Identifying the Condition of Arm through Classification of EMG Signals by the Use of Hybrid Trained Adaptive Neural Fuzzy Inference Systems (ANFIS)

سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 553

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شناسه ملی سند علمی:

NEEREC08_081

تاریخ نمایه سازی: 28 اسفند 1394

چکیده مقاله:

The received electrical signals from electromyography (EMG) can be applied to diagnose neural-muscular diseases, to control robot arms, and also to identify movements and direct artificial limbs. In this study, we dealt with increasing the accuracy of classifying electromyography signal patterns for segregating different movements with appropriate accuracy by the use of Adaptive Neural Fuzzy Inference Systems (ANFIS). The achieved results from conducting the suggested approach show that the error rate of ANFIS is considerably lower than that of ANN and by the use of ANFIS, up to 89% accurate classifying has been performed.

نویسندگان

Faezeh Rajablou

Department of Electrical Engineering,Department Ali Abad Branch, Islamic Azad University, Ali Abad Branch, Iran.

Mahmood Ghandari

Department of Electrical Engineering,Department Ali Abad Branch, Islamic Azad University, Ali Abad Branch, Iran