Intelligent assistive technology applications to dementia care: current capabilities, limitations, and future challenges.

The number of older Americans afflicted by Alzheimer disease and related dementias will triple to 13 million persons by 2050, thus greatly increasing healthcare needs. An approach to this emerging crisis is the development and deployment of intelligent assistive technologies that compensate for the specific physical and cognitive deficits of older adults with dementia, and thereby also reduce caregiver burden. The authors conducted an extensive search of the computer science, engineering, and medical databases to review intelligent cognitive devices, physiologic and environmental sensors, and advanced integrated sensor networks that may find future applications in dementia care. Review of the extant literature reveals an overwhelming focus on the physical disability of younger persons with typically nonprogressive anoxic and traumatic brain injuries, with few clinical studies specifically involving persons with dementia. A discussion of the specific capabilities, strengths, and limitations of each technology is followed by an overview of research methodological challenges that must be addressed to achieve measurable progress to meet the healthcare needs of an aging America.

[1]  E. Hristoforou,et al.  Displacement sensors using soft magnetostrictive alloys , 1994 .

[2]  A R Brown,et al.  Do it yourself: home-made aids for disabled elderly people. , 1997, Disability and rehabilitation.

[3]  Richard Levinson,et al.  The Planning and Execution Assistant and Trainer (peat) , 1997 .

[4]  J. Yesavage,et al.  Cognitive function and the costs of Alzheimer disease. An exploratory study. , 1997, Archives of neurology.

[5]  Stuart S. Blume,et al.  Technology Assessment and the Sociopolitics of Health Technologies , 2000, Journal of health politics, policy and law.

[6]  N. Bosanquet,et al.  The epidemic of Alzheimer's disease. How can we manage the costs? , 2000, PharmacoEconomics.

[7]  J. R. Scotti,et al.  Available From , 1973 .

[8]  Karel Vredenburg,et al.  User-Centered Design: An Integrated Approach , 2001 .

[9]  Albrecht Schmidt,et al.  Multi-sensor context aware clothing , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[10]  Paul Lukowicz,et al.  WearNET: A Distributed Multi-sensor System for Context Aware Wearables , 2002, UbiComp.

[11]  D. Bennett,et al.  Alzheimer disease in the US population: prevalence estimates using the 2000 census. , 2003, Archives of neurology.

[12]  J. Collins,et al.  Vibrating insoles and balance control in elderly people , 2003, The Lancet.

[13]  Andreas Krause,et al.  SenSay: a context-aware mobile phone , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..

[14]  Martha E. Pollack,et al.  Autominder: an intelligent cognitive orthotic system for people with memory impairment , 2003, Robotics Auton. Syst..

[15]  Sebastian Thrun,et al.  A robotic walker that provides guidance , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[16]  A. Dittmar,et al.  VTAM - a new "biocloth" for ambulatory telemonitoring , 2003, 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003..

[17]  P. Gorman,et al.  Effectiveness of the ISAAC cognitive prosthetic system for improving rehabilitation outcomes with neurofunctional impairment. , 2003, NeuroRehabilitation.

[18]  M. Skubic,et al.  Older adults' attitudes towards and perceptions of ‘smart home’ technologies: a pilot study , 2004, Medical informatics and the Internet in medicine.

[19]  Stephen J. McKenna,et al.  Activity summarisation and fall detection in a supportive home environment , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[20]  Stephen J. McKenna,et al.  Activity summarisation and fall detection in a supportive home environment , 2004, ICPR 2004.

[21]  Neil Johnson,et al.  A smart sensor to detect the falls of the elderly , 2004, IEEE Pervasive Computing.

[22]  J. Matthews,et al.  Everyday Health: Technology for Adaptive Aging , 2004 .

[23]  Henry A. Kautz,et al.  Inferring activities from interactions with objects , 2004, IEEE Pervasive Computing.

[24]  Theodoros N. Arvanitis,et al.  The design of the SensVest , 2004, Personal and Ubiquitous Computing.

[25]  A. Mihailidis,et al.  Assistive technology for cognitive rehabilitation: State of the art , 2004 .

[26]  J. Barbenel,et al.  The efficacy of an intelligent cognitive orthosis to facilitate handwashing by persons with moderate to severe dementia , 2004 .

[27]  Richard W Pew,et al.  Technology for Adaptive Aging , 2004 .

[28]  P. Castiglioni,et al.  A textile-based wearable system for vital sign monitoring: applicability in cardiac patients , 2005, Computers in Cardiology, 2005.

[29]  Martha E. Pollack,et al.  Intelligent Technology for an Aging Population: The Use of AI to Assist Elders with Cognitive Impairment , 2005, AI Mag..

[30]  Sidney S. Fels,et al.  A visual recipe book for persons with language impairments , 2005, CHI.

[31]  Garrett R. Brown,et al.  An Accelerometer Based Fall Detector : Development , Experimentation , and Analysis , 2005 .

[32]  Alex Mihailidis,et al.  An intelligent emergency response system: preliminary development and testing of automated fall detection , 2005, Journal of telemedicine and telecare.

[33]  M. Alwan,et al.  A Smart and Passive Floor-Vibration Based Fall Detector for Elderly , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[34]  Alex John London,et al.  Ethical Considerations in the Conduct of Electronic Surveillance Research , 2006, The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics.

[35]  Mark D. Miller,et al.  Psychotherapy in long-term care: A review. , 2006, Journal of the American Medical Directors Association.

[36]  B. Winblad,et al.  An Estimate of the Worldwide Prevalence and Direct Costs of Dementia in 2003 , 2006, Dementia and Geriatric Cognitive Disorders.

[37]  Shahram Izadi,et al.  SenseCam: A Retrospective Memory Aid , 2006, UbiComp.

[38]  S. Ann Becker,et al.  In-home monitoring of persons with dementia: Ethical guidelines for technology research and development , 2007, Alzheimer's & Dementia.

[39]  A. Sixsmith,et al.  Quality of Life Technologies for People With Dementia , 2007 .

[40]  Henry A. Kautz,et al.  Learning and inferring transportation routines , 2004, Artif. Intell..

[41]  Simon Brownsell,et al.  The role of telecare in supporting the needs of elderly people , 2007, Journal of telemedicine and telecare.

[42]  Chad A. Phipps,et al.  CareWatch: A Home Monitoring System for Use in Homes of Persons With Cognitive Impairment , 2007, Topics in geriatric rehabilitation.

[43]  Elizabeth D. Mynatt,et al.  Using Memory Aid to Build Memory Independence , 2007, HCI.

[44]  Takeo Kanade,et al.  CareMedia: Automated Video and Sensor Analysis for Geriatric Care , 2007 .

[45]  W. Mann,et al.  Older Adults' Perception and Use of PDAs, Home Automation System, and Home Health Monitoring System , 2007 .

[46]  Anthony Almudevar,et al.  Home monitoring using wearable radio frequency transmitters , 2008, Artif. Intell. Medicine.