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All Journal Majalah Ilmiah Teknologi Elektro Majalah Ilmiah Teknologi Elektro
I Made Esa Darmayasa Adi Putra
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Majalah Ilmiah Teknologi Elektro

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Evaluasi Model Machine Learning Klasifikasi Gerak Tangan Untuk Sistem Kontrol Prototipe Prostesis Tangan I Made Esa Darmayasa Adi Putra; Ilham Fauzi; Karuna Sindhu Krishna Prasad; I Made Putra Arya Winata; I Wayan Widhiada
Majalah Ilmiah Teknologi Elektro Vol 22 No 1 (2023): (Januari - Juni) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2023.v22i01.P18

Abstract

Obstacles in the form of loss of function of body parts will cause difficulty in carrying out normal activities. In the application of electromyography (EMG) and electroencephalography (EEG) sensors that are not good at compensating for various kinds of human physical conditions, force sensing resistor (FSR) sensors can be an alternative to EMG and EEG in hand prostheses. In planning the neural network model, the data needed for the actual output is only in the form of hand gestures for post-amputation non-patients. Long Short Term Memory (LSTM) is used because it can handle data processing in the long run which is one of the conditions that arise in sequential data processing. The resulting evaluation metrics are in the form of accuracy values in training data with epoch 200 and accuracy in data testing. The first result with no dropout variation shows the accuracy value in training is 0,9449 and the accuracy in testing is 0,961 with the loss value in training is 0,1284 and the loss in testing is 0,0717. The second result with dropout variations shows the accuracy value in training is 0,9699 and accuracy in testing is 0,9688 with a loss value in training is 0,0803 and loss in testing is 0,1061. the metrics accuracy evaluation generated on the dataset has exceeded the value of 0,9. This indicates that the model has run well for the classification of 11 movements. Keyword — Control System; machine learning; moving arm; prostesis arm.
Co-Authors I Made Putra Arya Winata I Wayan Widhiada Ilham Fauzi Karuna Sindhu Krishna Prasad