Egocentric vision-based detection of surfaces: towards context-aware free-living digital biomarkers for gait and fall risk assessment

Egocentric vision-based detection of surfaces: towards context-aware free-living digital biomarkers for gait and fall risk assessment

Abstract Background Falls in older adults are a critical public health problem. As a means to assess fall risks, free-living digital biomarkers (FLDBs), including spatiotemporal gait measures, drawn from wearable inertial measurement unit (IMU) data have been investigated to identify those at high r...

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Bibliographic Details
Main Authors: Mina Nouredanesh, Alan Godfrey, Dylan Powell, James Tung
Format: Article
Language:English
Published: BMC 2022-07-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
Free-living digital biomarkers
Egocentric vision
Free-living gait analysis
Wearable sensors
Terrain type identification
Deep convolutional neural networks
Online Access:https://doi.org/10.1186/s12984-022-01022-6

Internet

https://doi.org/10.1186/s12984-022-01022-6

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