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An Expert System for Quantification of Bradykinesia Based on Wearable Inertial Sensors

1
University of Belgrade-School of Electrical Engineering, 11000 Belgrade, Serbia
2
Innovation Center, School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia
3
Clinic of Neurology, School of Medicine, University of Belgrade, 11000 Belgrade, Serbia
4
Institute for Medical Research, University of Belgrade, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(11), 2644; https://doi.org/10.3390/s19112644
Received: 3 April 2019 / Revised: 15 May 2019 / Accepted: 4 June 2019 / Published: 11 June 2019
(This article belongs to the Special Issue Wearable Sensors and Devices for Healthcare Applications)
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Abstract

Wearable sensors and advanced algorithms can provide significant decision support for clinical practice. Currently, the motor symptoms of patients with neurological disorders are often visually observed and evaluated, which may result in rough and subjective quantification. Using small inertial wearable sensors, fine repetitive and clinically important movements can be captured and objectively evaluated. In this paper, a new methodology is designed for objective evaluation and automatic scoring of bradykinesia in repetitive finger-tapping movements for patients with idiopathic Parkinson’s disease and atypical parkinsonism. The methodology comprises several simple and repeatable signal-processing techniques that are applied for the extraction of important movement features. The decision support system consists of simple rules designed to match universally defined criteria that are evaluated in clinical practice. The accuracy of the system is calculated based on the reference scores provided by two neurologists. The proposed expert system achieved an accuracy of 88.16% for files on which neurologists agreed with their scores. The introduced system is simple, repeatable, easy to implement, and can provide good assistance in clinical practice, providing a detailed analysis of finger-tapping performance and decision support for symptom evaluation. View Full-Text
Keywords: decision support system; wearable inertial sensors; finger-tapping; automatic scoring; Parkinson’s disease; atypical parkinsonism; UPDRS decision support system; wearable inertial sensors; finger-tapping; automatic scoring; Parkinson’s disease; atypical parkinsonism; UPDRS
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Bobić, V.; Djurić-Jovičić, M.; Dragašević, N.; Popović, M.B.; Kostić, V.S.; Kvaščev, G. An Expert System for Quantification of Bradykinesia Based on Wearable Inertial Sensors. Sensors 2019, 19, 2644.

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