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Fridastya Andini Pamudyaningrum
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Electrical & Electronics Engineering

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Implementation of Myo Armband on Mobile Application for Post-stroke Patient Hand Rehabilitation Tri Bintang Dewantoro; Riyanto Sigit; Heny Yuniarti; Yudith Dian Prawitri; Fridastya Andini Pamudyaningrum; Mahaputra Ilham Awal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (720.059 KB) | DOI: 10.11591/eecsi.v5.1585

Abstract

Medical rehabilitation is one of the efforts to restore motor function of post-stroke patients, but the biggest factor that makes patients quickly restore motor function by active patient movement exercises. The movement in question is the movement carried out every day outside medical rehabilitation at the hospital. On the other hand, patients are reluctant to do therapy independently outside the hospital, because there is no tool that supports patients to do so. So, we need a device that helps patients to do therapy independently. The device is connected to Myo Armband to read the gestures of the patient by looking at the EMG signal from the patient's hand. Then the system performs matching gestures during therapy with EMG signal data that has been trained. The motion matching is done by calculating the Euclidean distance between the two EMG signal data obtained from the Myo Armband device. From the results of the tests carried out, the accuracy of movement matching results obtained an average accuracy of 89.67 percent for flexion-extension gestures and 82 percent for pronation-supination gestures. It can be concluded that Myo Armband in the Mobile Application can be used for Rehabilitation of post stroke patient hands.
Co-Authors Heny Yuniarti Mahaputra Ilham Awal Prawitri, Yudith Dian Riyanto Sigit Tri Bintang Dewantoro