AI health monitoring of older adults

Demographic modelling has, for some time (e.g. "The Age of Ageing: How Demographics are Changing the Global Economy and Our World", Magnus, 2009), indicated that we are observing an increase the relative proportion of older adults in our population. This has resulted, in some instances, to an hysteria about a "silver tsunami" (a term I for one think we need to expunge from the dialogue around ageing), where the doomsayers arguments rest on the potential significant increase in health budgets that will be required to support the needs of older adults. However we absolutely "should not fear an ageing population" https://nla.gov.au/nla.obj-3154772588/view

With advances in sensing, computing and communication technologies there is the opportunity to proactively address such arguments and instead, through appropriate innovation, demonstrate that we will be able to monitor and mitigate markers of health and wellness long before an older person (indeed any of us) need to access the expensive end of healthcare.

At the upcoming Information Technology in Aged Care Conference (https://www.aciitc.com.au/itac/) we'll no doubt hear and see many of these innovative technologies. I expect many speakers and vendors will be discussing the potential use of Artificial Intelligence as an adjunct to aged health and service delivery. I thought it might be useful to think through this issue in some detail.

The proposition of leveraging artificial intelligence (AI) as a health monitoring tool emerges as both a promising and complex solution. This approach necessitates a careful exploration of not only the potential benefits but also the ethical dimensions associated with employing AI for health monitoring in aged care. The integration of AI in aged care offers significant advantages, including the potential to complement existing care provisions, enhance the quality of care, and mitigate the burden on healthcare systems and family caregivers. Notably, ethical considerations must be thoroughly addressed to ensure these technologies genuinely benefit older adults without compromising their privacy or autonomy (Ho et al., 2020).

Technology-based home monitoring, such as in-home sensors and wearables, has shown promise in managing chronic conditions, improving safety, and prolonging independence for older adults. Nearly two decades ago we kicked off the Technology Research for Independent Living project in Ireland to explore design and development of devices and data solutions to enable older adults to remain living in the communities and home sod their choice. Some lessons learning from that project can be found here: https://link.springer.com/article/10.1007/s10209-013-0308-1

This and other research has revealed the importance on focussing on adherence, privacy, and user preferences for successful implementation of technology into the home (e.g. Boot, 2019). Moreover, proposed Smart Healthcare systems, which include bio-signal measuring and web applications, have been positively received by medical professionals and are expected to be accepted by elderly users, enhancing health monitoring and control (Thaduangta et al., 2016).

More recently AI will enable us to extract greater meaning from the data captured by health monitoring technologies such as wearable devices, smart homes, and robotic systems. These tools are poised to improve life quality by offering tailored healthcare solutions, emphasising the necessity to address ethical and privacy concerns in their design and implementation (Iqbal, 2023). Furthermore, AI technology in smart home environments has been highlighted for its potential in proactive health monitoring, especially in managing conditions such as Alzheimer's, showcasing the critical role of technology-guided algorithms in deploying effective health services for the elderly (Roy, 2017).

Understanding healthcare professionals' perceptions and attitudes towards technology and AI is crucial for fostering higher levels of technology acceptance, particularly among younger, more educated, and male demographics (Choi, 2023). Voice assistive technology, for instance, significantly enhances the usability and user experience of health monitoring applications for older adults, underscoring the importance of designing user-friendly technologies (Rath & Chandna, 2021).

More recently Shinners et al. (2023) provide valuable research in this area, focusing on the experiences and perceptions of healthcare professionals regarding AI in regional and rural health districts in Australia. Their findings offer an in-depth look at the practical and conceptual challenges faced by healthcare providers in these areas, shedding light on the broader implications for AI integration in health monitoring for older adults. The study emphasizes the need for targeted training and support systems to enhance AI technology adoption and utilization, ensuring that healthcare professionals are equipped to leverage AI tools effectively in enhancing patient care (Shinners et al., 2023).

Despite the promising aspects, concerns regarding age biases and discrimination in AI applications necessitate a careful examination to mitigate potential negative impacts on the elderly population (Stypińska & Franke, 2023). The integration of Internet of Health Things (IoHT) and edge computing in remote health monitoring enhances personalized health protocols and empowers seniors to manage their health effectively, maintaining independence and well-being (Ianculescu et al., 2019).

In conclusion, leveraging AI health monitoring technology offers a path towards sustaining the health, wellness, and independence of older adults. Nonetheless, it is imperative to design these technologies with a keen eye on ethical considerations, personalisation, privacy, and accessibility to ensure they meet the diverse needs and preferences of the elderly population effectively.