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Technologies for Health Assessment, Promotion, and Assistance: Focus on Gerontechnology

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Abstract

With the aging of the world’s population, it is becoming increasingly urgent to develop innovative and preventative health-care methods. If we are to provide the highest quality of care to our aging population, we must consider technological innovations in our future planning and implementation. Technologies have the potential to offer innovations for home-based prevention, early detection, independent living, safety and security, behavioral change, social support, and caregiver aid. Neuropsychologists have the opportunity to play an important role in the development, evaluation, and dissemination of these technologies. In this chapter, we describe our multidisciplinary work with both simple and artificial intelligence-based technologies that can be used proactively to promote healthy lifestyle behaviors and improve autonomy and quality of life. We also discuss challenges that remain to be addressed as the field of gerontechnology moves forward.

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References

  • Babbitt, R. (2006, September). Information privacy management in smart home environments: Modeling, verification, and implementation. Presented at Computer Software and Applications Conference, Chicago, IL.

    Google Scholar 

  • Barger, T. S., Brown, D. E., & Alwan, M. (2005). Health status monitoring through analysis of behavioral patterns. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 35(1), 22–27. doi:10.1109/TSMCA.2004.838474.

    Article  Google Scholar 

  • Barnett, A., Smith, B., Lord, S. R., Williams, M., & Baumand, A. (2003). Community-based group exercise improves balance and reduces falls in at-risk older people: A randomized controlled trial. Age and Ageing, 32, 407–414. doi:10.1093/ageing/32.4.407.

    Article  PubMed  Google Scholar 

  • Bayer, A.-H., & Harper, L. (2000). Fixing to stay: A national survey of housing and home modification issues. AARP. Retrieved from http://www.aarp.org/home-garden/housing/info-2000/aresearch-import-783.html

  • Beringer, R., Sixsmith, A., Campo, M., Brown, J., & McCloskey, R. (2011). Theacceptanceof ambient assisted living: Developing an alternate methodology to this limited research lens. Presented at the 9th International Conference on Smart Homes and Health Telematics, Montréal, Canada.

    Google Scholar 

  • Blanson Henkemans, O. A., Caine, K. E., Rogers, W. A., Fisk, A. D., Neerincx, M. A., & de Ruyter, B. (2007). Medical monitoring for independent living: User-centered design of smart home technologies for older adults. Presented at Med-e-Tel, Luxembourg.

    Google Scholar 

  • Boger, J., Hoey, J., Poupart, P., Boutilier, C., Fernie, G., & Mihaildis, A. (2006). A planning system based on Markov decision processes to guide people with dementia through activities of daily living. IEEE Transactions on Information Technology in Biomedicine, 10, 323–333. doi:10.1109/TITB.2005.864480.

    Article  PubMed  Google Scholar 

  • Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys, 41(3), 1–58.

    Article  Google Scholar 

  • Ching-Show, L. (2008). Technology for care. Gerontechnology, 7(4), 349–350.

    Google Scholar 

  • Chute, D. L. (2002). Neuropsychological technologies in rehabilitation. The Journal of Head Trauma Rehabilitation, 17(5), 369–377.

    Article  PubMed  Google Scholar 

  • Clare, L., Wilson, B. A., Carter, G., & Hodges, J. R. (2003). Cognitive rehabilitation as a component of early intervention in Alzheimer’s disease: A single case study. Aging & Mental Health, 7(1), 15–21. doi:10.1080/1360786021000045854.

    Article  Google Scholar 

  • Cohen-Mansfield, J., & Biddison, J. (2007). The scope and future trends of gerontechnology: Consumers’ opinions and literature survey. Journal of Technology in Human Services, 25(3), 1–19.

    Article  Google Scholar 

  • Comeau, D. E. (2005). Proposal for a course of instruction in Gerontechnology within the University of North Texas Gerontology Program: “Gerontechnology: A class on aging with technology.

    Google Scholar 

  • Cook, D. (2012). Learning setting-generalized activity models for smart spaces. IEEE Intelligent Systems, 27(1), 32–38. doi:10.1109/MIS.2010.112.

    Article  Google Scholar 

  • Cook, D. J., & Schmitter-Edgecombe, M. (2009). Assessing the quality of activities in a smart environment. Methods of Information in Medicine, 48, 480–485. doi:10.3414/ME0592.

    Article  PubMed  Google Scholar 

  • Courtney, K. L. (2008). Privacy and senior willingness to adopt smart home information technology in residential care facilities. Methods of Information in Medicine, 47(1), 76–81. doi:10.3414/ME9104.

