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Innovations

Aging and technology: understanding the issues and creating a base for technology designers

Pages 258-283 | Received 02 Dec 2020, Accepted 11 Jan 2021, Published online: 13 Apr 2021

References

  • “United Nations Population Division, Department of Economic and Social Affairs.” Accessed March 26, 2021. https://www.un.org/en/development/desa/population/events/other/10/index.asp.
  • Bouma H, Graafmans JAM. Gerontechnology. Amsterdam: IOS Press; 1992.
  • Knipscheer CPM. Interdependency among the generations within the family: a sociological approach. Gerontechnology. 1992;3:39.
  • Maier HR. What constitutes a good literature review and why does its quality matter? Environ Model Softw. 2013;43:3–4.
  • Parsons K, Surprenant A, Tracey A-M, et al. Community-dwelling older adults with memory loss. Can Fam Physician. 2013;59(3):278–285.
  • Burns PC. Wayfinding errors while driving. J Environ Psychol. 1998;18(2):209–217.
  • Bryden KJ, Charlton JL, Oxley JA, et al. Self-reported wayfinding ability of older drivers. Accid Anal Prev. 2013;59:277–282.
  • Anstey KJ, Wood J. Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life. Neuropsychology. 2011;25(5):613–621.
  • Mallon K, Wood J. Occupational therapy assessment of open-road driving performance: validity of directed and self-directed navigational instructional components. Am J Occup Ther. 2003;58(3):279–286.
  • Wood JM, Anstey KJ, Lacherez PF, et al. The on-road difficulties of older drivers and their relationship with self-reported motor vehicle crashes. J Am Geriatr Soc. 2009;57(11):2062–2069.
  • Commissaris CJ, Verhey FR, Jr, Ponds RW, et al. Public education about normal forgetfulness and dementia: importance and effects. Patient Educ Couns. 1994;24(2):109–115.
  • Blazer DG, Hays JC, Fillenbaum GG, et al. Memory complaint as a predictor of cognitive decline: a comparison of African American and White elders. J Aging Health. 1997;9(2):171–184.
  • Mol M, Carpay M, Ramakers I, et al. The effect of perceived forgetfulness on quality of life in older adults; a qualitative review. Int J Geriatr Psychiatry. 2007;22(5):393–400.
  • Geerlings MI, Jonker C, Bouter LM, et al. Association between memory complaints and incident Alzheimer's disease in elderly people with normal baseline cognition. Am J Psychiatry. 1999;156(4):531–537.
  • Jonker C, Geerlings MI, Schmand B. Are memory complaints predictive for dementia? A review of clinical and population-based studies. Int J Geriat Psychiatry. 2000;15(11):983–991.
  • Hughes CP, Berg L, Danziger WL, et al. A new clinical scale for the staging of dementia. Br J Psychiatry. 1982;140(6):566–572.
  • Unverzagt FW, Gao S, Baiyewu O, et al. Prevalence of cognitive impairment: data from the Indianapolis study of health and aging. Neurology. 2001;57(9):1655–1662.
  • Cipriani G, Lucetti C, Nuti A, et al. Wandering and dementia. Psychogeriatrics. 2014;14(2):135–142.
  • Alzheimer’s Association. 7 Stages of Alzheimer’s & symptoms | Alzheimer’s Association [Online] [cited 2015 Jan 22]. Available from: http://www.alz.org/alzheimers_disease_stages_of_alzheimers.asp#stage1.
  • Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–186.
  • Salthouse T. A theory of cognitive aging. Amsterdam: Elsevier; 2000.
  • Seidler RD, Bernard JA, Burutolu TB, et al. Motor control and aging: Links to age-related brain structural, functional, and biochemical effects. Neurosci Biobehav Rev. 2010;34(5):721–733.
  • Stelmach GE, Nahom A. Cognitive-motor abilities of the elderly driver. Hum Factors. 1992;34(1):53–65.
  • Olson PL, Sivak M. Perception-response time to unexpected roadway hazards. Hum Factors. 1986;28(1):91–96.
  • Gottsdanker R. Age and simple reaction time. J Gerontol. 1982;37(3):342–348.
