A wavelet-based approach to monitoring Parkinson's disease symptoms

Avishai Wagner, Naama Fixler, Yehezkel S. Resheff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Parkinson's disease is a neuro-degenerative disorder affecting tens of millions of people worldwide. Lately, there has been considerable interest in systems for at-home monitoring of patients, using wearable devices which contain inertial measurement units. We present a new wavelet-based approach for analysis of data from single wrist-worn smart-watches, and show high detection performance for tremor, bradykinesia, and dyskinesia, which have been the major targets for monitoring in this context. We also discuss the implication of our controlled-experiment results for uncontrolled home monitoring of freely behaving patients.

Original languageAmerican English
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5980-5984
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - 16 Jun 2017
Externally publishedYes
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume0
ISSN (Print)1520-6149

Conference

Conference2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period5/03/179/03/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Accelerometer
  • Monitoring
  • Parkinson's Disease
  • Wavelets
  • Wearable Devices

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