A Dynamic Bayesian Network Approach To Behavioral Modelling Of Elderly People During A Home-Based Augmented Reality Balance Physiotherapy Programme

In this study, we propose a dynamic Bayesian network (DBN)-based approach to behavioral modelling of community dwelling older adults at risk for falls during the daily sessions of a hologram-enabled vestibular rehabilitation therapy programme. The component of human behavior being modelled is the level of frustration experienced by the user at each exercise, as it is assessed by the NASA Task Load Index. Herein, we present the topology of the DBN and test its inference performance on real-patient data.