It was purposed to use for developing of a low-cost real-time application in laboratory for biomedical technologies education.
📌 3 Key Takeaways
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Objective & Hypothesis: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.
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Key Findings & Data:Firstly, it was generated an EMG sensor and it was obtained EMG signals by communication between Arduino and LabVIEW interface by using muscle electrodes.
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Conclusion & Impact:It was purposed to use for developing of a low-cost real-time application in laboratory for biomedical technologies education.
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.
Mulayim, N., Ciklacandir, S., Can, F. C., Sahin, S. (2017). LOW-COST REAL-TIME ELECTROMYOGRAPHY (EMG) DATA ACQUISITION EXPERIMENTAL SETUP FOR BIOMEDICAL TECHNOLOGIES EDUCATION. The Eurasia Proceedings of Educational and Social Sciences, Volume: 7. https://ajindex.com/articles/1550229
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.
ANDRYNOWSKA A., KLEKIEL T., Application Of INA122 Amplifier To Measure Of Emg Signals, Aktualne Problemy Biomechaniki, nr 5/2011
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.