Fall risks assessment and fall prediction among community dwelling elderly using wearable wireless sensors

Xuefang Wu; Han Teik Yeoh; Thurmon Lockhart

doi:10.1177/1541931213571026

Fall risks assessment and fall prediction among community dwelling elderly using wearable wireless sensors

Xuefang Wu, Han Teik Yeoh, Thurmon Lockhart

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

This study examines the predictive ability of fall risks among community dwelling elderly using wearable wireless sensors. Forty-eight community-dwelling elderly (17 non-fallers and 31 fallers) participated in the study. Timed up and go test, sit-to-stand test and ten-meter walking test were carried out. Activitiesspecific Balance Confidence (ABC) Scale was also obtained. The results showed fairly good predictive ability of fall risks among older adults, with stance time, walking velocity and timed up and go time being promising of indicating fall risks. Further investigation is warranted to better understand the signals from the wearable sensors and justify the model. Larger sample size is also warranted to validate the model.

Original language	English (US)
Title of host publication	Proceedings of the Human Factors and Ergonomics Society Annual Meeting, HFES 2013
Pages	109-113
Number of pages	5
DOIs	https://doi.org/10.1177/1541931213571026
State	Published - 2013
Externally published	Yes
Event	57th Human Factors and Ergonomics Society Annual Meeting - 2013, HFES 2013 - San Diego, CA, United States Duration: Sep 30 2013 → Oct 4 2013

Publication series

Name	Proceedings of the Human Factors and Ergonomics Society
ISSN (Print)	1071-1813

Other

Other	57th Human Factors and Ergonomics Society Annual Meeting - 2013, HFES 2013
Country/Territory	United States
City	San Diego, CA
Period	9/30/13 → 10/4/13

ASJC Scopus subject areas

Human Factors and Ergonomics

Access to Document

10.1177/1541931213571026

Cite this

Fall risks assessment and fall prediction among community dwelling elderly using wearable wireless sensors. / Wu, Xuefang; Yeoh, Han Teik; Lockhart, Thurmon.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting, HFES 2013. 2013. p. 109-113 (Proceedings of the Human Factors and Ergonomics Society).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wu, X, Yeoh, HT & Lockhart, T 2013, Fall risks assessment and fall prediction among community dwelling elderly using wearable wireless sensors. in Proceedings of the Human Factors and Ergonomics Society Annual Meeting, HFES 2013. Proceedings of the Human Factors and Ergonomics Society, pp. 109-113, 57th Human Factors and Ergonomics Society Annual Meeting - 2013, HFES 2013, San Diego, CA, United States, 9/30/13. https://doi.org/10.1177/1541931213571026

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abstract = "This study examines the predictive ability of fall risks among community dwelling elderly using wearable wireless sensors. Forty-eight community-dwelling elderly (17 non-fallers and 31 fallers) participated in the study. Timed up and go test, sit-to-stand test and ten-meter walking test were carried out. Activitiesspecific Balance Confidence (ABC) Scale was also obtained. The results showed fairly good predictive ability of fall risks among older adults, with stance time, walking velocity and timed up and go time being promising of indicating fall risks. Further investigation is warranted to better understand the signals from the wearable sensors and justify the model. Larger sample size is also warranted to validate the model.",

author = "Xuefang Wu and Yeoh, {Han Teik} and Thurmon Lockhart",

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doi = "10.1177/1541931213571026",

language = "English (US)",

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booktitle = "Proceedings of the Human Factors and Ergonomics Society Annual Meeting, HFES 2013",

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AB - This study examines the predictive ability of fall risks among community dwelling elderly using wearable wireless sensors. Forty-eight community-dwelling elderly (17 non-fallers and 31 fallers) participated in the study. Timed up and go test, sit-to-stand test and ten-meter walking test were carried out. Activitiesspecific Balance Confidence (ABC) Scale was also obtained. The results showed fairly good predictive ability of fall risks among older adults, with stance time, walking velocity and timed up and go time being promising of indicating fall risks. Further investigation is warranted to better understand the signals from the wearable sensors and justify the model. Larger sample size is also warranted to validate the model.

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Fall risks assessment and fall prediction among community dwelling elderly using wearable wireless sensors

Abstract

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