Overwatch-M System: Implementation of Bayesian Statistics for Assessment of Sensorimotor Control

Abstract

This work introduces a novel strategy that combines a Bayesian Probabilistic Theory with Mixed Reality (MR) to assess user’s sensorimotor control. The purpose of this system is to estimate where does the user beliefs its hand is located from sensory information after performing a set of short MR tests. Thence, to accomplish this goal, the system applies a Bayesian approach to adjust the likelihood of a test with prior evidence. Hence, the system collects spatial information about the user’s hand position in a 3D space. After data collection, the data gets structured into visual (azimuth) and proprioceptive (depth) senses. Then, the probability distribution of these two senses gets analyzed using Bayesian Statistics to adjust the user’s belief about the position of the hand given these two senses. With this approach, we intend to determine a framework to collect sensory information in an MR environment and use a statistical framework to study motor performance.