AGELESS - Applications for Geriatric Exercises: Learning of the Elderly by Sensors and Software

Abstract

This paper proposes the study of a system intended to improve the quality of life and the autonomy of the elderly population through physical exercise controlled by several applications. The goal is to evaluate the evolution of three physical components in two distinct groups of elderly in different institutions. There is a control group and a study group per institution. The experimental protocol is based on distinct scenarios. In one scenario, the idea is to assess the impact of exercise preview on emotional (Neurofeedback) and motor (Biofeedback) levels. For that, users will have access to an application to preview on a monitor the sequence of exercises to be performed later in the classroom. During the preview, a BCI device will be used to evaluate parameters of the EEG signal (stress, immersion and anxiety). In another scenario, the evaluation of the impact and dynamism of using an application of augmented reality at the motor level considering the three components under analysis (balance, strength and flexibility) is done while users, in a classroom environment, will follow the proposed tasks. A monitoring application with several modules, for user's data, for professional configuration modes and for data visualization, is also included. All the applications use a range of gamification techniques, appropriate to the users’ physical condition, to motivate them. There is also the application of an automatic taxonomy to facilitate the selection of an appropriate exercise to be proposed to a particular individual at a specific moment.