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DOI: 10.14569/IJACSA.2019.0100719
PDF

A Mobile-based Tremor Detector Application for Patients with Parkinson’s Disease

Author 1: Pang Xin Yi
Author 2: Maryati Mohd. Yusof
Author 3: Kalaivani Chelappan

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 7, 2019.

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Abstract: Parkinson’s disease affects millions of people worldwide and its frequency is steadily increasing. No cure is currently available for Parkinson’s disease patients, and most medications only treat the symptoms. This treatment depends on the quantification of Parkinson’s symptoms, such as hand tremors. The most commonly used method to measure human tremors is a severity scale, which lacks accuracy because it is based on the subjectivity of neurologist review. Furthermore, the use of severity scales prevents the extraction of information from tremor activity, such as speed, amplitude, and frequency. Therefore, a mobile application was developed to measure the hand tremor level of Parkinson’s patients using a mobile phone-based accelerometer. Agile method was used to develop this application, and Android Studio and Android Software Development Kit were utilized. The application runs on an Android smartphone. This application allows patients to identify their tremor activity and subsequently seek relevant medical advice. In addition, a neurologist can monitor tremor activity of patients by analyzing the records generated from this application.

Keywords: Agile; mhealth; mobile application; Parkinson; tremor detector

Pang Xin Yi, Maryati Mohd. Yusof and Kalaivani Chelappan, “A Mobile-based Tremor Detector Application for Patients with Parkinson’s Disease” International Journal of Advanced Computer Science and Applications(IJACSA), 10(7), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100719

@article{Yi2019,
title = {A Mobile-based Tremor Detector Application for Patients with Parkinson’s Disease},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100719},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100719},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {7},
author = {Pang Xin Yi and Maryati Mohd. Yusof and Kalaivani Chelappan}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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