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Independent Living Applications

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Introduction to Nursing Informatics

Part of the book series: Health Informatics ((HI))

Abstract

Countries globally have been experiencing an unprecedented increase in the number of older adults. As a result there has been an elevated interest in understanding the factors that may support the maintenance of independent living and quality of life of older adults. There is a large role for innovative technology to support monitoring, early detection and management of health and wellbeing in the home. Most diagnostic and treatment approaches to health are centered in clinical settings, and very few have focused on improving the self-management of wellbeing using novel in-home, ICT (information communication technology) based intervention systems. Utilizing combinations of ambient sensor data acquisition, telehealth and ICT it is possible to predict changes in wellbeing, and to deliver feedback and interventions to support personal wellness management.

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Notes

  1. 1.

    The dependency ratio is an age population ratio of those typically not in the labor force (the dependent part) and those typically in the labor force. It is calculated as (number of people aged 65 and over/number of people aged 15–64) × 100.

  2. 2.

    http://wid.wisc.edu/research/lel/

  3. 3.

    https://www.mindbloom.com/

  4. 4.

    http://moodjam.com/

  5. 5.

    http://moodpanda.com/

  6. 6.

    Centers for Disease Control: Chronic Disease at a Glance 2009. See:

    http://www.cdc.gov/nccdphp/publications/AAG/chronic.htm

  7. 7.

    Gerard Anderson, “Chronic Conditions: Making the Case for Ongoing Care” (Partnership to Fight Chronic Disease: November 2007). See: http://www.fightchronicdisease.com/news/pfcd/pr12102007.cfm

  8. 8.

    http://3millionlives.co.uk/

References

  1. Hayutin AM. How population aging differs across countries: a briefing on global demographics. Stanford Center on Longevity US. California: Stanford; 2007.

    Google Scholar 

  2. Kinsella K, Wan H. An ageing world: 2008. United States Census Bureau, International Population Reports P95/09-1 11; 2009.

    Google Scholar 

  3. CSO Ireland Ageing in Ireland Report. 2007. Available at: http://www.cso.ie/en/media/csoie/releasespublications/documents/otherreleases/2007/ageinginireland.pdf.

  4. US Census Bureau. An aging world. 2008. Available at: https://www.census.gov/prod/2009pubs/p95-09-1.pdf.

  5. Centers for Disease Control and Prevention. Health, United States. Hyattsville: National Center for Health Statistics; 2011.

    Google Scholar 

  6. European Commission. Major and chronic diseases executive summary. European Commission. Belgium: Brussels; 2007.

    Google Scholar 

  7. Turner K, Arnott A, Gray PD, Renals S, et al. Grand challenge in assisted living – home care technologies. Match Consortium, UKCRC Grand Challenges in Computing Research. Edinburgh, 2010.

    Google Scholar 

  8. DeFrances CJ, Hall MJ, Podgornik MN. 2003 national hospital discharge survey. Advance data from vital and health statistics, 359. Hyattsville: National Center for Health Statistics; 2005.

    Google Scholar 

  9. Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2008;360:1418–28.

    Article  Google Scholar 

  10. Dewsbury G, Clarke K, Rouncefield M, Sommerville I. Depending on digital design: extending inclusivity. Housing Stud. 2004;19(5):811–25.

    Article  Google Scholar 

  11. Koch S. Home tele-health current state and future trends. Int J Med Inform. 2006;75:565–76.

    Article  PubMed  Google Scholar 

  12. Magnusson L, Hanson E, Borg M. A literature review study of information and communication technology as a support for frail older people living at home and their family carers. Technol Disabil. 2004;16:223–35.

    Google Scholar 

  13. Brennan PF, Moore SM, Smyth KA. Computer link: electronic support for the home caregiver. ANS Adv Nurs Sci. 1991;13(4):14–27.

    Article  CAS  PubMed  Google Scholar 

  14. Brennan PF, Moore S, Bjomsdottir G, Jones J, Visovsky C, Rogers M. HeartCare: an internet-based information and support system for patient home recovery after coronary artery bypass graft (CABG) surgery. J Adv Nurs. 2001;35(5):699–708.