  • Stelmach GE, Goggin NL, Garcia-Colera A. Movement specification time with age. Exp Aging Res. 1987;13(1–2):39–46.
  • Simon JR, Pouraghabagher AR. The effect of aging on the stages of processing in a choice reaction time task. J Gerontol. 1978;33(4):553–561.
  • Ball K, Owsley C. Identifying correlates of accident involvement for the older driver. Hum Factors. 1991;33(5):583–595.
  • Miller, Denver J, John E Morley. Attitudes of Physicians toward Elderly Drivers and Driving Policy. J Am Geriatr Soc. 1993;41(7):722–724.
  • Shinar D. Driver visual limitations diagnosis and treatment final report, contract DOT-HS-5- 1275, Institute for Research in Public Safety, Bloomington, Ind; 1977.
  • Gabriel Z, Bowling A. Quality of life from the perspectives of older people. Ageing Soc. 2004;24(5):675–691.
  • Yardley L, Donovan-Hall M, Francis K, et al. Older people's views of advice about falls prevention: a qualitative study. Health Educ Res. 2006;21(4):508–517.
  • Lord SR, Sherrington C, Menz HB, et al. Falls in older people: risk factors and strategies for prevention. Cambridge (UK): Cambridge University Press; 2007.
  • Yardley L, Donovan-Hall M, Francis K, et al. Attitudes and beliefs that predict older people's intention to undertake strength and balance training. J Gerontol B Psychol Sci Soc Sci. 2007;62(2):P119–P125.
  • Carter ND, Kannus P, Khan KM. Exercise in the prevention of falls in older people: a systematic literature review examining the rationale and the evidence. Sports Med. 2001;31(6):427–438.
  • Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. In: Cochrane database of systematic reviews. Hoboken (NJ): John Wiley & Sons, Ltd.; 2009. https://www.cochranelibrary.com/about/about-cochrane-library
  • Campbell VA, Crews JE, Moriarty DG, et al. Surveillance for sensory impairment, activity limitation, and health-related quality of life among older adults – United States, 1993–1997 [Online] [cited 2015 Sep 8]. Available from: http://origin.glb.cdc.gov/mmwR/preview/mmwrhtml/ss4808a6.html.
  • DeLoss DJ, Watanabe T, Andersen GJ. Improving vision among older adults: behavioral training to improve sight. Psychol Sci. 2015;26(4):456–466.
  • Chou K-L. Combined effect of vision and hearing impairment on depression in older adults: Evidence from the English Longitudinal Study of Ageing. J Affect Disord. 2008;106(1–2):191–196.
  • Olphert W, Damodaran L, Balatsoukas P, et al. Process requirements for building sustainable digital assistive technology for older people. J Assist Technol. 2009;3(3):4–13.
  • Pratt SR, Kuller L, Talbott EO, et al. Prevalence of hearing loss in Black and White elders: results of the cardiovascular health study. J Speech Lang Hear Res. 2009;52(4):973–989.
  • Helfer KS, Wilber LA. Hearing loss, aging, and speech perception in reverberation and noise. J Speech Hear Res. 1990;33(1):149–155.
  • Crews JE, Campbell VA. Vision impairment and hearing loss among community-dwelling older Americans: implications for health and functioning. Am J Public Health. 2004;94(5):823–829.
  • Elble RJ. Tremor in ostensibly normal elderly people. Mov Disord. 1998;13(3):457–464.
  • Chester JG, Rudolph JL. Vital signs in older patients: age-related changes. J Am Med Dir Assoc. 2011;12(5):337–343.
  • Flu & People 65 Years and Older. CDC. (2021, February 10). https://www.cdc.gov/flu/highrisk/65over.htm
  • Visvanathan R. Under-nutrition in older people: a serious and growing global problem! J Postgrad Med. 2003;49(4):352.
  • Sullivan DH, Bopp MM, Roberson PK. Protein-energy undernutrition and life-threatening complications among the hospitalized elderly. J Gen Intern Med. 2002;17(12):923–932.
