Towards predicting sensorimotor disorders in older adults via Bayesian probabilistic theory and mixed reality

Abstract

In this work, we present the Overwatch-M platform, a novel approach that combines Bayesian theory with mixed reality (MR) to assess the user's sensorimotor control. This platform is composed of a set of simple MR tests, which are short, and guides the user through a series of activities while monitoring the user's interaction. The main advantage of this strategy relays on its ability to combine prior and observed user's interaction to determine the impact on the user's functional performance. This approach aims to detect changes in the user's functional performance that could lead to sensorimotor problems in older adults at an early stage. For validation, a Bayesian model is implemented into the system to collect and analyze datasets and to provide a quantitative estimation of functional performance by providing a probabilistic conditioning assessment of their test-interaction over time. The strategy has been implemented to test the sensorimotor function, eye-hand coordination.