    Article  CAS  PubMed  Google Scholar 

  15. Cooper R. Wheeled mobility and manipulation technologies. The Bridge: Linking Engineering and Society; 2009.

    Google Scholar 

  16. Steventon A, Bardsley M, Billings J, Dixon J, et al. Effect of telehealth on use of secondary care and mortality: findings from the Whole System Demonstrator cluster randomised trial. BMJ. 2012;344:e3874.

    Article  PubMed Central  PubMed  Google Scholar 

  17. Czaja S, Charness N, Fisk A, Hertzog C, Nair S, Rogers W, Sharit J. Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychol Aging. 2006;21(2):333–52.

    Article  PubMed Central  PubMed  Google Scholar 

  18. Hawthorn D. Possible implications of aging for interface designers. Interacting Comput. 2000;12:507–28.

    Article  Google Scholar 

  19. Salces FS, Baskett M, LLewelyn-Jones D, England D. Ambient interfaces for elderly people at home. Ambient Intelligence in Everyday Life. Lecture notes in computer science 2864. 2006. pp. 256–84.

    Google Scholar 

  20. Gardner D, Helmes E. Locus of control and self-directed learning as predictors of well-being in the elderly. Aust Psychol. 1999;34(2):99–103.

    Article  Google Scholar 

  21. Melenhorst AS, Rogers W, Caylor E. The use of communication technologies by older adults: exploring the benefits from the user’s perspective. Human factors and ergonomics society 45th annual meeting. Minneapolis, USA; 2001.

    Google Scholar 

  22. Davis F. A Technology acceptance model for empirically testing new end-user information systems: theory and results. Unpublished doctoral thesis, MIT Sloan School of Management, Cambridge, MA, 1985.

    Google Scholar 

  23. Oppenauer C. Motivation and needs for technology use in old age. Gerontechnology. 2009;8(2):82–7.

    Article  Google Scholar 

  24. Wilkowska W, Ziefle M. Which factors form older adults’ acceptance of mobile information and communication technologies? In: Proceedings of HCI and usability for E-Inclusion, USAB, Linz: Springer LNCS; 9–10 Nov 2009. pp. 81–101.

    Google Scholar 

  25. Umemuro H. Computer attitudes, cognitive abilities and technology usage among Japanese older adults. Gerontechnology. 2004;3(2):64–76.

    Article  Google Scholar 

  26. Alm M, Gregor P, Newell AF. Older people and information technology are ideal partners. In: Proceedings of the international conference on for universal design (UD 2002), Yokohama, 2002.

    Google Scholar 

  27. Carmichael A, Rice M, MacMillan F, Kirk A. Investigating a DTV-based physical activity application to facilitate wellbeing in older adults. In: Proceedings of HCI conference on people and computers XXIV (HCI 2010), Dundee, 2010. pp. 278–88.

    Google Scholar 

  28. Doyle J, Skrba Z, McDonnell R, Arent B. Designing a touch screen communication device to support social interaction amongst older adults. In: Proceedings of HCI conference on people and computers XXIV (HCI 2010), Dundee, 2010. pp. 177–85.

    Google Scholar 

  29. Jones C, Winegarden C, Rogers W. Supporting healthy aging with new technologies. ACM Interactions. 2009;16(4):48–51.

    Article  Google Scholar 

  30. Bieber G, Koldrack P, Sablowski C, Peter C, Urban B. Mobile physical activity recognition of stand-up and sit-down transitions for user behaviour analysis. In: Proceedings of 3rd international conference on PErvasive technologies related to assistive environments, Samos, 23–25 June 2010.

    Google Scholar 

  31. Lorenz A, Mielke S, Oppermann R, Zahl L. Personalised mobile health monitoring for elderly. In: Proceedings of 9th international conference on Human Computer Interaction with Mobile Devices and Services (Mobile HCI), Singapore, 11–14 Sept 2007. pp. 297–304.