    PubMed  Google Scholar 

  • Courtney, K. L., Demiris, G., & Hensel, B. K. (2007). Obtrusiveness of information-based assistive technologies as perceived by older adults in residential care facilities: A secondary analysis. Medical Informatics and the Internet in Medicine, 32(3), 241–249. doi:10.1080/14639230701447735.

    Article  PubMed  Google Scholar 

  • Crilly, J. F., Keefe, R. H., & Volpe, F. (2011). Use of electronic technologies to promote community and personal health for individuals unconnected to health care systems. American Journal of Public Health, 101(7), 1163–1167. doi:10.2105/AJPH.2010.300003.

    Article  PubMed  Google Scholar 

  • Cruz-Jentoft, A. J., Franco, A., Sommer, P., Baeyens, J.-P., Jankowska, E., Maggi, A., et al. (2008). European silver paper on the future of health promotion and preventive actions, basic research, and clinical aspects of age-related disease. Gerontechnology, 7(4), 331–399.

    Article  Google Scholar 

  • Das, B., Cook, D. J., Schmitter-Edgecombe, M., & Seelye, A. M. (2012). PUCK: An automated prompting system for smart environments. Personal & Ubiquitous Computing, 16(7), 859–873.

    Article  Google Scholar 

  • Dawadi, P., Parsey, C., Schneider, M., Schmitter-Edgecombe, M., & Cook, D. (2011). An approach to cognitive assessment in smart homes. Proceedings of the 2011 Workshop on Data Mining for Medicine and Healthcare (pp. 56–59).

    Google Scholar 

  • Ernst, R. L., & Hay, J. W. (1994). The US economic and social costs of Alzheimer’s disease revisited. American Journal of Public Health, 84(8), 1261–1264.

    Article  PubMed  Google Scholar 

  • Farias, S. T., Mungas, D., Reed, B. R., Harvey, D. H., Cahn Weiner, D., & Decarli, C. (2006). MCI is associated with deficits in everyday living. Alzheimer’s Disease and Associated Disorders, 20(4), 217–223.

    Article  Google Scholar 

  • Graafmans, J. A. M., Fozard, J. L., Rietsema, J., van Berlo, A., & Bouma, H. (1996). Gerontechnology: Matching the technological environment to the needs and capacities of the elderly. In K. A. Brookhuls, C. Weikert, J. Moraal, & D. de Waard (Eds.), Aging and human factors (pp. 19–30). Haren, The Netherlands: University of Groningen, Traffic Research Centre.

    Google Scholar 

  • Greber, C., Ziviani, J., & Rodger, S. (2007). The four quadrant model of facilitated learning: A clinically based action research project. Australian Occupational Therapy Journal, 54(2), 149–152.

    Article  Google Scholar 

  • Gross, J. (2007, August 14). A grass-roots effort to grow old at home. The New York Times. Retrieved from http://www.nytimes.com

  • Hewitt, R., & Hon, P. (2007, May). Speech at long-term conditions alliance annual conference, Department of Health. Retrieved from http://webarchive.nationalarchives.gov.uk/+/www.dh.gov.uk/en/MediaCentre/Speeches/DH_074812

  • Hoey, J., Von Bertoldi, A., Craig, T., Poupart, P., & Mihailidis, A. (2010). Automated hand washing assistance for persons with dementia using video and a partially observable Markov ­decision process. Computer Vision and Image Understanding, 114(5), 503–519. doi:10.1016/j.cviu.2009.06.008.

    Article  Google Scholar 

  • Hsu, H.-H., & Chen, C.-C. (2010). RFID-based human behavior modeling and anomaly detection for elderly care. Mobile Information Systems, 6(4), 341–354. doi:10.3233/MIS-2010-0107.

    Google Scholar 

  • Hume, K., & Odom, S. (2007). Effects of an individual work system on the independent functioning of students with autism. Journal of Autism and Developmental Disorders, 37(6), 1166–1180. doi:10.1007/s10803-006-0260-5.

    Article  PubMed  Google Scholar 

  • Jakkula, V., & Cook, D. J. (2008). Anomaly detection using temporal data mining in a smart home environment. Methods of Information in Medicine, 47(1), 70–75. doi:10.3414/ME9103.

    PubMed  Google Scholar 

  • Kang, H. G., Mahoney, D. F., Hoening, H., Hirth, V. A., Bonato, P., Hajjar, I., et al. (2010). In situ monitoring of health in older adults: Technologies and issues. Journal of American Geriatrics Society, 58(8), 1579–1586. doi:10.1111/j.1532-5415.2010.02959.x.

    Article  Google Scholar 

  • Kaushik, P., Intille, S., & Larson, K. (2008). User-adaptive reminders for home-based medical tasks: A case study. Methods of Information in Medicine, 47(3), 203–207. doi:10.3414/ME9111.

