Literature DB >> 24406708

Fall detection devices and their use with older adults: a systematic review.

Shomir Chaudhuri1, Hilaire Thompson, George Demiris.   

Abstract

BACKGROUND: Falls represent a significant threat to the health and independence of adults aged 65 years and older. As a wide variety and large number of passive monitoring systems are currently and increasingly available to detect when individuals have fallen, there is a need to analyze and synthesize the evidence regarding their ability to accurately detect falls to determine which systems are most effective.
OBJECTIVES: The purpose of this literature review is to systematically assess the current state of design and implementation of fall-detection devices. This review also examines to what extent these devices have been tested in the real world as well as the acceptability of these devices to older adults. DATA SOURCES: A systematic literature review was conducted in PubMed, CINAHL, EMBASE, and PsycINFO from their respective inception dates to June 25, 2013. STUDY ELIGIBILITY CRITERIA AND
INTERVENTIONS: Articles were included if they discussed a project or multiple projects involving a system with the purpose of detecting a fall in adults. It was not a requirement for inclusion in this review that the system targets persons older than 65 years. Articles were excluded if they were not written in English or if they looked at fall risk, fall detection in children, fall prevention, or a personal emergency response device. STUDY APPRAISAL AND SYNTHESIS
METHODS: Studies were initially divided into those using sensitivity, specificity, or accuracy in their evaluation methods and those using other methods to evaluate their devices. Studies were further classified into wearable devices and nonwearable devices. Studies were appraised for inclusion of older adults in sample and if evaluation included real-world settings.
RESULTS: This review identified 57 projects that used wearable systems and 35 projects using nonwearable systems, regardless of evaluation technique. Nonwearable systems included cameras, motion sensors, microphones, and floor sensors. Of the projects examining wearable systems, only 7.1% reported monitoring older adults in a real-world setting. There were no studies of nonwearable devices that used older adults as subjects in either a laboratory or a real-world setting. In general, older adults appear to be interested in using such devices although they express concerns over privacy and understanding exactly what the device is doing at specific times. LIMITATIONS: This systematic review was limited to articles written in English and did not include gray literature. Manual paper screening and review processes may have been subject to interpretive bias. CONCLUSIONS AND IMPLICATIONS OF KEY
FINDINGS: There exists a large body of work describing various fall-detection devices. The challenge in this area is to create highly accurate unobtrusive devices. From this review it appears that the technology is becoming more able to accomplish such a task. There is a need now for more real-world tests as well as standardization of the evaluation of these devices.

Entities:  

Mesh:

Year:  2014        PMID: 24406708      PMCID: PMC4087103          DOI: 10.1519/JPT.0b013e3182abe779

Source DB:  PubMed          Journal:  J Geriatr Phys Ther        ISSN: 1539-8412            Impact factor:   3.381


  110 in total

Review 1.  Clinical practice. Preventing falls in elderly persons.

Authors:  Mary E Tinetti
Journal:  N Engl J Med       Date:  2003-01-02       Impact factor: 91.245

2.  A microphone array system for automatic fall detection.

Authors:  Yun Li; K C Ho; Mihail Popescu
Journal:  IEEE Trans Biomed Eng       Date:  2012-05       Impact factor: 4.538

3.  Smart Carpet: Developing a sensor system to detect falls and summon assistance.

Authors:  Myra A Aud; Carmen C Abbott; Harry W Tyrer; Rohan Vasantha Neelgund; Uday G Shriniwar; Ashrafuddin Mohammed; Krishna Kishor Devarakonda
Journal:  J Gerontol Nurs       Date:  2010-07-08       Impact factor: 1.254

4.  Assessment of waist-worn tri-axial accelerometer based fall-detection algorithms using continuous unsupervised activities.

Authors:  Alan K Bourke; Pepijn van de Ven; Mary Gamble; Raymond O'Connor; Kieran Murphy; Elizabeth Bogan; Eamonn McQuade; Paul Finucane; Gearoid Olaighin; John Nelson
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

5.  Development of novel algorithm and real-time monitoring ambulatory system using Bluetooth module for fall detection in the elderly.