  • Wenger GC, Davies R, Shahtahmasebi S, et al. Social isolation and loneliness in old age: review and model refinement. Ageing Soc. 1996;16(3):333–358.
  • Trout DL. The role of social isolation in suicide. Suicide Life Threat Behav. 1980;10(1):10–23.
  • Wiley J, Sung J, Abowd G. The message center: enhancing elder communication. In CHI ′06 Extended Abstracts on Human Factors in Computing Systems (Montréal, Québec, Canada, April 22–27, 2006). CHI ′06. New York (NY): ACM Press; 2006. p. 1523–15288.
  • Homer AC, Gilleard C. Abuse of elderly people by their carers. BMJ. 1990;301(6765):1359–1362.
  • Pillemer K, Finkelhor D. The prevalence of elder abuse: a random sample survey. Gerontologist. 1988;28(1):51–57.
  • Brandl B. Elder abuse detection and intervention: a collaborative approach. New York: Springer; 2007.
  • Minichiello V, Browne J, Kendig H. Perceptions and consequences of ageism: views of older people. Ageing Soc. 2000;20(3):253–278.
  • Rowe M, Lane S, Phipps C. CareWatch: a home monitoring system for use in homes of persons with cognitive impairment. Top Geriatr Rehabil. 2007;23(1):3–8.
  • Desai AK, Grossberg GT. Diagnosis and treatment of Alzheimer's disease. Neurology. 2005;64(12 Suppl 3):S34–S39.
  • Shumaker SA, Ockene JK, Riekert KA. The handbook of health behavior change. Third Edition. New York (NY): Springer Publishing Company; 2008.
  • Hutchison LC, Jones SK, West DS, et al. Assessment of medication management by community-living elderly persons with two standardized assessment tools: a cross-sectional study. Am J Geriatr Pharmacother. 2006;4(2):144–153.
  • National Institute on Aging. Translating research into action: Go4Life Month promotes exercise. National Institute on Aging; 2015 August 31 [Online] [cited 2015 Oct 2015]. Available from: https://www.nia.nih.gov/research/blog/2015/08/translating-research-action-go4life-month-promotes-exercise.
  • Dishman RK. Motivating older adults to exercise. South Med J. 1994;87:S79–S82.
  • Flint SJ, Smith KW, Rossi DG. An evaluation of mature driver performance. Presented at the Fifth International Conference on mobility and transport for elderly and disabled persons, Stockholm, Sweden; 1991.
  • Goldsmith TC. On the programmed/non-programmed aging controversy. Biochemistry. 2012;77(7):729–732.
  • Satariano WA, Scharlach AE, Lindeman D. Aging, place, and technology: toward improving access and wellness in older populations. J Aging Health. 2014;26(8):1373–1389.
  • Parra C. Information technology for active ageing: a review of theory and practice. FNT Human Comput Interact. 2014;7(4):351–444.
  • Consolvo S, Roessler P, Shelton BE, et al. Technology for care networks of elders. IEEE Pervasive Comput. 2004;3(2):22–29.
  • Strauss AL. Social organization of medical work. Piscataway (NJ): Transaction Publishers; 1997.
  • van Bronswijk JEMH. Persuasive GERONtechnology: an introduction. In: IJsselsteijn WA, de Kort YAW, Midden C, Eggen B, van den Hoven E, editors. Persuasive technology. Berlin, Heidelberg: Springer; 2006. p. 183–186.
  • Bee Lau T. Assistive technologies for physical and cognitive disabilities. Hershey (PA): IGI Global; 2014.
  • Judd N. Assistive technology – devices to help with everyday living [Online] [cited 2015 Mar 31]. Available from: http://www.alzheimers.org.uk/site/scripts/documents_info.php?documentID=109.
  • de Joode E, van Heugten C, Verhey F, et al. Efficacy and usability of assistive technology for patients with cognitive deficits: a systematic review. Clin Rehabil. 2010;24(8):701–714.
  • Pollack ME. Intelligent technology for an aging population: the use of AI to assist elders with cognitive impairment. AI Mag. 2005;26(2):9–24.