    PubMed  Google Scholar 

  • Kaye, J. (2008). Home based technologies: A new paradigm for conducting dementia prevention trials. Alzheimer’s & Dementia, 4, S60–S66. doi:10.1016/j.jalz.2007.10.003.

    Article  Google Scholar 

  • Kraskowsky, L. H., & Finlayson, M. (2001). Factors affecting older adults’ use of adaptive equipment: Review of the literature. American Journal of Occupational Therapy, 55(3), 303–310.

    Article  PubMed  Google Scholar 

  • Lawton, M. P. (1998). Future society and aging. In J. Graafmans, V. Taipale, & N. Charness (Eds.), Gerontechnology: A sustainable investment in the future (pp. 12–22). Amsterdam, Holland: IOS Press.

    Google Scholar 

  • Li, K.-L., Huang, H.-K., Tian, S.-F., & Xu, W. (2003). Improving one-class SVM for anomaly detection. Proceedings of the International Conference on Machine Learning and Cybernetics (Vol. 5, pp. 3077–3081), Xi’an, China.

    Google Scholar 

  • Lotfi, A., Langensiepen, C., Mahmoud, S. M., & Akhlaghinia, M. J. (2012). Smart homes for the elderly dementia sufferers: Identification and prediction of abnormal behavior. Journal of Ambient Intelligence and Humanized Computing, 3(3), 205–218.

    Article  Google Scholar 

  • Lundell, J., Hayes, T. L., Vurgun, S., Ozertem, U., Kimel, J., Kaye, J., et al. (2007). Continuous activity monitoring and intelligent context prompting to improve medication adherence. Proceedings of the IEEE International Conference on Engineering in Medicine and Biology Society, 2007, 6286–6289.

    Google Scholar 

  • Mahoney, D. (2004). Linking home care and the workplace through innovative wireless technology: The Worker Interactive Networking (WIN) project. Home Health Care Manage Practice, 16(5), 417–428.

    Article  Google Scholar 

  • Mahoney, D. F., Mahoney, E., & Liss, E. (2009). Outcomes from aging in place with “ATEASE” automated technology for elder assessment, safety, and environmental monitoring. Gerontechnology, 8(1), 11–25.

    Article  Google Scholar 

  • Mihaildis, A., Fernie, G. R., & Barbenel, J. C. (2001). The use of artificial intelligence in the design of an intelligent cognitive orthosis for people with dementia. Assistive Technology, 13(1), 23–39.

    Article  Google Scholar 

  • Moncrieff, S., Venkatesh, S., & West, G. (2008). Dynamic privacy assessment in a smart house environment using multimodal sensing. ACM Transactions on Multimedia Computing, Communications, and Applications, 5(2), 10–27. doi:10.1145/1413862.1413863.

    Article  Google Scholar 

  • Nelson, R. C., & Amin, M. A. (1990). Falls in the elderly. Emergency Medicine Clinics of North America, 8(2), 309–324.

    PubMed  Google Scholar 

  • NIST. (2012). IEEE P1451: Draft standard for a smart transducer interface for sensors and actuators. Retrieved from Ieee1451.nist.gov/intro.htm

  • OGC. (2012). Sensor model language (SensorML). Retrieved from www.opengeospatial.org/standards/sensorml

  • Parsey, C., Dawadi, P., Schmitter-Edgecombe, M., & Cook, D. (2011). Measures of everyday functioning in a smart environment: An evaluation of direct observation and data mining ­techniques. Presented at the Festival of International Conferences on Caregiving, Disability, Aging and Technology, Toronto, Canada.

    Google Scholar 

  • Penhale, B., & Manthorpe, J. (2001). Using electronic aids to assist people with dementia. Nursing and Resident Care, 3(12), 586–589.

    Google Scholar 

  • Pollack, M. E. (2005). Intelligent technology for an aging population: The use of AI to assist elders with cognitive impairment. AI Magazine, 26(2), 9–24.

    Google Scholar 

  • Rashidi, P., Cook, D. J., Holder, L. B., & Schmitter-Edgecombe, M. (2011). Discovering activities to recognize and track in a smart environment. IEEE Transactions on Knowledge and Data Engineering, 23, 527–539. doi:10.1109/TKDE.2010.148.

    Article  PubMed  Google Scholar 

  • Rothman, A. J., Baldwin, A. S., & Hertel, A. W. (2004). Self-regulation and behavior change: Disentangling behavioral initiation and behavioral maintenance. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of self-regulation: Research, theory, and applications (pp. 130–148). New York, NY: Guilford Press.

    Google Scholar 

  • Rudary, M., Singh, S., & Pollack, M. E. (2004). Adaptive cognitive orthotics: Combining reinforcement learning and constraint-based temporal reasoning. Proceedings of the 21st International Conference on Machine Learning (pp. 719–726).