Authors:  J Y Hwang; J M Kang; Y W Jang; H Kim
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2004

6.  Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm.

Authors:  A K Bourke; J V O'Brien; G M Lyons
Journal:  Gait Posture       Date:  2006-11-13       Impact factor: 2.840

7.  Software simulation of unobtrusive falls detection at night-time using passive infrared and pressure mat sensors.

Authors:  Arni Ariani; Stephen J Redmond; David Chang; Nigel H Lovell
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

8.  iFall: an Android application for fall monitoring and response.

Authors:  Frank Sposaro; Gary Tyson
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

9.  Randomised controlled trial of a general practice programme of home based exercise to prevent falls in elderly women.

Authors:  A J Campbell; M C Robertson; M M Gardner; R N Norton; M W Tilyard; D M Buchner
Journal:  BMJ       Date:  1997-10-25

10.  Wireless fall sensor with GPS location for monitoring the elderly.

Authors:  Eric Campo; Etienne Grangereau
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008
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  31 in total

Review 1.  Using Information Technology in the Assessment and Monitoring of Geriatric Oncology Patients.

Authors:  Kah Poh Loh; Colin McHugh; Supriya G Mohile; Karen Mustian; Marie Flannery; Heidi Klepin; Rebecca Schnall; Eva Culakova; Erika Ramsdale
Journal:  Curr Oncol Rep       Date:  2018-03-06       Impact factor: 5.075

Review 2.  Predicting geriatric falls following an episode of emergency department care: a systematic review.

Authors:  Christopher R Carpenter; Michael S Avidan; Tanya Wildes; Susan Stark; Susan A Fowler; Alexander X Lo
Journal:  Acad Emerg Med       Date:  2014-10-07       Impact factor: 3.451

3.  Older Adults' Perceptions of Fall Detection Devices.

Authors:  Shomir Chaudhuri; Laura Kneale; Thai Le; Elizabeth Phelan; Dori Rosenberg; Hilaire Thompson; George Demiris
Journal:  J Appl Gerontol       Date:  2015-06-24

4.  Older Adults' Experience with a Novel Fall Detection Device.

Authors:  George Demiris; Shomir Chaudhuri; Hilaire J Thompson
Journal:  Telemed J E Health       Date:  2016-03-09       Impact factor: 3.536

5.  Care Transition Decisions After a Fall-related Emergency Department Visit: A Qualitative Study of Patients' and Caregivers' Experiences.

Authors:  Cameron J Gettel; Kelsey Hayes; Renee R Shield; Kate M Guthrie; Elizabeth M Goldberg
Journal:  Acad Emerg Med       Date:  2020-03-15       Impact factor: 3.451

6.  Using Smart City Technology to Make Healthcare Smarter.

Authors:  Diane J Cook; Glen Duncan; Gina Sprint; Roschelle Fritz
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2018-01-23       Impact factor: 10.961

7.  A wavelet-based approach to fall detection.

Authors:  Luca Palmerini; Fabio Bagalà; Andrea Zanetti; Jochen Klenk; Clemens Becker; Angelo Cappello
Journal:  Sensors (Basel)       Date:  2015-05-20       Impact factor: 3.576

Review 8.  Involvement of older people in the development of fall detection systems: a scoping review.

Authors:  Friederike J S Thilo; Barbara Hürlimann; Sabine Hahn; Selina Bilger; Jos M G A Schols; Ruud J G Halfens
Journal:  BMC Geriatr       Date:  2016-02-11       Impact factor: 3.921

9.  Involvement of the end user: exploration of older people's needs and preferences for a wearable fall detection device - a qualitative descriptive study.

Authors:  Friederike Js Thilo; Selina Bilger; Ruud Jg Halfens; Jos Mga Schols; Sabine Hahn
Journal:  Patient Prefer Adherence       Date:  2016-12-20       Impact factor: 2.711

10.  Stratification of risk for hospital admissions for injury related to fall: cohort study.

Authors:  Victor M Castro; Thomas H McCoy; Andrew Cagan; Hannah R Rosenfield; Shawn N Murphy; Susanne E Churchill; Isaac S Kohane; Roy H Perlis
Journal:  BMJ       Date:  2014-10-24
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