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Pamanasari, Elta Diah
University of Muhammadiyah Malang
Mechanical Engineering

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Parkinson Disease Detection Based on Voice and EMG Pattern Classification Method for Indonesian Case Study Putri, Farika; Caesarendra, Wahyu; Pamanasari, Elta Diah; Ariyanto, Mochammad; Setiawan, Joga D
Journal of Energy, Mechanical, Material and Manufacturing Engineering Vol 3, No 2 (2018)
Publisher : University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (835.552 KB) | DOI: 10.22219/jemmme.v3i2.6977

Abstract

Parkinson disease (PD) detection using pattern recognition method has been presented in literatures. This paper present multi-class PD detection utilizing voice and electromyography (EMG) features of Indonesian subjects. The multi-class classification consists of healthy control, possible stage, probable stage and definite stage. These stages are based on Hughes scale used in Indonesia for PD. Voice signals were recorded from 15 people with Parkinson (PWP) and 8 healthy control subjects. Voice and EMG data acquistion were conducted in dr Kariadi General Hospital Semarang, Central Java, Indonesia. Twenty two features are used for voice signal feature extraction and twelve features are emploed for EMG signal. Artificial Neural Network is used as classification method. The results of voice classification show that accuracy for testing step of 94.4%. For EMG classification, the accuracy of testing of 71%.
Co-Authors Mochammad Ariyanto Putri, Farika Setiawan, Joga D Wahyu Caesarendra