Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item A Comparison of Different Signal Processing Techniques for Upper Limb Muscle Activity Onset Detection using Surface Electromyography(Institute of Electrical and Electronics Engineers Inc., 2023) Koppolu, P.K.; Chemmangat, K.This work presents the use of real-time experimental Surface Electromyography (sEMG) signals to determine muscle activity of upper limb by detecting the exact onset and offset timings. Various muscle activity detection methods were evaluated, such as Sample Entropy (SEn), Permutation Entropy (PEn), Amplitude Aware Permutation Entropy (AAPEn), and Integrated Profile (IP). The performance of these methods was compared, and it was found that IP detects muscle activity quickly and requires less computation for real-time implementation as compared to other methods. © 2023 IEEE.Item Classification of Hand Gestures with Real Time Muscle Activity Detection for Myoelectric Control of Upper Limb Prosthesis(Institute of Electrical and Electronics Engineers Inc., 2023) Koppolu, P.K.; Chemmangat, K.This paper presents the classification of basic hand movements with the determination of onset and offset timings of muscle activity in real time using surface Electromyography (sEMG). Integration Profile (IP) method is evaluated to detect muscle activity in real time. Dynamic Time Warping (DTW) is used to classify hand movements using detected muscle activity signals. The sEMG data collection, muscle activity detection and classification of different muscle activities are performed in the National Instrument (NI) LabView environment. The movement classification results suggest that the proposed procedure accurately demonstrates the importance of muscle activity detection in the classification. © 2023 IEEE.