چکیده مقاله
Electromyography signals are used in areas such as artificial limbs, rehabilitation, diagnostic medicine, and wearable and control instruments In this paper, we present a method for classifying the 12 most widely used everyday movements for controlling modern artificial hands and making them smart The sEMG signals were recorded from ten volunteers and classified after the noise removal process using Butterworth Filter 3, classification, and window placement In this study, 24 features extracted in the time frequency domain were used The results show that using the decision tree classifier one channel sEMG signal was classified with 91 4% accuracy In future studies, a combination of other biological signals such as electroencephalography could be used to improve detection and reduce the time of segregation
کلیدواژهها
نویسندگان
Ali Ghanbar
Department of Medical Engineering, Faculty of Medical Sciences and Technologies, Islamic Azad University Research and Sciences Branch,Tehran, Iran
Shiva Kazembeigibarzi
Department of Medical Engineering, Faculty of Medical Sciences and Technologies, Islamic Azad University Research and Sciences Branch,Tehran, Iran
Amirali Alilooie
Department of Medical Engineering, Faculty of Medical Sciences and Technologies, Islamic Azad University Research and Sciences Branch,Tehran, Iran
Sarvin Tohidi
Department of Medical Engineering, Faculty of Medical Sciences and Technologies, Islamic Azad University Research and Sciences Branch,Tehran, Iran
Babak Rezaee Afshar
PhD in Medical Engineering, Department of Orthotics and Prosthetics, Faculty of Rehabilitation Iran University of Medical Science, Tehran, Iran
شیوه ارجاع
Ghanbar, Ali and Kazembeigibarzi, Shiva and Alilooie, Amirali and Tohidi, Sarvin and Rezaee Afshar, Babak,1403,Classification of selected finger movements with single-channel electromyography by decision tree,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده3 اردیبهشت 1403 · بوشهر