BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250327T203344Z LOCATION:Frontenac Foyer DTSTART;TZID=America/New_York:20250331T164500 DTEND;TZID=America/New_York:20250331T181500 UID:HFESHCS_2025 International Symposium on Human Factors and Ergonomics i n Health Care_sess147_POST274@linklings.com SUMMARY:DH3 - Artificial Intelligence for Older Adults: A Literature Surve y on AI as an Aid for Independent Living DESCRIPTION:Poster Presentation\n\nAnt Ozok (UMBC)\n\nIntroduction and Aim s\nToday, approximately one quarter of adults above the age of 60 live ind ependently according to the Project of Art & Healing (2018). With the Baby Boomer generation currently belonging to this category and Generation X ( born 1965-1980) reaching the age milestone in the very near future, sophis ticated technologies are easier to integrate into the daily lives of the o lder adults for improving the quality of life and health resilience of the population. A highly anticipated such technology is Artificial Intelligen ce, with its wide-reaching applications also including health resilience a mong older adults. This literature search focused on the current AI based technologies and their categorization to improve health resilience and the easiness of daily routines that can contribute to the lives of older adul ts who are living independently. The independent literature search conduct ed aimed at determining the current and potential future of AI technologie s with a strong human factors emphasis on the lives of independently livin g older adults. Twelve databases were searched with the top five keywords being: Artificial intelligence, older adults, healthcare, daily routines, and health resilience. \nArtificial Intelligence for Older Adults \nDue to the relatively recent big advancements in the AI field, the literature su rvey primarily focused on articles in the field that were published betwee n 2020 and 2024. The literate so far has been analyzed and the following c ategories have been determined in the current and potential practical AI u se for the benefit of independently living older adults:\nAid to improve l ife routines: Older adults’ daily routines such as getting off the bed, ea ting, bathing, etc. while living independently are assisted by AI-integrat ed systems in the form of computers, mobile and wearables devices, and/or robotics (mentioned in 26 articles).\nAid to improve health capabilities: AI assists older adults with daily health routines and capabilities such a s taking their mediations, moving a certain amount every day, going to the bathroom regularly, etc. by reminders and other means as well as confirma tion of their completion (mentioned in 31 articles).\nEmergency detection and help: Falls, seizures, strokes and other emergencies are detected prec isely and acted upon by AI-integrated health systems with sensors (mention ed in 34 articles).\nFight dementia and cognitive decline-related problems : Older adults are aided by AI through social interactions targeting memor y decline and other ailments that can be slowed down via conversational an d visual interactions (mentioned in 19 articles).\nPreventive health issue s: AI focuses on preventing health deterioration and adverse health events such as taking action when high blood pressure or instability in movement is detected (mentioned in 23 articles). \nSample Application Areas of AI in the Daily Lives of Older Adults\nNewer technologies developed by leadin g companies, nonprofit institutions and academic outlets are already havin g a major role in monitoring, detecting issues, and offering solutions in independent living for the elderly (Capodieci et al., 2018). Roosan (2020) et al. indicated that with the increasing prevalence of AI, medication in teractions can be improved using a system that reminds adults to take thei r medications in a way that is more complete than a simple reminder, and t hese systems can work as a personalized provider for medication informatio n which can result in higher adherence rates. This study alone shows the p otential that AI systems shows in improving the lives and medical standing s of older adults when designed based on human factors rules and guideline s. Additionally, Yoo (2020) showed immense interest among older adults to use AI in their daily lives as a speaking companion helping them in their routines with the ultimate goal of reaching better quality of life. Yang e t al. (2021) saw AI as an education and training tool to improve lives and human conditions, proposing Human-Centered AI (HAI). Qian et al. (2021) i ndicated the importance of providing technology aids for older adults in b oth developed and developing countries, and produced a framework to improv e the visual and auditory capabilities of older adults using AI. Yuan et a l.’s (2020) study, while comparatively older, indicated the importance of AI interventions in facilitation and prevention of issues including diseas e, quality of life and sleep, brain injury, dementia and cancer. A feasibi lity study by Kang et al. (2021) found that the Internet of Things is a s uitable platform for adults aged 65 and older to be used as an AI platform to help with their health care, with sensors and smart sensors being able to better understand the nature of falls, ailments and other anomalies wi th the help of newer AI systems and acting and alerting accordingly. Their study also proposes the interfacing of mobile robots to the AI-supported IoT systems for better effectiveness in saving lives. According to Alharbi et al. (2023), smart fall detection systems could be developed by integra ting RFID detectors into the carpet and combined with AI and IoT to detect fall severity among independently living older adults, with almost 99% ac curacy. Similarly, in their conceptual framework, Onthoni et al. (2022) fo cused on a smart home concept with the main components of accelerometer, g yroscope, magnetometer, global positioning system, motion and temperature tracker outputs, where AI could recognize the type of action or the activi ty the older adult was engaged in with high accuracy and have the smart ho me system accordingly while also alerting for emergencies. \nThe sample ab ove from the literature survey demonstrates tremendous potential for AI to be integrated as a daily routine-specific as well as health care-specific tool in a total of five categories. The next step is to determine user at titudes towards the integration of such AI technologies into the lives of older adults in an experimental study. This literature survey proved that AI technologies to improve the daily routine-related and healthcare-relate d tasks of older adults is highly promising to improve the quality and spa n of life for older adults in independent living.\nAlharbi, Hatem A., Khul ud K. Alharbi, and Ch Anwar Ul Hassan. "Enhancing elderly fall detection t hrough IoT-enabled smart flooring and AI for independent living sustainabi lity." Sustainability 15.22 (2023): 15695.\nCapodieci, Antonio, Luca Maine tti, and Paolo Panarese. "Ambient assisted living for elderly people using smart personal assistants." 2018 International Conference on Computationa l Science and Computational Intelligence (CSCI). IEEE, 2018.\nYoo, Hyun-Si l, Eung-Kyo Suh, and Tae-Hyung Kim. "A study on technology acceptance of e lderly living alone in smart city environment: Based on AI speaker." The J ournal of Industrial Distribution & Business 11.2 (2020): 41-48.\nYuan, Fe i, Kumiko Miyazaki, and Santiago Ruiz-Navas. "An empirical analysis of AI related scientific knowledge and technologies to support elderly independe nt living." Journal of STI Policy and Management 6.2 (2021): 119-129.\nKan g, Minsoo, et al. "A Study on the Feasibility of IoT and AI-based elderly care system application." Korea Journal of Artificial Intelligence 9.2 (20 21): 15-21.\nOnthoni, Djeane Debora, and Prasan Kumar Sahoo. "Artificial-i ntelligence-assisted activities of daily living recognition for elderly in smart home." Electronics 11.24 (2022): 4129.\nRoosan, Don, et al. "Artifi cial intelligence–powered smartphone app to facilitate medication adherenc e: protocol for a human factors design study." JMIR Research Protocols 9.1 1 (2020): e21659.\nThe Foundation of Art & Healing: Fact Sheet: Loneliness and Older Adults. April 23, 2018, Last Visited: October 7, 2024. Older Ad ults Loneliness Fact Sheet - The Foundation for Art & Healing (artandheali ng.org)\nYang, Stephen JH, et al. "Human-centered artificial intelligence in education: Seeing the invisible through the visible." Computers and Edu cation: Artificial Intelligence 2 (2021): 100008.\n\nTrack: Digital Health (DH), Simulation and Education (SE), Hospital Environments (HE), Medical and Drug Delivery Devices (MDD), Patient Safety and Research Initiatives ( PS) END:VEVENT END:VCALENDAR