    Google Scholar 

  • Salzhauer, A. (2005, November). Is there a patient in the house? Harvard Business Review, 32.

    Google Scholar 

  • Schmitter-Edgecombe, M., Parsey, C., & Cook, D. (2011). Cognitive correlates of functional performance in older adults: Comparison of self-report, direct observation and performance-based measures. Journal of the International Neuropsychological Society, 17(5), 853–864. doi:10.1017/S1355617711000865.

    Article  PubMed  Google Scholar 

  • Schmitter-Edgecombe, M., Woo, E., & Greeley, D. (2009). Characterizing multiple memory deficits and their relation to everyday functioning in individuals with mild cognitive impairment. Neuropsychology, 23(2), 168–177. doi:10.1037/a0014186.

    Article  PubMed  Google Scholar 

  • Seelye, A. M., Howieson, D. B., Wild, K., Sauceda, L. R., & Kaye, J. A. (2009). Living well with MCI: Behavioral interventions for older adults with mild cognitive impairment. In R. Brougham (Ed.), New directions in aging research: Health and cognition (pp. 57–74). New York, NY: Nova Science Publishers, Inc.

    Google Scholar 

  • Seelye, A. M., Schmitter-Edgecombe, M., Das, B., & Cook, D. Using cognitive rehabilitation theory to inform the development of smart prompting technologies. Manuscript submitted for publication.

    Google Scholar 

  • Seelye, A. M., Smith, A., Schmitter-Edgecombe, M., & Cook, C. J. (2010, October). Cueing technologies for assisting persons with mild cognitive impairment in IADL completion in an experimenter-­assisted smart environment. Presented at the 30th annual meeting of the National Academy of Neuropsychology, Vancouver, BC.

    Google Scholar 

  • Singla, G., Cook, D. J., & Schmitter-Edgecombe, M. (2009). Tracking activities in complex settings using smart environment technologies. International Journal of BioSciences, Psychiatry and Technology, 1(1), 25–35.

    Google Scholar 

  • Singla, G., Cook, D. J., & Schmitter-Edgecombe, M. (2010). Recognizing independent and joint activities among multiple residents in smart environments. Journal of Ambient Intelligence and Humanized Computing, 1, 57–63.

    Article  PubMed  Google Scholar 

  • Skelton, D. A., & Dinan, S. M. (1999). Exercise for falls management: Rationale for an exercise programme aimed at reducing postural instability. Physiological Theory and Practice, 15(2), 105–120.

    Article  Google Scholar 

  • St. John, P. D., & Montgomery, P. R. (2010). Cognitive impairment and life satisfaction in older adults. International Journal of Geriatric Psychiatry, 25, 814–821.

    Article  PubMed  Google Scholar 

  • Stanley, K. G., & Osgood, N. D. (2011). The potential of sensor-based monitoring as a tool for health care, health promotion, and research. Annals of Family Medicine, 9(4), 296–298. doi:10.1370/afm.1292.

    Article  PubMed  Google Scholar 

  • Thielke, S., Harniss, M., Thompson, H., Patel, S., Demiris, G., & Johnson, K. (2012). Maslow’s hierarchy of human needs and the adoption of health-related technologies for older adults. Ageing International, 37(4), 470–488.

    Article  Google Scholar 

  • Vincent, G., & Velkoff, K. (2010). The next four decades: The older population in the United States. U.S. Census Bureau.

    Google Scholar 

  • Vitaliano, P., Echeverria, D., Yi, J., Phillips, P., Young, H., & Siegler, I. (2005). Psychophysiological mediators of caregiver stress and differential cognitive decline. Psychology and Aging, 20(3), 402–411. doi:10.1037/0882-7974.20.3.402.

    Article  PubMed  Google Scholar 

  • World Health Organization. (2008). Primary health care now more than ever. The World Health report. Retrieved from http://www.who.int/whr/2008/08_overview_en.pdf

  • ZigBee Alliance. (2012). ZigBee standards overview. Retrieved from www.zigbee.org/Standards/Overview.aspx

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Acknowledgments

This work was partially supported by grants from the Life Science Discovery Fund of Washington State, NIH NIBIB (Grant R01-EB009675), NSF (Grant DGE-0900781), and the Alzheimer’s Association.

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Correspondence to Maureen Schmitter-Edgecombe PhD .

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Schmitter-Edgecombe, M., Seelye, A., Cook, D.J. (2013). Technologies for Health Assessment, Promotion, and Assistance: Focus on Gerontechnology. In: Randolph, J. (eds) Positive Neuropsychology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6605-5_8

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