Using models of baseline gameplay to design for physical rehabilitation

TL;DR

This paper introduces a statistical modeling approach to design game modifications that balance rehabilitation needs and engagement by emulating baseline gameplay behaviors, demonstrated through a case study with upper limb rehab and a Pac-Man game.

Contribution

It presents a method using a low-latency model of gameplay to identify design parameters that replicate unmodified play under degraded control conditions.

Findings

The model successfully reproduces baseline gameplay behaviors.

Design parameters can be systematically tuned for rehabilitation and engagement balance.

The approach is applicable to various gamification scenarios involving physical and engagement trade-offs.

Abstract

Modified digital games manage to drive motivation in repetitive exercises needed for motor rehabilitation, however designing modifications that satisfy both rehabilitation and engagement goals is challenging. We present a method wherein a statistical model of baseline gameplay identifies design configurations that emulate behaviours compatible with unmodified play. We illustrate this approach through a case study involving upper limb rehabilitation with a custom controller for a Pac-Man game. A participatory design workshop with occupational therapists defined two interaction parameters for gameplay and rehabilitation adjustments. The parameters' effect on the interaction was measured experimentally with 12 participants. We show that a low-latency model, using both user input behaviour and internal game state, identifies values for interaction parameters that reproduce baseline gameplay under degraded control. We discuss how this method can be applied to systematically balance gamification problems involving trade-offs between physical requirements and subjectively engaging experiences.