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Title: A Smartphone-Based Tool for Assessing Parkinsonian Hand Tremor
Authors: Kostikis, N
Hristu-Varsakelis, Dimitrios
Arnaoutoglou, M
Kotsavasiloglou, C
Type: Article
Subjects: FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Subjects MESH: Accelerometry
Aged, 80 and over
Cluster Analysis
Machine Learning
Middle Aged
Monitoring, Physiologic
Parkinson Disease
Mobile Applications
Issue Date: Nov-2015
Source: IEEE journal of biomedical and health informatics
Volume: 19
Issue: 6
First Page: 1835
Last Page: 1842
Abstract: The aim of this study is to propose a practical smartphone-based tool to accurately assess upper limb tremor in Parkinson's disease (PD) patients. The tool uses signals from the phone's accelerometer and gyroscope (as the phone is held or mounted on a subject's hand) to compute a set of metrics which can be used to quantify a patient's tremor symptoms. In a small-scale clinical study with 25 PD patients and 20 age-matched healthy volunteers, we combined our metrics with machine learning techniques to correctly classify 82% of the patients and 90% of the healthy volunteers, which is high compared to similar studies. The proposed method could be effective in assisting physicians in the clinic, or to remotely evaluate the patient's condition and communicate the results to the physician. Our tool is low cost, platform independent, noninvasive, and requires no expertise to use. It is also well matched to the standard clinical examination for PD and can keep the patient "connected" to his physician on a daily basis. Finally, it can facilitate the creation of anonymous profiles for PD patients, aiding further research on the effectiveness of medication or other overlooked aspects of patients' lives.
ISSN: 2168-2194
Electronic ISSN: 2168-2208
Other Identifiers: 10.1109/JBHI.2015.2471093
Appears in Collections:Department of Applied Informatics

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