ARIMA-based motor anomaly detection in schizophrenia inpatients

Talia Tron, Yehezkel S. Resheff, Mikhail Bazhmin, Daphna Weinshall, Abraham Peled

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

9 Scopus citations

Abstract

Motor alteration is an important aspect of the elusive schizophrenia disorder, manifested both throughout the various phases of the disease and as a response to treatment. Tracking of patients' movement, and especially in a closed ward hospital setting, can therefore shed light on the dynamics of the disease, and help alert staff to possible deterioration and adverse effects of medication. In this paper we describe the use of ARIMA-based anomaly detection for monitoring of patient motor activity in a closed ward hospital setting. We demonstrate the utility of the approach in several intriguing case studies.

Original languageAmerican English
Title of host publication2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages430-433
Number of pages4
ISBN (Electronic)9781538624050
DOIs
StatePublished - 6 Apr 2018
Event2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018 - Las Vegas, United States
Duration: 4 Mar 20187 Mar 2018

Publication series

Name2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
Volume2018-January

Conference

Conference2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018
Country/TerritoryUnited States
CityLas Vegas
Period4/03/187/03/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

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