Time-Critical Fall Prediction Based on Lipschitz Data Analysis and Design of a Reconfigurable Walker for Preventing Fall Injuries

Time-Critical Fall Prediction Based on Lipschitz Data Analysis and Design of a Reconfigurable Walker for Preventing Fall Injuries

Falls may cause serious injuries to older adults, leading to a deteriorated quality of life. Currently, there is a lack of fall injury prevention devices, especially for the balance impaired population who rely on mobility aids. Here, the functionality of a walker is augmented, so that it can predic...

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Bibliographic Details
Main Authors: Emily A. Kamienski, Paolo Bonato, H. Harry Asada
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Fall prediction
machine learning
mobility aid
fall injury prevention
Lipschitz analysis
eldercare
Online Access:https://ieeexplore.ieee.org/document/10374122/

Internet

https://ieeexplore.ieee.org/document/10374122/

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