  • Roberts D, Beech R. Assistive technology and older people: SCIE Research Brieifing No. 28. Research Briefings, Social Care Institute for Excellence, London; 2008.
  • McCreadie C, Tinker A. The acceptability of assistive technology to older people. Ageing Soc. 2005;25(01):91–110.
  • Miljanović B, Dana R, Sullivan DA, et al. Impact of dry eye syndrome on vision-related quality of life. Am J Ophthalmol. 2007;143(3):409–415.e2.
  • Fogg BJ. Persuasive technology: using computers to change what we think and do. Ubiquity. 2002;2002:2.
  • Atkinson BMC. Captology: a critical review. In: IJsselsteijn WA, de Kort YAW, Midden C, Eggen B, van den Hoven, E, editors. Persuasive technology. Berlin, Heidelberg: Springer; 2006. p. 171–182.
  • Intille SS. A new research challenge: persuasive technology to motivate healthy aging. IEEE Trans Inf Technol Biomed. 2004;8(3):235–237.
  • Fogg B. Creating persuasive technologies: an eight-step design process. In Proceedings of the 4th International Conference on Persuasive Technology, New York, NY, USA; 2009. p. 44:1–44:6.
  • Fogg B. A behavior model for persuasive design. In Proceedings of the 4th International Conference on Persuasive Technology, New York, NY, USA, 2009. p. 40:1–40:7.
  • Consolvo S, McDonald DW, Landay JA. Theory-driven design strategies for technologies that support behavior change in everyday life. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, 2009. p. 405–414.
  • Locke EA, Latham GP. Building a practically useful theory of goal setting and task motivation: a 35-year odyssey. Am Psychol. 2002;57(9):705–717.
  • Bradley EH, Curry LA, Devers KJ. Qualitative data analysis for health services research: developing taxonomy, themes, and theory. Health Serv Res. 2007;42(4):1758–1772.
  • Cash M. Assistive technology and people with dementia. Rev Clin Gerontol. 2003;13(4):313–319.
  • Philipose M, Fishkin KP, Perkowitz M, et al. Inferring activities from interactions with objects. IEEE Pervasive Comput. 2004;3(4):50–57.
  • Bharucha AJ, Anand V, Forlizzi J, et al. Intelligent assistive technology applications to dementia care: current capabilities, limitations, and future challenges. Am J Geriatr Psychiatry. 2009;17(2):88–104.
  • Gaddam A, Mukhopadhyay SC, G. Sen G. Trial amp; experimentation of a smart home monitoring system for elderly. In 2011 IEEE Instrumentation and Measurement Technology Conference (I2MTC); 2011; Hangzhou, China. p. 1–6.
  • Ojo A, Chatterjee S, Neighbors HW, et al. OH-BUDDY: mobile phone texting based intervention for diabetes and oral health management. In 2015 48th Hawaii International Conference on System Sciences (HICSS), 2015; Hawaii, United States. p. 803–813.
  • Miskelly F. Electronic tracking of patients with dementia and wandering using mobile phone technology. Age Ageing. 2005;34(5):497–499.
  • Wan L, Müller C, Wulf V, et al. Addressing the subtleties in dementia care: pre-study & evaluation of a GPS monitoring system. In Proceedings of the 32Nd Annual ACM Conference on Human Factors in Computing Systems, New York, NY, USA; 2014. p. 3987–3996.
  • Faria S, Fernandes TR, Perdigoto FS. Mobile web server for elderly people monitoring. ISCE 2008. IEEE International Symposium on consumer electronics; 2008; Vilamoura, Portugal, p. 1–4.
  • Sposaro F, Danielson J, Tyson G. iWander: an Android application for dementia patients. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2010; Buenos Aires Sheraton Hotel, Buenos Aires. p. 3875–3878.
  • Kearns WD, Algase D, Moore DH, et al. Ultra wideband radio: A novel method for measuring wandering in persons with dementia. Gerontechnology. 2008;7(1):48–57.
  • Frank Lopresti E, Mihailidis A, Kirsch N. Assistive technology for cognitive rehabilitation: State of the art. Neuropsychol Rehabil. 2004;14(1-2):5–39.
