Paper Info
Title
Feasibility of Using Dynamic Time Warping to Measure Motor States in Parkinson's Disease.
Abstract
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.
Year
DOI
Venue
2020
10.1155/2020/3265795
JOURNAL OF SENSORS
Field
DocType
Volume
Computer vision,Parkinson's disease,Gyroscope,Dynamic time warping,Treatment response,Distance score,Artificial intelligence,Motion sensors,Engineering,Physical medicine and rehabilitation
Journal
2020
ISSN
Citations 
PageRank 
1687-725X
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Somayeh Aghanavesi142.22
Hasan Fleyeh200.34
Mark Dougherty300.68