Abstract
Currently, there is a growing number of older people worldwide. This demographic change results in serious social and economic problems. Therefore governments, especially in developed countries, attempt to intervene in this process and help to enhance quality of life of older population groups with different means. One of the approaches in this respect is the use of mobile and wireless technologies in healthcare. The purpose of this article is to discuss the use of wearable and portable monitoring devices for older people in three areas of healthcare: fall detection, dementia care and low access to healthcare. The findings revealed that there is a lack of clinical studies examining the use of wearable devices in healthcare for older people. Therefore more research should be performed because the benefits of the use of wearable devices, such as their unobtrusiveness, sensitivity, or reliability, can contribute to the enhancement of quality of life of older people.
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References
AoA (2016). http://www.aoa.acl.gov/aging_statistics/index.aspx
Bujnowska-Fedak, M.M., Grata-Borkowska, U.: Use of telemedicine-based care for the aging and elderly: promises and pitfalls. Smart Homecare Technol. TeleHealth 3, 91–105 (2015)
Erostat: Databse Population (2016). http://ec.europa.eu/eurostat/data/database
Klimova, B., Maresova, P., Kuca, K.: Non-pharmacological approaches to the prevention and treatment of Alzheimer’s disease with respect to the rising treatment costs. Current Alzheimer Research (2016, in press)
Klimova, B., Maresova, P., Valis, M., Hort, J., Kuca, K.: Alzheimer’s disease and language impairments: social intervention and medical treatment. Clin. Interv. Aging 10, 1401–1408 (2015)
Maresova, P., Mohelska, H., Dolejs, J., Kuca, K.: Socio-economic aspects of Alzheimer’s disease. Curr. Alzheimer Res. 12, 903–911 (2014)
National Strategy for an Ageing Australia (2001). http://www.ifa-fiv.org/wp-content/uploads/2012/11/062_Australia-2001-National-Strategy-for-an-Ageing-Australia.pdf
Virginia Assistive Technology System: Assistive technology and aging. A Handbook for Virginians Who Are Aging and Their Caregivers (2016). http://www.vda.virginia.gov/pdfdocs/Assistive%20Technology%20&%20Aging%20-%20All.pdf
Wearable Technology (2016). http://www.investopedia.com/terms/w/wearable-technology.asp#ixzz4LLX0aRe7
Arean, P.A., Ly, K.H., Andersson, G.: Mobile technology for mental assessment. Dialogues Clin. Neurisci. 18, 163–169 (2016)
Kretschmar, M., Welsby, S.: Capacitive and Inductive Displacement Sensors, Sensor Technology Handbook. Newnes, Burlington (2005)
Semantic Sensor Network XG Final Report (2016). http://www.w3.org/2005/Incubator/ssn/XGR-ssn-20110628/
Klimova, B., Simonova, I., Poulova, P., Truhlarova, Z., Kuca, K.: Older people and their attitude to the use of information and communication technologies – a review study with special focus on the Czech Republic (older people and their attitude to ICT). Educ. Gerontol. 42, 361–369 (2016)
Dave, P.: Privacy and security in an age of wearable devices. Wearable Devices (2016). http://www.wearabledevices.com/2016/01/06/privacy-security-age-wearable-devices/
Thierer, A.: The internet of things and wearable technology. Mercatus Working Paper (2014). http://mercatus.org/sites/default/files/Thierer-Wearable-Tech.pdf
Kang, H.G., Mahonez, D., Hoenig, H., Hirth, V.A., Bonato, P., Hajjar, I., et al.: In situ monitoring of health in older adults: technologies and issues. J. Am. Geriatr. Soc. 58, 1579–1586 (2010)
Chaudhuri, S., Thompson, H., Demiris, G.: Fall detection devices and their use with older adults: a systematic review. J. Geriatr. Phys. Ther. 37, 178–196 (2014)
Igual, R., Medrano, C., Plaza, I.: Challenges, issues and trends in fall detection systems. Biomed. Eng. Online 12, 66 (2010)
Litvak, D., Zigel, Y., Gannot, I.: Fall detection of elderly through floor vibrations and sound. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, pp. 4632–4635 (2008)
Ariani, A., Redmond, S.J., Chang, D., Lovell, N.H.: Software simulation of unobtrusive falls detection at night-time using passive infrared and pressure mat sensors. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, pp. 2115–2118. (2010)
Zigel, Y., Litvak, D., Gannot, I.: A method for automatic fall detection of elderly people using floor vibrations and sound–proof of concept on human mimicking doll falls. IEEE Trans. Biomed. Eng. 56, 2858–2867 (2010)
Zhang, Z., Kapoor, U., Narayanan, M., Lovell, N.H., Redmond, S.J.: Design of an unobtrusive wireless sensor network for nighttime falls detection. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, pp. 5275–5278 (2011)
Bourennane, W., Charlon, Y., Bettahar, F., Campo, E., Esteve, D.: Homecare monitoring system: a technical proposal for the safety of the elderly experimented in an Alzheimer’s care unit. IRBM 34, 92–100 (2013)
Charlon, Y., Bourennane, W., Bettahar, F., Campo, E.: Activity monitoring system for elderly in a context of smart home. IRBM 34, 60–63 (2013)
Doukas, C.N., Maglogiannis, I.: Emergency fall incidents detection in assisted living environments utilizing motion, sound, and visual perceptual components. IEEE Trans. Inf Technol. Biomed. 15, 277–289 (2011)
Gietzelt, M., Spehr, J., Ehmen, Y., et al.: GAL@Home: a feasibility study of sensor-based in-home fall detection. Z. Gerontol. Geriatr. 45, 716–721 (2012)
Tasoulis, S.K., Doukas, C.N., Maglogiannis, I., Plagianakos, V.P.: Statistical data mining of streaming motion data for fall detection in assistive environments. In: Conference Proceedings IEEE Engineering in Medicine and Biology Society, pp. 3720–3723 (2011)
Langa, K.M., Foster, N.L., Larson, E.B.: Mixed dementia: emerging concepts and therapeutic implications. JAMA 292, 2901–2908 (2004)
Klimova, B., Kuca, K.: Speech and language impairments in dementia – a mini review. J. Appl. Biomed. 14, 97–103 (2016)
Dementia and elderly GPS tracking devices (2015). http://www.aplaceformom.com/blog/4-29-15-dementia-and-elderly-gps-tracking-devices/
Matthews, J.T., Lingler, J.H., Campbell, G.B., Hunsaker, A.E., Hu, L., Pires, B.R., et al.: Usability of a wearable camera system for dementia family caregivers. J. Healthc. Eng. 6, 213–238 (2015)
Abidoye, A.P., Azeez, N.A., Adesina, A.O., Agbele, K.K., Nyongesa, H.O.: Using wearable sensors for remote healthcare monitoring systém. J. Sens. Technol. 1, 22–28 (2011)
Acknowledgments
This paper is published thanks to the support of SPEV project 2017 run at the Faculty of Informatics and Management of the University of Hradec Kralove. The authors also thank Jan Freiberg for his help with data collection.
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Klimova, B., Maresova, P. (2017). Wearable and Portable Monitoring Devices for Older People. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_72
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DOI: https://doi.org/10.1007/978-981-10-5041-1_72
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