  • Wan J, Byrne C, O’Hare GMP, et al. OutCare: supporting dementia patients in outdoor scenarios. In: Setchi R, Jordanov I, Howlett RJ, Jain LC, editors. Knowledge-based and intelligent information and engineering systems. Berlin (Heidelberg): Springer; 2010. p. 365–374.
  • Liao L, Patterson DJ, Fox D, et al. Learning and inferring transportation routines. Artif. Intell. 2007;171(5–6):311–331.
  • Patterson D, Etzioni O, Fox D, Kautz H. The activity compass. In: Proc. of UbiCog 2002: First International Workshop on Ubiquitous Computing for Cognitive Aids, Gothenberg, Sweden; 2002.
  • Kim S, Dey AK. Simulated augmented reality windshield display as a cognitive mapping aid for elder driver navigation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA; 2009. p. 133–142.
  • Alsaqer M, Hilton B. Indirect Wayfinding navigation system for the elderly. AMCIS 2015 Proc. 2015. https://aisel.aisnet.org/amcis2015/HealthIS/
  • Hervas R, Bravo J, Fontecha J. An assistive navigation system based on augmented reality and context awareness for people with mild cognitive impairments. IEEE J Biomed Health Inform. 2014;18(1):368–374.
  • Carmien S, Dawe M, Fischer G, et al. Socio-technical environments supporting people with cognitive disabilities using public transportation. ACM Trans Comput-Hum Interact. 2005;12(2):233–262.
  • Vemuri S, Schmandt C, Bender W. iRemember: a personal, long-term memory prosthesis. In Proceedings of the 3rd ACM Workshop on continuous archival and retrival of personal experences, New York, NY, USA, 2006. p. 65–74.
  • Vemuri S, Schmandt C, Bender W, et al. An audio-based personal memory aid. In: Davies N, Mynatt ED, Siio I, editors. UbiComp 2004: ubiquitous computing. Berlin, Heidelberg: Springer, 2004. p. 400–417.
  • Anguera JA, Boccanfuso J, Rintoul JL, et al. Video game training enhances cognitive control in older adults. Nature. 2013;501(7465):97–101.
  • Jimison H, Pavel M. Embedded assessment algorithms within home-based cognitive computer game exercises for elders. In 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. EMBS ’06; 2006. p. 101–104.
  • Tong T, Chignell M. Designing game-based cognitive assessments for elderly adults. In Proceedings of the First International Conference on Gameful Design, Research, and Applications, New York, NY, USA, 2013. p 127–130.
  • Lumos Labs (online brain traning game). Home – lumosity [Online] [cited 2015 Sep 22]. Available from: http://www.lumosity.com/app/v4/dashboard.
  • Beigl M. MemoClip: a location-based remembrance appliance. Pers Ubiquitous Comput. 2000;4(4):230–233.
  • Pollack ME, Brown L, Colbry D, et al. Autominder: an intelligent cognitive orthotic system for people with memory impairment. Robot Auton Syst. 2003;44(3–4):273–282.
  • Wan D. Magic medicine cabinet: a situated portal for consumer healthcare. In: Gellersen H-W, editor. Handheld and ubiquitous computing. Berlin, Heidelberg: Springer; 1999. p. 352–355.
  • de Oliveira R, Cherubini M, Oliver N. MoviPill: improving medication compliance for elders using a mobile persuasive social game. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing, New York, NY, USA; 2010. p. 251–260.
  • Silva JM, Mouttham A, Saddik AE. UbiMeds: a mobile application to improve accessibility and support medication adherence, In Proceedings of the 1st ACM SIGMM International Workshop on Media Studies and Implementations that Help Improving Access to Disabled Users, New York, NY, USA; 2009. p. 71–78.
  • Morris A, Donamukkala R, Kapuria A, et al. A robotic walker that provides guidance. In IEEE International Conference on Robotics and Automation, 2003, proceedings, ICRA ’03; 2003. vol. 1. p. 25–30.
  • Abou Haidar G, Achkar R, Maalouf R, et al. Smart Walker. In 2014 International Conference on Future Internet of Things and Cloud (FiCloud), Bahrain; 2014. p. 415–419.
