Assistive sensor-based technology driven self-management for building resilience among people with early stage cognitive impairment

Abstract

This paper reports the technologies and workplan of the AAL RESILIEN-T project. Focused on assistive technologies, RESILIEN-T aims to improve, through self-management, the autonomy, participation in social life, and skills, of older Persons with Cognitive Impairment (PwCI) who are too often considered as “objects” of research, rather than “partners”. The study investigates existing ICT solutions to improve the self-management ability of PwCl at different stages of cognitive impairment. Sensors, devices and apps to reduce the progression of the disease are analyzed. To increase sensor capability, innovative data management, i.e. Artificial Intelligence and Machine Learning algorithms, are considered to extract significant information from the data and optimize the sensor network. Moreover, approaches to involve end-users in the development are also investigated to enhance the final outputs. The study proposes a modular and integrated platform for PwCI to self-manage various activities including nutrition, physical activities, social life, cognitive training. The choice of offering an open API to integrate wearable devices and lifestyle monitoring systems from different suppliers makes available a customable and modular product. Considering that functional decline is part of the normal aging process, it might be challenging to individuate three levels of modular architecture to increase the accuracy of the monitoring with the decline of the cognitive capabilities.

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