Intelligent Decision-Support (IDS) mechanisms to improve an ‘in-action’ facilitator intervention model and ‘on-action’ evaluation and refinement model are proposed for contemporary Virtual Reality Healthcare & Rehabilitation training. The ‘Zone of Optimized Motivation’ (ZOOM) model and the ‘Hermeneutic Action Research Recursive Reflection’ model have emerged from a body of virtual reality research called SoundScapes. The work targets all ages and all abilities through gesture-control of responsive multimedia within Virtual Interactive Space (VIS). VIS is an interactive information environment at the core of an open-ended custom system where unencumbered residual function manipulates selected audiovisual and robotic feedback that results in afferent-efferent neural feedback loop closure. Such loop closure is hypothesized as the reason why such interactive system environments are so effective in the context of rehabilitation and healthcare. The approach is adaptive across the range of dysfunction, from the most profoundly disabled to traditionally developed. This proposal considers enhancing VIS data exchange, i.e. human input information matched to responsive content, through dynamic decision-support of adjustment of difficulty encountered. To date facilitator role has included manual parameter manipulation of interface to affect an invisible active zone quality (typically, sensitivity or location) and/or content quality. Inaction human adjustment-decisions are according to interpretation of user state and engagement. Questioned is whether automated support for such decisions is feasible so that dynamic difficulty adjustment (DDA) of that which is encountered by the user is considered optimal to goal. Core issues are presented to detail and justify the concept. Findings are related to current trends with conclusions reflecting on potential impact.
Studies in Computational Intelligence, 2011, Vol 326, p. 143-169