    Google Scholar 

  32. Doyle J, Bailey C, Dromey B, Ni Scanaill C. BASE – an interactive technology solution to deliver balance and strength exercises to older adults. In: Proceedings of 4th international conference on Pervasive Computing Technologies for Healthcare, Munich, 22–25 Mar 2010. pp. 1–5.

    Google Scholar 

  33. Tinetti M, Williams C. The effect of falls and fall injuries on functioning in community-dwelling older persons. J Gerontol A Biol Sci Med Sci. 1998;53(2):M112–9.

    Article  CAS  PubMed  Google Scholar 

  34. Chang JT, Morton SC, Rubenstein LZ, Mojica WA, et al. Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomized clinical trials. BMJ. 2004;328:680–3.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Gannon B, O’Shea E, Hudson E. Economic cost of falls and fractures among older people in Ireland. Ir Med J. 2008;101(6):170–3.

    CAS  PubMed  Google Scholar 

  36. Kerse N, Flicker L, Plaff JJ, et al. Falls, depression and antidepressants in later life: a large primary care appraisal. PLoS One. 2008;3(6):e2423.

    Article  PubMed Central  PubMed  Google Scholar 

  37. Stevens JA, Corso PS, Finkelstein EA, Miller TR. The cost of fatal and non-fatal falls among older adults. Inj Prev. 2006;12:290–5.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007;62:722–7.

    Article  PubMed  Google Scholar 

  39. Bandeen-Roche K, Xue QL, Ferrucci L, et al. Phenotype of frailty: characterisation in the women’s health and aging studies. J Gerontol A Biol Sci Med Sci. 2006;61A:262–6.

    Article  Google Scholar 

  40. Santos-Eggiman B, Cuenod P, Spagnoli J, Junod J. Prevalence of frailty in middle-aged and older community-dwelling Europeans living in 10 countries. J Gerontol A Biol Sci Med Sci. 2009;64(6):675–81.

    Article  Google Scholar 

  41. Smit E, Winters-Stone KM, Loprinzi PD, Tang AM, Crespo C. Lower nutritional status and higher food insufficiency in frail older US adults. Br J Nutr. 2013;110(1):172–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Fillit H, Butler RN. The frailty identity crisis. J Am Geriatr Soc. 2009;57:348–53.

    Article  PubMed  Google Scholar 

  43. SilverFit. http://www.silverfit.nl/en/index.htm. Accessed Feb 2014.

  44. Egglestone SR, Axelrod L, Nind T et al. A design framework for a home-based stroke rehabilitation system: identifying the key components. In: Proceedings of 3rd international conference on Pervasive Computing Technologies for Healthcare, London, 1–3 Apr 2009. pp. 1–8.

    Google Scholar 

  45. Campbell AJ, Robertson MC, Gardner MM, et al. Randomised control trial of a general practice programme of home based exercise to prevent falls in elderly women. BMJ. 1997;315:1065–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  46. Hawkley LC, Preacher KJ, Cacioppo JT. Loneliness impairs daytime functioning but not sleep duration. Health Psychol. 2010;29:124–9.

    Article  PubMed Central  PubMed  Google Scholar 

  47. Hawkley LC, Thisted RA, Masi CM, Cacioppo JT. Loneliness predicts increased blood pressure: five-year cross-lagged analyses in middle-aged and older adults. Psychol Aging. 2010;25:132–41.

    Article  PubMed Central  PubMed  Google Scholar 

  48. Tilvis RS, Kahonen-Vare MH, Jolkkonen J, Valvanne J, Pitkala KH, Strandberg TE. Predictors of cognitive decline and mortality of aged people over a 10-year period. J Gerontol A Biol Sci Med Sci. 2004;59:268–74.

    Article  PubMed  Google Scholar 

  49. Patterson AC, Veenstra G. Loneliness and risk of mortality: a longitudinal investigation in Alameda County, California. Soc Sci Med. 2010;71:181–6.

