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EMG Signals Classification of Wide Range Motion Signals for Prosthetic Hand Control
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The recent revolution in the biomedical field carried out the researchers to work on the prosthetic technique
because it reflects the amputee's need. Therefore, the electromyography (EMG) signals generated by muscle
contractions are used to implement the prosthetic human body parts. This paper presents a pattern recognition system
based on two EMG data; the first EMG data represents the general body movements collected from biceps and triceps
muscles for six different motions, i.e., bowing, clapping, handshaking, hugging, jumping, and running. The Root Mean
Square, Difference Absolute Standard Deviation Value, and Principal Component Analysis extract the raw signal data
features and enhance classification accuracy. The machine learning method is applied, i.e., Support Vector Machine
(SVM) and K-Nearest Neighbours (KNN) are used for data classification; the results show high accuracy reached
94.8% and 98.9%, respectively. Whereas, the second EMG data is selected to be more specific in hand movements,
i.e., cylindrical, spherical, palmar, lateral, hook, and tip motions, because these significant motions are the first step
implementing any prosthetic hand. Consequently, the mean, Standard Deviation Value, and Principal Component
Analysis extract the raw signal feature. Meanwhile, the same algorithm used in the first data classification is also used
to classify the second data because it shows high accuracy and good performance. SVM algorithm is used to classify
the data and achieved high training accuracy, reaching 89%. The high training accuracy for different hand movements
is considered an essential step toward implementing human prosthetic parts to help the people who suffer from an
amputee.
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Citrus aurantium L.PEELS AND SEEDS : PHYTOCHEMICAL SCREENING AND ANTIBA CTERIAL ACTIVITY
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أ.م.د. قتيبة ابراهيم خضر الزند2024
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An overview of neuro-ophthalmic disorders at Jenna Ophthalmic Center, Baghdad, Iraq (2021-2022)
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م.د ليث غضنفر شريف جمعة2024
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Emerging Innovations In vincristine-encapsulated nanoparticles :pioneering a new era in oncological therapeutics
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ا.م.د. اسراء غازي جبار اللعيبي الماذي2024
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ا.م.د. اسراء غازي جبار اللعيبي الماذي2024
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Comparative Study for Citrus Fruits Peel Extract , Phytochemical Screening and In-vitro Antioxidant Activity
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أ. م. د. ايهاب ابراهيم عبد الوهاب سليمان الخليفة2023