Paper Info
Title
Evaluation Of Daily Walking Activity And Gait Profiles: A Novel Application Of A Time Series Analysis Framework
Abstract
Wearable technology allows an in-depth analysis of gait behaviour in free-living environments. This investigation aimed to use Alzheimer's disease as an example to apply the time series analysis technique of Statistical Parametric Mapping (SPM) to create daily gait profiles and test if they differed from cognitively intact controls. A framework of macro (habitual walking behaviours) and micro characteristics (spatiotemporal gait variables) characteristics were calculated on an hourly basis. SPM showed that select micro gait characteristics differed from controls at specific hours of the day. Therefore, the application of SPM may provide a more in-depth reflection of activity and gait time-dependent fluctuations than commonly used whole day values. Considering macro and micro gait hour-by-hour may have applications towards disease management, personalized care, monitoring medication and targeted interventions for people with a range of neurodegenerative diseases.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857250
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Time series,Gait,Computer science,Statistical parametric mapping,Artificial intelligence,Physical medicine and rehabilitation,Macro,Wearable technology,Walking (activity),Disease management
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Christopher Buckley100.34
Ríona Mc Ardle200.34
Brook Galna3121.34
Alan Thomas400.34
Lynn Rochester5638.24
Silvia Del Din6133.05