research-article

Portable, non-invasive fall risk assessment in end stage renal disease patients on hemodialysis

Authors:

Thurmon E. Lockhart,

Emaad Abdel-Rahman,

John LachAuthors Info & Claims

WH '10: Wireless Health 2010

Pages 84 - 93

https://doi.org/10.1145/1921081.1921092

Published: 05 October 2010 Publication History

Abstract

Patients with end stage renal diseases (ESRD) on hemodialysis (HD) have high morbidity and mortality due to multiple causes, one of which is dramatically higher fall rates than the general population. The mobility mechanisms that contribute to falls in this population must be understood if adequate interventions for fall prevention are to be achieved. This study utilizes emerging non-invasive, portable gait, posture, strength, and stability assessment technologies to extract various mobility parameters that research has shown to be predictive of fall risk in the general population. As part of an ongoing human subjects study, mobility measures such as postural and locomotion profiles were obtained from five (5) ESRD patients undergoing HD treatments. To assess the effects of post-HD-fatigue on fall risk, both the pre- and post-HD measurements were obtained. Additionally, the effects of inter-HD periods (two days vs. three days) were investigated using the non-invasive, wireless, body-worn motion capture technology and novel signal processing algorithms. The results indicated that HD treatment influenced strength and mobility (i.e., weaker and slower after the dialysis, increasing the susceptibility to falls while returning home) and inter-dialysis period influenced pre-HD profiles (increasing the susceptibility to falls before they come in for a HD treatment). Methodology for early detection of increased fall risk -- before a fall event occurs -- using the portable mobility assessment technology for out-patient monitoring is further explored, including targeting interventions to identified individuals for fall prevention.

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Soangra RLockhart T(2021)Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture MeasuresSensors10.3390/s2105170421:5(1704)Online publication date: 2-Mar-2021
https://doi.org/10.3390/s21051704
Mehmood ANadeem AAshraf MSiddiqui MRizwan KAhsan K(2021)A Fall Risk Assessment Mechanism for Elderly People Through Muscle Fatigue Analysis on Data From Body Area Sensor NetworkIEEE Sensors Journal10.1109/JSEN.2020.304328521:5(6679-6690)Online publication date: 1-Mar-2021
https://doi.org/10.1109/JSEN.2020.3043285
Dang QChen SRanasinghe DFumeaux C(2020)Modular Integration of a Passive RFID Sensor With Wearable Textile Antennas for Patient MonitoringIEEE Transactions on Components, Packaging and Manufacturing Technology10.1109/TCPMT.2020.303604510:12(1979-1988)Online publication date: Dec-2020
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Index Terms

Portable, non-invasive fall risk assessment in end stage renal disease patients on hemodialysis
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health informatics

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Information & Contributors

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Published In

cover image ACM Other conferences

WH '10: Wireless Health 2010

October 2010

232 pages

ISBN:9781605589893

DOI:10.1145/1921081

General Chairs:
Irwin Mark Jacobs
Qualcomm Incorporated
,
Patrick Soon-Shiong
UCLA Wireless Health Institute
,
Eric Topol
West Wireless Institute
,
Chris Toumazou
Institute of Biomedical Engineering, Imperial College London

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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WLSA: Wireless-Life Sciences Alliance
University of California, Los Angeles

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 05 October 2010

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WH '10: Wireless Health 2010

October 5 - 7, 2010

California, San Diego

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Cited By

Soangra RLockhart T(2021)Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture MeasuresSensors10.3390/s2105170421:5(1704)Online publication date: 2-Mar-2021
https://doi.org/10.3390/s21051704
Mehmood ANadeem AAshraf MSiddiqui MRizwan KAhsan K(2021)A Fall Risk Assessment Mechanism for Elderly People Through Muscle Fatigue Analysis on Data From Body Area Sensor NetworkIEEE Sensors Journal10.1109/JSEN.2020.304328521:5(6679-6690)Online publication date: 1-Mar-2021
https://doi.org/10.1109/JSEN.2020.3043285
Dang QChen SRanasinghe DFumeaux C(2020)Modular Integration of a Passive RFID Sensor With Wearable Textile Antennas for Patient MonitoringIEEE Transactions on Components, Packaging and Manufacturing Technology10.1109/TCPMT.2020.303604510:12(1979-1988)Online publication date: Dec-2020
https://doi.org/10.1109/TCPMT.2020.3036045
Zemp DGiannini OQuadri Pde Bruin E(2019)Gait characteristics of CKD patients: a systematic reviewBMC Nephrology10.1186/s12882-019-1270-920:1Online publication date: 6-Mar-2019
https://doi.org/10.1186/s12882-019-1270-9
Zhou HAl-Ali FRahemi HKulkarni NHamad AIbrahim RTalal TNajafi B(2018)Hemodialysis Impact on Motor Function beyond Aging and Diabetes—Objectively Assessing Gait and Balance by Wearable TechnologySensors10.3390/s1811393918:11(3939)Online publication date: 14-Nov-2018
https://doi.org/10.3390/s18113939
Soangra RLockhart T(2018)Inertial Sensor-Based Variables Are Indicators of Frailty and Adverse Post-Operative Outcomes in Cardiovascular Disease PatientsSensors10.3390/s1806179218:6(1792)Online publication date: 2-Jun-2018
https://doi.org/10.3390/s18061792
Gui XChen YKou YPine KChen Y(2017)Investigating Support Seeking from Peers for Pregnancy in Online Health CommunitiesProceedings of the ACM on Human-Computer Interaction10.1145/31346851:CSCW(1-19)Online publication date: 6-Dec-2017
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Erken EOzelsancak RSahin SYılmaz ETorun DLeblebici BKuyucu YSezer S(2016)The effect of hemodialysis on balance measurements and risk of fallInternational Urology and Nephrology10.1007/s11255-016-1388-748:10(1705-1711)Online publication date: 6-Aug-2016
https://doi.org/10.1007/s11255-016-1388-7
Calhoun BLach JStankovic JWentzloff DWhitehouse KBarth ABrown JLi QOh SRoberts NZhang Y(2012)Body Sensor Networks: A Holistic Approach From Silicon to UsersProceedings of the IEEE10.1109/JPROC.2011.2161240100:1(91-106)Online publication date: Jan-2012
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Soangra RLockhart TLach JAbdel-Rahman E(2012)Effects of Hemodialysis Therapy on Sit-to-Walk Characteristics in End Stage Renal Disease PatientsAnnals of Biomedical Engineering10.1007/s10439-012-0701-641:4(795-805)Online publication date: 5-Dec-2012
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