Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease

The aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson’s disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and mu...

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Main Authors: Somayeh Aghanavesi, Hasan Fleyeh, Mark Dougherty
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Journal of Sensors
Online Access:http://dx.doi.org/10.1155/2020/3265795
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spelling doaj-4da5ce3d3686427fa89391ec339afcfa2020-11-25T02:06:19ZengHindawi LimitedJournal of Sensors1687-725X1687-72682020-01-01202010.1155/2020/32657953265795Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s DiseaseSomayeh Aghanavesi0Hasan Fleyeh1Mark Dougherty2School of Technology and Business Studies, Dalarna University, Falun 78188, SwedenSchool of Technology and Business Studies, Dalarna University, Falun 78188, SwedenSchool of Information Technology, Halmstad University, Halmstad 30250, SwedenThe aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson’s disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and multiple times after an administration of 150% of their normal daily dose of medication. Experiments of 22 healthy controls were included. Three movement disorder specialists rated the motor states of the patients according to Treatment Response Scale (TRS) using recorded videos of the experiments. A DTW-based motor state distance score (DDS) was constructed using the acceleration and gyroscope signals collected during leg agility motor tests. Mean DDS showed similar trends to mean TRS scores across the test occasions. Mean DDS was able to differentiate between PD patients at Off and On motor states. DDS was able to classify the motor state changes with good accuracy (82%). The PD patients who showed more response to medication were selected using the TRS scale, and the most related DTW-based features to their TRS scores were investigated. There were individual DTW-based features identified for each patient. In conclusion, the DTW method can provide information about motor states of advanced PD patients which can be used in the development of methods for automatic motor scoring of PD.http://dx.doi.org/10.1155/2020/3265795
collection DOAJ
language English
format Article
sources DOAJ
author Somayeh Aghanavesi
Hasan Fleyeh
Mark Dougherty
spellingShingle Somayeh Aghanavesi
Hasan Fleyeh
Mark Dougherty
Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
Journal of Sensors
author_facet Somayeh Aghanavesi
Hasan Fleyeh
Mark Dougherty
author_sort Somayeh Aghanavesi
title Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
title_short Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
title_full Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
title_fullStr Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
title_full_unstemmed Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson’s Disease
title_sort feasibility of using dynamic time warping to measure motor states in parkinson’s disease
publisher Hindawi Limited
series Journal of Sensors
issn 1687-725X
1687-7268
publishDate 2020-01-01
description The aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson’s disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and multiple times after an administration of 150% of their normal daily dose of medication. Experiments of 22 healthy controls were included. Three movement disorder specialists rated the motor states of the patients according to Treatment Response Scale (TRS) using recorded videos of the experiments. A DTW-based motor state distance score (DDS) was constructed using the acceleration and gyroscope signals collected during leg agility motor tests. Mean DDS showed similar trends to mean TRS scores across the test occasions. Mean DDS was able to differentiate between PD patients at Off and On motor states. DDS was able to classify the motor state changes with good accuracy (82%). The PD patients who showed more response to medication were selected using the TRS scale, and the most related DTW-based features to their TRS scores were investigated. There were individual DTW-based features identified for each patient. In conclusion, the DTW method can provide information about motor states of advanced PD patients which can be used in the development of methods for automatic motor scoring of PD.
url http://dx.doi.org/10.1155/2020/3265795
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