U-healthcare system for pre-diagnosis of Parkinson's disease from voice signal
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With the ageing and growth of the population, some chronic diseases, such as Parkinson's disease (PD), urge the society to a health-conscious looking for better health system designs. Some recent research endeavour has been supported by solutions grounded in ubiquitous healthcare (u-Health) coupling telemedicine, context awareness and decision support capabilities. In this work, we propose a u-healthcare system to pre-diagnose PD based on the speech signal of people under voice call. The speech stream is sampled as well as processed to support the pre-diagnose using machine learning (ML). Experiments were conducted over a PD voice dataset composed of 40 individuals by using five different ML algorithms. Based on a linear Support Vector Machine (SVM) model, a false negative rate of 10% was obtained when classifying the locution of number “three”.
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Health, Machine Learning, Signal Processing, Speech, Ubiquitous Computing
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Inglês
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Proceedings - 2018 IEEE International Symposium on Multimedia, ISM 2018, p. 271-274.
