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Time series clustering to examine presence of decrement in Parkinson’s finger-tapping bradykinesia

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conference contribution
posted on 01.05.2020, 12:54 authored by Zhibin Zhao, Hui FangHui Fang, Stefan Williams, Samuel Relton, Jane Alty, David Wong
— Parkinson’s disease is diagnosed based on expert clinical observation of movements. One important clinical feature is decrement, whereby the range of finger motion decreases over the course of the observation. This decrement has been assumed to be linear but has not been examined closely. We previously developed a method to extract a time series representation of a finger-tapping clinical test from 137 smartphone video recordings. Here, we show how the signal can be processed to visualize archetypal progression of decrement. We use k-means with features derived from dynamic time warping to compare similarity of time series. To generate the archetypal time series corresponding to each cluster, we apply both a simple arithmetic mean, and dynamic time warping barycenter averaging to the time series belonging to each cluster. Visual inspection of the cluster-average time series showed two main trends. These corresponded well with participants with no bradykinesia and participants with severe bradykinesia. The visualizations support the concept that decrement tends to present as a linear decrease in range of motion over time. Clinical relevance— Our work visually presents the archetypal types of bradykinesia amplitude decrement, as seen in the Parkinson’s finger-tapping test. We found two main patterns, one corresponding to no bradykinesia, and the other showing linear decrement over time.

History

School

  • Science

Department

  • Computer Science

Published in

2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Pages

780 - 783

Source

42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society

Publisher

IEEE

Version

AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

05/04/2020

Publication date

2020-08-27

Copyright date

2020

ISBN

9781728119908

eISSN

1558-4615

Language

en

Location

Montreal, Canada

Event dates

20th July 2020 - 24th July 2020

Depositor

Dr Hui Fang Deposit date: 29 April 2020

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