    Article  PubMed  Google Scholar 

  50. Czaja S, Guerrier J, Nair S, Landauer T. Computer communication as an aid to independence for older adults. Behav Inform Technol. 1993;12(4):197–207.

    Article  Google Scholar 

  51. Dalsgaard T, Skov M, Thomassen B. eKiss: sharing experiences in families through a picture blog. In: Proceedings of HCI conference on People and Computers XXI (HCI 2007), Lancaster, 3–7 Sept 2007. pp. 67–75.

    Google Scholar 

  52. Sokoler T, Svensson MS. Presence remote: embracing ambiguity in the design of social TV for senior citizens. In: Changing television environments – 6th European conference EUROITV. Salzburg, Austria; 2008. pp. 158–62.

    Google Scholar 

  53. Riche Y, Mackay W. PeerCare: supporting awareness of rhythms and routines for better aging in place. Comput Supported Coop Work. 2010;19(1):73–104.

    Article  Google Scholar 

  54. Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, et al. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005;366(9503):2112–7.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Astell A, Alm N, Gowans G, Ellis M, Dye R, Vaughan P. Involving older people with dementia and their carers in designing computer based support systems: some methodological considerations. Universal Access in the Information Society. 2009;8(1)49–58.

    Google Scholar 

  56. Arnott J, Alm N, Waller A. Cognitive prostheses: communication, rehabilitation and beyond. In: Proceedings of IEEE system man and cybernetics conference, 1999. pp. 346–51.

    Google Scholar 

  57. Kautz H, Arnstein L, Borriello G, Etzioni O, Fox D. An overview of the assisted cognition project. In: AAAI-2002 workshop on automation as Caregiver: the role of intelligent technology in elder care. Edmonton, AB, Canada; 2002.

    Google Scholar 

  58. Wherton J, Monk AF. Problems people with dementia have with kitchen tasks: the challenge for pervasive computing. Interacting Comput. 2010;22(4):253–66.

    Article  Google Scholar 

  59. Wherton J, Monk AF. Technological opportunities for supporting people with dementia who are living at home. Int J Hum Comput Stud. 2008;66:571–86.

    Article  Google Scholar 

  60. Woods B, Spector A, Jones C, Orrell M, Davies S. Reminiscence therapy for dementia. Cochrane Database Syst Rev. 2005;(2):CD001120.

    Google Scholar 

  61. Sarne-Fleischmann V, Tractinsky N, Dwolatzky T, Rief I. Personalized reminiscence therapy for patients with Alzheimer’s disease using a computerized system. In: Proceedings of the 4th international conference on Pervasive Technologies Related to Assistive Environments (PETRA ’11), 2011.

    Google Scholar 

  62. Kikhia B, Hallberg J, Synnes K, Sani Z. Context-aware life-logging for persons with mild dementia. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:6183–6. doi: 10.1109/IEMBS.2009.5334509.

  63. Dem@Care EU Project. http://www.demcare.eu/.

  64. McHugh JE, Wherton JP, Prendergast DK, Lawlor BA. Teleconferencing as a source of social support for older spousal caregivers: initial explorations and recommendations for future research. Am J Alzheimers Dis Other Demen. 2012;27(6):381–7.

    Article  PubMed  Google Scholar 

  65. McHugh JE, Wherton JP, Prendergast DK, Lawlor BA. Identifying opportunities for supporting caregivers of persons with dementia through information and communication technology. Gerontechnology. 2012;10(4):220–30.

    Google Scholar 

  66. Discover for Carers EU Project. http://www.discover4carers.eu/.

  67. Vurgun S, Philipose M, Pavel M. A statistical reasoning system for medication prompting. In: Proceedings of UbiComp. Innsbruck, Austria; 2007. pp. 1–18.

