mV and frequency range between 20-500Hz. The electrode sensor is needed to read contraction muscle signals. These signals will be processed in EMG instrumentation: instrumentation amplifier, non-inverting amplifier, filter and clamper to get those EMG characteristics. Next, these signals will be sent to personal computer (PC) using serial communication and internal analog to digital converter (ADC) technique from ATMega8535 with 2000 sample/seconds. Raw data signal will be processed with digital filter, feature extraction and classification process using Lab VIEW 8.5. Feature extraction will be processed in time domain to get integrated EMG (IEMG) value. Classification will determine which arm movement that obtained and then will control robotic arm movement based on the classification data. Artificial neural network (ANN) with perceptron method is used in this classification process. Based on the testing result, this EMG instrumentation has a total gain about 548,85 and frequency range about 18-460 Hz. The response of this system is about 1,434 second that got by do a response system testing to detect a hand movement. Testing last received presentations accuracy of 100% for the extension supination movements, 80% for flexion supination and pronation 80% for flexion movements.

Item Type: Article
Uncontrolled Keywords: Electromyography (EMG), EMG Instrumentation, EMG Signal Analysis, Artificial Neural Network (ANN)
Subjects: Prosiding > ICo-ApICT 2015
Divisions: Universitas Komputer Indonesia > Perpustakaan UNIKOM
Date Deposited: 10 Dec 2015 10:25
Last Modified: 31 Jan 2019 10:25

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