LOW-COST REAL-TIME ELECTROMYOGRAPHY (EMG) DATA ACQUISITION EXPERIMENTAL SETUP FOR BIOMEDICAL TECHNOLOGIES EDUCATION

Yıl 2017, Cilt: 7 , 155 - 161, 08.09.2017

Naciye Mulayim Samet Ciklacandir Fatih Cemal Can Savas Sahin

Öz

Electromyography
(EMG) is a technique used in electro-diagnostic therapy by recording and
evaluating the skeletal muscle electrical activity.  When muscle cells are activated, electric
potential, which is produced by these cells, is detected via an
electromyography. These signals can be use analyzing of medical activation
levels, anomalies and detection of recruitment order. At the same time they can
used to make analyses of biomechanics motions of human or animals. In this
study, it was developed a real time EMG data acquisition system based on
threshold level. Firstly, it was generated an EMG sensor and it was obtained
EMG signals by communication between Arduino and LabVIEW interface by using
muscle electrodes. It was purposed to use for developing of a low-cost
real-time application in laboratory for biomedical technologies education.

Anahtar Kelimeler

Real-Time Electromyography (EMG), experimental setup, LabVIEW, biomedical technologies education

Kaynakça

• Rajput J., Prof. Jignesh Vyas, M.E. Student Head of Department, EMG Thresholding Algorithm by using LabVIEW, Department of Biomedical Engineering Government Engineering College, Gandhinagar, Gujarat, India, IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 01, 2015 | ISSN (online): 2321-0613 Retrived from https://en.wikipedia.org/wiki/Electromyography, Alkan A., Gunay M., Identification of EMG signals using discriminant analysis and SVM classifier, Elsevier Journal of Expert Systems with Applications, Vol. 39, Issue 1, pp. 44-47, January 2012. Gonzalez-Ibarra J.C., Soubervielle-Montalvo C., Vital-Ochoa O., Perez-Gonzalez H. G., EMG Pattern Recognition System Based on Neural Networks, Eleventh Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence and Applications, 2012.. Subasi A., Classification of EMG signals using combined features and soft computing techniques, International Journal of Applied Soft Computing, Vol. 12, Issue 8, pp. 2188-2198, August 2014.. Pradeep C, George S., K2 Control of Stepper Motor Using Surface EMG Signals International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 4, Issue 10, October 2015 Copyright to IJAREEIE DOI: 10.15662/IJAREEIE.2015.0410038 8326 Retrived from http://www.instructables.com/id/Muscle-EMG-Sensor-for-a-Microcontroller/ ANDRYNOWSKA A., KLEKIEL T., Application Of INA122 Amplifier To Measure Of Emg Signals, Aktualne Problemy Biomechaniki, nr 5/2011