    Google Scholar 

  68. Consolvo S, Landay JA. Designing for behaviour change in everyday life. IEEE Comput. 2009;42(6):86–9.

    Article  Google Scholar 

  69. Lane ND, Mohammod M, Lin M et al. BeWell: a smartphone application to monitor, model and promote wellbeing. In: Proceedings of 5th international conference on Pervasive Computing Technologies for Healthcare, Dublin, 23–26 May 2011.

    Google Scholar 

  70. Doyle J, O’Mullane B, McGee S, Knapp B. YourWellness: designing an application to support positive emotional wellbeing in older adults. In: Proceedings of HCI conference on People and Computers XXVI (HCI 2012), Birmingham, 12–14 Sept 2012.

    Google Scholar 

  71. Marcu G, Bardram JE, Gabrielli S. A framework for overcoming challenges in designing persuasive monitoring and feedback systems for mental illness. In: Proceedings of 5th international conference on Pervasive Computing Technologies for Healthcare, Dublin, 23–26 May 2011.

    Google Scholar 

  72. Cruickshank J, Beer G, Winpenny E, Manning J. Healthcare without walls: a framework for delivering telehealth at scale. 2010. Available at http://www.2020health.org/2020health/Publication-2012/NHSit/telehealth.html.

  73. McLean A, Protti D, Sheikh A. Telehealth for long term conditions. BMJ. 2011;342:d120.

    Article  PubMed  Google Scholar 

  74. Farmer A, Gibson O, Tarassenko L, Neil A. A systematic review of telemedicine interventions to support blood glucose self-monitoring in diabetes. Diabet Med. 2005;22:1372–8.

    Article  CAS  PubMed  Google Scholar 

  75. Martinez A, Everss E, Rojo-Alvarez J, Figal D, Garcia-Alberola A. A systematic review of the literature on home monitoring for patients with heart failure. J Telemed Telecare. 2006;12:234–41.

    Article  PubMed  Google Scholar 

  76. Barlow J, Singh D, Bayer C, Curry R. A systematic review of the benefits of home telecare for frail elderly people and those with long-term conditions. J Telemed Telecare. 2007;13:172–9.

    Article  PubMed  Google Scholar 

  77. Canadian Health Infoway Collaboration and communication for Chronic Disease Patients. Available at: http://www.youtube.com/watch?v=9ICjviv1_-8.

  78. Bower P, Cartwright M, Hirani SP, Barlow J, et al. A comprehensive evaluation of the impact of telemonitoring in patients with long-term conditions and social care needs: protocol for the whole systems demonstrator cluster randomised trial. BMC Health Serv Res. 2011;11:184.

    Article  PubMed Central  PubMed  Google Scholar 

  79. Bardram JE, Bossen C, Thomsen A. Designing for transformations in collaboration – a study of the deployment of homecare technology. In: Proceedings of GROUP ‘05. Sanibel Island, FL, USA; 2005.

    Google Scholar 

  80. Canada Health Infoway Telehealth Benefits and Adoption: Connecting People and Providers Across Canada. 2011. Available at: https://www.infoway-inforoute.ca/index.php/resources/toolkits/knowing-is-better-for-clinicians/index.php?searchword=benefits+of+telehealth&ordering=newest&searchphrase=all&areas%5B%5D=docman&limit=5&option=com_search&Itemid=736. Accessed 12 Feb 2014.

  81. Cook D, Hagras H, Callaghan V, Helal A. Making our environments intelligent. J Pervasive Mobile Comput. 2009;5:556–7.

    Article  Google Scholar 

  82. Cook D, Schmitter-Edgecombe M, Crandall A, Sanders C, Thomas B. Collecting and disseminating smart home sensor data in the CASAS project. In: Proceedings of the CHI workshop on developing shared home behavior datasets to advance HCI and ubiquitous computing research. Boston, MA, USA; 2009.

    Google Scholar 

  83. Skubic M, Guevara R, Rantz M. Testing classifiers for embedded health assessment. Impact analysis of solutions for chronic disease prevention and management. In: Icost 2012, LNCS 7251, 2012. pp 198–205 Springer-Verlag, Berlin Heidelberg.

