Comparison of Different Time and Frequency Domain Feature Extraction Methods on Elbow Gesture’s EMG
| Autor: | Cemil Altın, Orhan Er |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
business.industry Noise (signal processing) Elbow Feature extraction Process (computing) Pattern recognition 02 engineering and technology Signal k-nearest neighbors algorithm 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Frequency domain 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Artificial intelligence business 030217 neurology & neurosurgery Gesture |
| Zdroj: | European Journal of Interdisciplinary Studies. 2:35 |
| ISSN: | 2411-4138 2411-958X |
| DOI: | 10.26417/ejis.v2i3.p35-44 |
| Popis: | Objective:In this study we will get EMG signals from arm for different elbow gestures, than filtering the signal and later classification the signal. The reason for doing is that, EMG signals are used for many rehabilitation and assistive prostheses of paralyzed or injured people. Methods:Filtering a biological signal is the key point for these type studies. Filtering the EMG signals needed and starts with the elimination of the 50 Hz mains supply noise. After filtering the signal, feature extraction will be applied for both wrist flexion and wrist extension cases. There are many feature extraction methods for time and frequency domain. After feature extraction, classification of hand movements will be studied using extracted features. Classification is made using K Nearest Neighbor algorithm. The dataset used in this study is acquired by the EMG signal acquisition tool and belong to us. Results:90 % accuracy performance is obtained by K Nearest Neighbor algorithm purposed signal classification. Conclusion:This system is capable of conducting the classification process with a good performance to biomedical studies. So,this structure can be helpful as machine-learning based decision support system for medical purpose. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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