Continuous parkinsonian tremor estimation using motion data

Murtadha D. Hssayeni, Joohi Jimenez-Shahed, Michelle A. Burack, Behnaz Ghoraani

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

Abstract

Tremor is one of the main symptoms of Parkinson's Disease (PD) that reduces the quality of life of affected patients. Tremor is measured as part of the Unified Parkinson Disease Rating Scale (UPDRS) part III. However, the assessment is based on onsite physical examinations and do not necessarily represent the patients' tremor experience in their day-to-day life. In this work, we developed two methods based on deep long short-term memory (LSTM) networks and gradient tree boosting to estimate Parkinsonian tremor using gyroscope sensor signals collected as the patients performed a variety of free body movements. The developed methods were assessed on data from 24 PD subjects. Subject-based, leave-one-out cross-validation demonstrated that the method based on gradient tree boosting provided a high correlation (r=0.93 (p<0.0001) between the estimated and clinically-assessed tremor subscores in comparison to the LSTM-based method with (r=0.77 (p<0.0001).

Original languageEnglish
Title of host publicationGlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728127231
DOIs
StatePublished - Nov 2019
Event7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada
Duration: 11 Nov 201914 Nov 2019

Publication series

NameGlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings

Conference

Conference7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019
Country/TerritoryCanada
CityOttawa
Period11/11/1914/11/19

Fingerprint

Dive into the research topics of 'Continuous parkinsonian tremor estimation using motion data'. Together they form a unique fingerprint.

Cite this