    Google Scholar 

  84. Bhattacharya A, Das SK. LeZi-Update: an information-theoretic approach to track mobile users in PCS networks. In: Proceedings of the 5th annual ACM/IEEE international conference on Mobile Computing and Networking (MobiCom’99). Seattle, WA, USA; 1999.

    Google Scholar 

  85. Das SK, Cook DJ, Bhattacharya A, Heierman EO, Lin TY. The role of prediction algorithm in the MavHome smart home architecture. IEEE Wireless Commun. 2002;9(6):77–84.

    Article  Google Scholar 

  86. Jain G, Cook D, Jakkula V, Monitoring health by detecting drifts and outliers for a smart environment inhabitant. In: Proceedings of the international conference on smart homes and health telematics (I-COST), Northern Ireland, 2006. pp. 114–21.

    Google Scholar 

  87. Helal S, Mann W, El-Zabadani H, King J, Kaddoura Y, Jansen E. The gator tech smart house: a programmable pervasive space. Computer. 2005;38(3):50–60.

    Article  Google Scholar 

  88. Mozer MC. The neural network house: an environment that’s adapts to its inhabitants. In: Proceedings of the AAAI spring symposium on intelligent environments, technical report SS-98-02. Palo Alto, CA, USA; 1998. pp.110–4.

    Google Scholar 

  89. Kidd CD, Orr R, Abowd GD, Atkeson CG, Essa IA, MacIntyre B, Mynatt ED, Starner T, Newstetter W. The aware home: a living laboratory for ubiquitous computing research. In: Proceedings of the second international workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture (CoBuild ’99). Pittsburgh, PA, USA; 1999. pp. 191–8.

    Google Scholar 

  90. Kientz JA, Patel SN, Jones B, Price E, Mynatt ED, Abowd GD, The Georgia Tech aware home. In: Proceedings of CHI ’08 Extended Abstracts on Human Factors in Computing Systems (CHI EA ’08). Florence, Italy; 2008. pp. 3675–80.

    Google Scholar 

  91. Intille SS. Designing a home of the future. IEEE Pervasive Comput. 2002;1(2):76–82.

    Article  Google Scholar 

  92. Logan B, Healey J, Philipose M, Tapia EM, Intille S. A long-term evaluation of sensing modalities for activity recognition. In: Proceedings of the 9th international conference on Ubiquitous Computing (UbiComp ’07). Innsbruck, Austria; 2007. pp. 483–500.

    Google Scholar 

  93. Tapia EM, Intille SS, Larson K. Activity recognition in the home setting using simple and ubiquitous sensors. In: Proceedings of PERVASIVE. Vienna, Austria; 2004. pp. 158–75.

    Google Scholar 

  94. Chen C, Das B, Cook D. A data mining framework for activity recognition in smart environments. In: Proceedings of the international conference on Intelligent Environments. Kuala Lumpur, Malaysia; 2010.

    Google Scholar 

  95. Rashidi P, Cook DJ, Holder LB, Schmitter-Edgecombe M. Discovering activities to recognize and track in a smart environment. IEEE Trans Knowl Data Eng. 2011;23(4):527–39.

    Article  PubMed Central  PubMed  Google Scholar 

  96. Jimison H, Bajcsy R. Integrated communications and inference systems for continuous coordinated care of older adults in the home. NSF Collaborative Research Grant. http://www.orcatech.org/research/studies/integrated-communications-and-inference-systems-for-continuous-coordinated-care-of-older-adults-in-the-home. Accessed Feb 2014.

  97. Kaye JA, Maxwell SA, Mattek N, Hayes T, Dodge H, Pavel M, Jimison H, Wild K, Boise KL, Zitzelberger T. Intelligent systems for assessing aging changes: home-based, unobtrusive and continuous assessment of aging. J Gerontol Psychol Sci. 2011;66B:i180–90.