  • Ko E, Ju JS, Kim EY, et al. An intelligent wheelchair to enable mobility of severely disabled and elder people. In Digest of Technical Papers International Conference on Consumer Electronics, 2009, ICCE ’09, Las Vegas, NV; 2009. p. 1–2.
  • Sawasdee S, Pumrin S. Elderly care notification system using hand posture recognition. In 2014 Fourth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), Bangkok, Thailand; 2014. p. 304–309.
  • Ding J-R, Sheng Y-S, Lin Y-T, et al. An automatic speech broadcast system for mobility disabled elders based on RSS network news. In 2010 Fifth International Conference on Digital Telecommunications (ICDT), Athens, Greece; 2010. p. 82–85.
  • Rodriguez MD, Roa JR, Moran AL, et al. Persuasive strategies for motivating elders to exercise. In 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), San Diego, CA; 2012. p. 219–223.
  • Au LK, Batalin M, Jordan B, Xu C, Bui A. A. T, Dobkin B, Kaiser WJ, Demonstration of WHI-FIT: a wireless-enabled cycle restorator. In Wireless Health 2010, New York, NY, USA; 2010. p. 190–191.
  • Postolache O, Girao PS, Ribeiro M, et al. Enabling telecare assessment with pervasive sensing and Android OS smartphone. In 2011 IEEE International Workshop on Medical Measurements and Applications Proceedings (MeMeA), Bari, Italy; 2011. p. 288–293.
  • Culhane KM, O'Connor M, Lyons D, et al. Accelerometers in rehabilitation medicine for older adults. Age Ageing. 2005;34(6):556–560.
  • Hristoforou E, Reilly RE. Displacement sensors using soft magnetostrictive alloys. IEEE Trans Magn. 1994;30(5):2728–2733.
  • Zhang Y-N, Ning H, Bai J, et al. Elderly safety early-warning system based on android mobile phones. In 2014 10th International Conference on Natural Computation (ICNC), Xiamen, China; 2014. p. 1126–1130.
  • Chen J, Kwong K, Chang D, et al. Wearable sensors for reliable fall detection. In 2005. 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. EMBS 2005, Shanghai, China; 2005, p. 3551–3554.
  • Degen T, Jaeckel H, Rufer M, et al. SPEEDY: a fall detector in a wrist watch. In Seventh IEEE International Symposium on Wearable Computers, 2003 Proceedings; 2003. p. 184–187.
  • Lee T, Mihailidis A. An intelligent emergency response system: preliminary development and testing of automated fall detection. J Telemed Telecare. 2005;11(4):194–198.
  • Lan M, Nahapetian A, Vahdatpour A, et al. SmartFall: an automatic fall detection system based on subsequence matching for the SmartCane. In Proceedings of the Fourth International Conference on Body Area Networks, ICST, Brussels, Belgium, Belgium; 2009. Vol. 8. p.1–8.
  • Han C, Wu K, Wang Y, et al. WiFall: device-free fall detection by wireless networks. In 2014 Proceedings IEEE INFOCOM, Toronto, Canada; 2014. p. 271–279.
  • Terroso M, Freitas R, Gabriel J, et al. Active assistance for senior healthcare: a wearable system for fall detection. In 2013 8th Iberian Conference on Information Systems and Technologies (CISTI), Lisboa, Portugal; 2013. p. 1–6.
  • Bourke AK, van de Ven PWJ, Chaya AE, et al. The design and development of a long-term fall detection system incorporated into a custom vest for the elderly. In 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. EMBS 2008, Vancouver, Canada; 2008. p. 2836–2839.
  • Singhal H, Kaur A, Yadav R. The development of an intelligent aid for blind and old people. in 2013 1st International Conference on Emerging Trends and Applications in Computer Science (ICETACS) Shillong, India; 2013. p. 182–186.
  • Yonekawa K, Yonezawa T, Nakazawa J, et al. FASH: detecting tiredness of elders. In 2009 Sixth International Conference on Networked Sensing Systems (INSS), Pittsburgh, PA, USA; 2009. p. 1–1.
