Fall-related gerontechnology preventing falls among the elderly for ageing-in-place

Main Article Content

Saruda Jiratkulthana

Abstract

Population ageing is becoming a major social in many parts of the world, recent developments in the field of an ageing society thus have led to a renewed interest in safety among the elderly people. Since ageing affects both the physical changes and the psychological changes, the daily basic activities may be concerned regarding fall accident in the elderly who decide to live in their home when they get old called ageing-in-place. The technology of specific design through ergonomics along with gerontechnology which technology and service support the older adults therefore can reduce the risk and accident in the older people. The purpose of this review was to examine the identification of the technology and service that the gerontechnology has developed in independent living for the elderly concerning fall accident. The benefit and drawback of fall-related gerontechnologies which are fall prevention, fall detection and fall monitoring were also represented in this review. However, although the gerontechnology has successfully demonstrated that the technology and service can assist older adult, it has certain limitations in terms of the user acceptance and usability of technology including individual preferences. Regarding fall detectors, although floor detector, vibration detector and motion detector provide the privacy condition as the main concern to elderly, the other factors such as the complication in collecting the fall datasets, the various ways of fall and the number of datasets should be still considered. Additional research should be conducted on these and a survey of user's satisfaction including exploring the use of other types of assistive technology in helping and easing the responsibilities for a medical field at the hospitals or nursing care.

Article Details

Section
Review Articles

References

World Health Organization. Older Population and Health System: A profile of Thailand. Retrieved August. 2015;10:19-36

Everson-Rose SA, Lewis TT. Psychosocial factors and cardiovascular diseases. Annu Rev Pub Health. 2005;26:469-500.

Willis L, Goodwin J, Lee K, Mosqueda L, Garry P, Liu P et al. Impact of Psychosocial Factors on Health Outcomes in the Elderly. JAH. 1997;9(3):396-414.

Pereira GF. Gerontechnology for Fall Prevention, Detection, and Monitoring: Examining the Diffusion of Technology Among Older Adults for Aging-in-Place [Doctoral dissertation]. Oklahoma State University; 2018.

Mack R, Salmoni A, Viverais-Dressler G, Porter E, Garg R. Perceived Risks to Independent Living: The Views of Older, Community-Dwelling Adults. The Gerontologist. 1997;37(6):729-736.

Fänge A, Ivanoff S. The home is the hub of health in very old age: Findings from the ENABLE-AGE Project. Archives of Gerontology and Geriatrics. 2009;48(3):340-345.

Davey JA, de Joux V, Nana G, Arcus M. Accommodation options for older people in Aotearoa/New Zealand. Christchurch: Centre for Housing Research; 2004.

Sharifah Norazizan S, Roznah M, Tengku Aizan H, Lina G, Mohd Rizal H. Ageing-in-Place: Towards an ergonomically designed home environment for older Malaysians. Gerontechnology. 2006;5(2).

Masud T, Morris R. Epidemiology of falls. Age and Ageing. 2001;30(4):3-7.

Blake AJ, Morgan K, Bendall MJ, Dallosso H, Ebrahim SB, Arie TA, et al. Falls by elderly people at home: prevalence and associated factors. Age and ageing. 1988;1;17(6):365-372.

Larsson T, Hägvide M, Svanborg M, Borell L. Falls prevention through community intervention – A Swedish example. Safety Science. 2010;48(2):204-208.

Pinto MR, De Medici S, Van Sant C, Bianchi A, Zlotnicki A, Napoli C. Ergonomics, gerontechnology, and design for the home-environment. Applied Ergonomics. 2000;1;31(3):317-322.

Anderson KE. Falls in the elderly. Journal-royal College of Physicians of Edinburgh. 2008;1;38 (2):138.

Spirduso WW. Physical dimensions of aging. Champaign: Human Kinetics; 1995.

Buzink SN, Bruin RD, Groothuizen TJ, Haagsman EM, Molenbroek JF. Fall prevention in the toilet environment. A Friendly Rest Room: Developing Toilets of the Future for Disabled and Elderly People. 2011;15;27:183.

Câmara JJ, De Castro Engler RI, De Oliveira Fonseca PR. Analysis and ergonomics of houses for elderly people. Periodicum biologorum. 2010 Mar 31;112(1):47-50.

Pinto MR, De Medici S, Zlotnicki A, Bianchi A, Van Sant C, Napou C. Reduced visual acuity in elderly people: the role of ergonomics and gerontechnology. Age and ageing. 1997Sep 1;26(5):339-44.

Rahman MM. Design of A Sensor Based Smart Restroom System for Elderly People. [Doctoral dissertation]; Texas A&M University-Kingsville; 2019.

Cini LM. The future is here: Senior living reimagined. Bloomington, In: iUniverse, 2016.

Doyle, J., Bayley, C., Dromey, B., & Scanaill, C. N. An interactive technology solution to deliver balance and strength exercise to older adults. In Pervasive Computing Technologies for Healthcare (PervasiveHealth), 4th International Conference, Muchen, Germany, 2010, p.1-5.

Williams M, Soiza R, Jenkinson A, Stewart A. EXercising with C omputers in later life (EXCELL) - pilot and feasibility study of the acceptability of the Nintendo® WiiFit in community-dwelling fallers. BMC Research Notes. 2010;3(1).

Cumming R, Sherrington C, Lord S, Simpson J, Vogler C, Cameron I et al. Cluster randomised trial of a targeted multifactorial intervention to prevent falls among older people in hospital. BMJ. 2008;336(7647):758-760.

Kelly K, Phillips C, Cain K, Polissar N, Kelly P. Evaluation of a Nonintrusive Monitor to Reduce Falls in Nursing Home Patients. J Am Med Dir Assoc. 2002;3(6):377-382.

Bagnasco A, Scapolla AM, Spasova V. Design, implementation and experimental evaluation of a wireless fall detector. InProceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies 2011, p.1-5.

Kangas M, Konttila A, Lindgren P, Winblad I, Jämsä T. Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait & Posture. 2008;28(2):285-291.

Gjoreski H, Lustrek M, Gams M. Accelerometer placement for posture recognition and fall detection. In: 2011 Seventh International Conference on Intelligent Environments. 2011, p.47-54.

Vermeiren D, Weyn M, De Ron G. Detecting human motion: Introducing step, fall and adl algorithms. InInternational Conference on Electronic Healthcare. Springer, Berlin, Heidelberg. 2009, p.62-69.

Litvak D, Gannot I, Zigel Y. Detection of falls at home using floor vibrations and sound. In2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel. 2008, p.514-518.

Wu G. Distinguishing fall activities from normal activities by velocity characteristics. J Biomech. 2000;33(11):1497-1500.

Nyan M, Tay F, Tan A, Seah K. Distinguishing fall activities from normal activities by angular rate characteristics and high-speed camera characterization. Medical Engineering & Physics. 2006;28(8):842-849.

Igual R, Medrano C, Plaza I. Challenges, issues and trends in fall detection systems. BioMedical Engineering OnLine. 2013;12(1):66.

Pannurat N, Thiemjarus S, Nantajeewarawat E. Automatic Fall Monitoring: A Review. Sensors. 2014;14(7):12900-12936.

Tesfaye A, Ewenetu S. The Role of Gerontechnology in Elderly Well-being. 2018.