Edited by:
Patrick Esser, PhD, Oxford Brookes University, United Kingdom
European Review of Aging and Physical Activity is calling for submissions to our Collection on AI methodologies to support physical activity and exercise prescription in aging populations.
This collection supports and amplifies research related to SDG 3: Good Health & Well-Being.
Dr. Patrick Esser, PhD, Oxford Brookes University, UK
Dr. Patrick Esser is a Reader (UK) / Associate Professor in Sport and Rehabilitation Technology and Director for the Centre for Movement, Occupation and Rehabilitation Sciences (MOReS) at Oxford Brookes University.
Patrick has been trained in Mechanical Engineering and Medical Technology in the Netherlands. He then went on to complete his PhD in Clinical Biomechanics, during which he created an easy and objective assessment tools for measuring the quality and quantity of movement in neurological conditions.
His academic activities include research and knowledge exchange, where he leads clinical and multidisciplinary teams to develop and evaluate bespoke hard- and software solutions for real-world medical applications. In addition, Patrick is involved in developing and evaluating novel technological-based products from commercial entities.
Artificial Intelligence (AI) and its potential applications have recently received much attention in the media, with partly bold claims that it will alter ‘our’ world beyond imagination. Indeed, AI is a very powerful tool in helping humans make sense of vast multidimensional sources of information. Yet, its full power within science, healthcare, and our day-to-day lives is still to be determined. This thematic series emphasizes the potential of applying AI to design and evaluate optimal physical activity or exercise programs tailored for older adults across various settings.
Optimal physical activity or exercise-based interventions to support healthy ageing require an individual tailoring of intervention ingredients to the older person. Effective tailoring requires knowledge of individual characteristics that can be targeted for an intervention, the effects of specific interventions, and the procedures to match intervention ingredients to individual needs and preferences. Using multi-dimensional data sets, AI-based methods can be employed to develop approaches supporting individual tailoring and, hence, healthy ageing.
This thematic series will highlight the state-of-the-art progress in this area of research through specialist contributions in physical activity, exercise, and AI. We anticipate that the readership of the European Review of Aging and Physical Activity (EURAPA) and beyond will be able to use this resource to get a high-quality, peer-reviewed and informed opinion on relevant applications of AI to promote healthy ageing and gaps of knowledge that need to be addressed in due course.
There are currently no articles in this collection.
This Collection welcomes submission of research articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal.
Articles for this Collection should be submitted via our submission system, Editorial Manager. Please select the appropriate Collection title “AI tools to support the contribution of physical activity and exercise to healthy ageing" from the dropdown menu.
Articles will undergo the journal’s peer-review process and are subject to all the journal’s standard policies. Articles will be added to the Collection as they are published.
The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.