  • Ferreira BN, Guimaraes V, Sereno Ferreira H. Smartphone based fall prevention exercises. In 2013 IEEE 15th International Conference on e-Health Networking, Applications Services (Healthcom), Lisbon, Portugal; 2013. p. 643–647.
  • Mihailidis A, Fernie GR, Barbenel JC. The use of artificial intelligence in the design of an intelligent cognitive orthosis for people with dementia. Assist Technol. 2001;13(1):23–39.
  • Tee K, Moffatt K, Findlater L, et al. A visual recipe book for persons with language impairments. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA; 2005. p. 501–510.
  • Tran QT, Mynatt ED, Calcaterra G. Using memory aid to build memory independence. In: Jacko JA, editor. Human-computer interaction. Interaction design and usability. Berlin, Heidelberg: Springer; 2007. p. 959–965.
  • Iglesias R, Ibarguren I, de Segura NG, et al. FoodManager: a cooking, eating and appliance controlling support system for the elderly. In Proceedings of the 3rd International Conference on Pervasive Technologies Related to Assistive Environments, New York, NY, USA; 2010. p. 38:1–38:6.
  • Takahashi Y, Kikuchi Y, Ibaraki T, et al. Robotic food feeder. In Proceedings of the 38th SICE Annual Conference, Morioka, Japan; 1999. p. 979–982.
  • Hervás R, Garcia-Lillo A, Bravo J. Mobile augmented reality based on the semantic web applied to ambient assisted living. In: Bravo J, Hervás R, Villarreal V, editors. Ambient assisted living. Berlin, Heidelberg: Springer; 2011. p. 17–24.
  • Hongo N, Yamamoto H, Yamazaki K. Web shopping support system for elderly people using WebRTC. In 2014 16th International Conference on Advanced Communication Technology (ICACT), Pyeong Chang, South Korea; 2014. p. 934–940.
  • Iwamura Y, Shiomi M, Kanda T, et al. Do elderly people prefer a conversational humanoid as a shopping assistant partner in supermarkets? In 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Lausanne, Switzerland; 2011. p. 449–457.
  • Marin-Hernandez A, de Jesus Hoyos-Rivera G, Garcia-Arroyo M, et al. Conception and implementation of a supermarket shopping assistant system. In 2012 11th Mexican International Conference on Artificial Intelligence (MICAI), Mexico; 2012. p. 26–31.
  • Ogawa H, Yonezawa Y, Maki H, et al. A mobile phone-based communication support system for elderly persons. In 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; EMBS 2007, Lyon, France; 2007. Vol. 2007. p. 3798–3801.
  • Gaddam A, Kaur K, Gupta GS, et al. Determination of sleep quality of inhabitant in a smart home using an intelligent bed sensing system. In 2010 IEEE Instrumentation and Measurement Technology Conference (I2MTC), Austin, TX; 2010. p. 1613–1617.
  • Hao T, Xing G, Zhou G. iSleep: unobtrusive sleep quality monitoring using smartphones. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, New York, NY, USA; 2013. p. 4:1–4:14.
  • Alqassim S, Ganesh M, Khoja S, et al. Sleep apnea monitoring using mobile phones. In 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom), Beijing, China; 2012. p. 443–446.
  • Song L, Wang Y, Yang J-J, et al. Health sensing by wearable sensors and mobile phones: a survey. In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom), Natal, Brazil; 2014. p. 453–459.
  • Rienzo MD, Rizzo F, Parati G, et al. A textile-based wearable system for vital sign monitoring: Applicability in cardiac patients. Computers in Cardiology, 2005, Lyon, France pp. 699–701. doi: 10.1109/CIC.2005.1588199.
  • Pioggia G, Tartarisco G, Ricci G, et al. A wearable pervasive platform for the intelligent monitoring of muscular fatigue. In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA), Cairo, Egypt; 2010. p. 132–135.
  • Hong J-H, Cha E-J, Lee T-S. A belt-type biomedical mobile device. J Korean Soc Med Inform. 2009;15(3):351.
