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Cognition Meets Gait: Where and How Mind and Body Weave Each Other in a Computational Psychometrics Approach in Aging

Academic Article
Publication Date:
2022
abstract:
Aging may be associated with conditions characterized by motor and cognitive alterations, which could have a detrimental impact on daily life. Although motors and cognitive aspects have always been treated as separate entities, recent literature highlights their relationship, stressing a strong association between locomotion and executive functions. Thus, designing interventions targeting the risks deriving from both components’ impairments is crucial: the dual-task represents a starting point. Although its role in targeting and decreasing difficulties in aging is well known, most interventions are focused on a single domain, proposing a vertical model in which patients emerge only for a single aspect per time during assessment and rehabilitation. In this perspective, we propose a view of the individual as a whole between mind and body, suggesting a multicomponent and multidomain approach that could integrate different domains at the same time retracing lifelike situations. Virtual Reality, thanks to the possibility to develop daily environments with engaging challenges for patients, as well as to manage different devices to collect multiple data, provides the optimal scenario in which the integration could occur. Artificial Intelligence, otherwise, offers the best methodologies to integrate a great amount of various data to create a predictive model and identify appropriate and individualized interventions. Based on these assumptions the present perspective aims to propose the development of a new approach to an integrated, multimethod, multidimensional training in order to enhance cognition and physical aspects based on behavioral data, incorporating consolidated technologies in an innovative approach to neurology.
Iris type:
1.1 Articolo in rivista
Keywords:
aging; artificial intelligence; dual-task; machine learning; neurology; psychometric; rehabilitation; virtual reality
List of contributors:
Bruni, F.; Borghesi, F.; Mancuso, V.; Riva, G.; Stramba-Badiale, M.; Pedroli, E.; Cipresso, P.
Authors of the University:
PEDROLI ELISA
Handle:
https://iris.uniecampus.it/handle/11389/49886
Published in:
FRONTIERS IN AGING NEUROSCIENCE
Journal
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