    Article  Google Scholar 

  98. O’Brien A, McDaid K, Loane J, Doyle J, Walsh L. Visualisation of movement of older adults within their homes based on PIR sensor data. In: Proceedings of PERVASENSE, workshop at pervasive health’12, San Diego, 2012.

    Google Scholar 

  99. Loane J, O’ Mullane B, Bortz B, Knapp B. Looking for similarities in movement between and within homes using cluster analysis. Health Informatics J. 2012;18(3):202–11.

    Article  PubMed  Google Scholar 

  100. O’Mullane B, Knapp B, O’Hanlon A, Loane J, Bortz B. Comparison of health measures to movement data in aware homes. In: Aml’ll Proceedings of the second international conference on Ambient Intelligence, Amsterdam, 2011. pp. 290–4.

    Google Scholar 

  101. Doyle J, O’Mullane B, O’Hanlon A, Knapp B. Requirements gathering for the delivery of healthcare data in aware homes. In: 5th Intl conference on pervasive computing technologies for healthcare, Dublin, 2011.

    Google Scholar 

  102. Doyle J, Kealy A, Loane J, Walsh L, et al. An integrated home-based self-management system to support the wellbeing of older adults. Accepted for publication in Journal of Ambient Intelligence and Smart Environments (JAISE); 2014;6(4):359–83.

    Google Scholar 

  103. Hybels CF, Blazer DG. Epidemiology of late-life mental disorders. Clin Geriatr Med. 2003;19(4):48–51.

    Google Scholar 

  104. Manabe T, Matsui M, Yamaya T, Sato-Nakagawa N, Okamura H, Arai H, Sasaki H. Sleep patterns and mortality among elderly patients in a geriatric hospital. Gerontology. 2000;46(6):318–22.

    Article  CAS  PubMed  Google Scholar 

  105. Miles LE, Dement WC. Sleep and aging. Sleep. 1980;3(3):119–220.

    Google Scholar 

  106. Ancoli-Israil S. Sleep problems in older adults: putting myths to bed. Geriatrics. 1997;52(1):20–9.

    Google Scholar 

  107. Barbar SI, Enright PL, Boyle P, Foley D, Sharp S, Petrovitch H, Quan SF. Sleep disturbances and their correlates in elderly Japanese American men residing in Hawaii. J Gerontol A Biol Sci Med Sci. 2000;55(7):406–11.

    Article  Google Scholar 

  108. Brassington GS, King AC, Bliwise DL. Sleep problems as a risk factor for falls in a sample of community-dwelling adults aged 64-99 years. J Am Geriatr Soc. 2000;48(10):1234–40.

    CAS  PubMed  Google Scholar 

  109. Happe S. Excessive daytime sleepiness and sleep disturbances in patients with neurological diseases. Drugs. 2003;63(24):2725–37.

    Article  PubMed  Google Scholar 

  110. Walsh L, Moloney E and McLoone S. Identification of nocturnal movements during sleep using non-contact under mattress bed sensor. In: Proceedings of 33rd annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC’11), Boston, 2011.

    Google Scholar 

  111. Kealy A, McDaid K, Loane J, Walsh L, Doyle J. Derivation of night time behaviour metrics using ambient sensors. In: Proceedings of 7th international conference on pervasive computing technologies for healthcare (Pervasive Health’13), Venice, 5–8 May 2013.

    Google Scholar 

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Acknowledgements

We would like to acknowledge the team at CASALA and Netwell, all of whom have contributed to ongoing research there, including Rodd Bond, Andrew MacFarlane, Benjamin Knapp, Brian O’Mullane, Carl Flynn, John Loane and Andrea Kealy. CASALA is funded under Enterprise Ireland’s Applied Research Enhancement Program with support from EU structural funds. Research at the Netwell Centre is supported by Atlantic Philanthropies.

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Doyle, J., Walsh, L. (2015). Independent Living Applications. In: Hannah, K., Hussey, P., Kennedy, M., Ball, M. (eds) Introduction to Nursing Informatics. Health Informatics. Springer, London. https://doi.org/10.1007/978-1-4471-2999-8_9

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