  • Lee HJ, Lee SH, Ha K-S, et al. Ubiquitous healthcare service using Zigbee and mobile phone for elderly patients. Int J Med Inform. 2009;78(3):193–198.
  • Alexan AI, Osan AR, Oniga S. Personal assistant robot. In 2012 IEEE 18th International Symposium for Design and Technology in Electronic Packaging (SIITME), Alba Iulia, Romania; 2012. p. 69–72.
  • Chatterjee S, Byun J, Pottathil A, et al. Persuasive sensing: a novel in-home monitoring technology to assist elderly adult diabetic patients. In: Bang M, Ragnemalm EL, editors. Persuasive Technology. Design for Health and Safety. Berlin (Heidelberg): Springer; 2012. p. 31–42.
  • Hernandez Munoz LU, Woolley SI, Baber C. A mobile health device to help people with severe allergies. In Second International Conference on Pervasive Computing Technologies for Healthcare, 2008. PervasiveHealth 2008, Tampere, Finland; 2008. p. 8–10.
  • Haris N, Majid RA, Abdullah N, et al. The role of social media in supporting elderly quality daily life. In 2014 3rd International Conference on User Science and Engineering (i-USEr), Shah Alam, Malaysia; 2014. p. 253–257.
  • Eduard G, Jesus F, Monica T. Assisting support groups of patients with chronic diseases through persuasive computing. J Univers Comput Sci. 2009;15(16):3081–3100.
  • Mamykina L, Mynatt E, Davidson P, et al. MAHI: investigation of social scaffolding for reflective thinking in diabetes management. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA; 2008. p. 477–486.
  • Bouchard Ryan E, Anas AP, Beamer M, et al. Coping with age-related vision loss in everyday reading activities. Educ. Gerontol. 2003;29(1):37–54.
  • Dickinson A, Gregor P, Newell AF. Ongoing investigation of the ways in which some of the problems encountered by some dyslexics can be alleviated using computer techniques. In Proceedings of the Fifth International ACM Conference on Assistive Technologies, New York, NY, USA; 2002. p. 97–103.
  • Voice driven web Apps: introduction to the web speech API — Google web updates. Web Fundamentals [Online] [cited 2015 Sep 15]. Available from: https://developers.google.com/web/fundamentals/.
  • Nagarajan SS, Wang X, Merzenich MM, et al. Speech modifications algorithms used for training language learning-impaired children. IEEE Trans Rehabil Eng. 1998;6(3):257–268.
  • Alm N, Astell A, Ellis M, et al. A cognitive prosthesis and communication support for people with dementia. Neuropsychol. Rehabil. 2004;14(1–2):117–134.
  • Ichimura T, Mera K, Yamashita T. Construction of a dialog system with emotions for elderly persons by neural networks. In 2000 IEEE International Conference on Systems, Man, and Cybernetics, Nashville, TN; 2000; vol. 5. p. 3594–3599.
  • Hsu C-C, Chien YY. An intelligent fuzzy affective computing system for elderly living alone. In Proceedings of the Ninth International Conference on Hybrid Intelligent Systems, Shenyang, China; 2009. p. 293–297.
  • Wang D, Tan A-H. Mobile humanoid agent with mood awareness for elderly care. In 2014 International Joint Conference on Neural Networks (IJCNN), Beijing, China; 2014. p. 1549–1556.
  • Santana PC, Rodriguez MD, Gonzalez VM, et al. A web-based system to facilitate elders communication with their families living abroad. In Sixth Mexican International Conference on Computer Science, 2005, Mexico. ENC 2005; 2005. p. 18–25.
  • Chiang C-Y, Chen Y-L, Tsai P-S, et al. A video conferencing system based on WebRTC for seniors. In 2014 International Conference on Trustworthy Systems and their Applications (TSA), Taichung, Taiwan; 2014. p. 51–56.
  • Machesney D, Wexler SS, Chen T, et al. Gerontechnology companion: virtual pets for dementia patients. In Systems, Applications and Technology Conference (LISAT), 2014 IEEE Long Island, Long Island, Taichung, Taiwan; 2014. p. 1–3.

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