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.
翻译:改造后的数字游戏能够激发机动车康复所需重复练习的动力,但设计既符合康复目标又符合参与目标的修改却具有挑战性。我们提出一种方法,使基线游戏的统计模型能够确定与未修改游戏相适应的行为相似的设计配置。我们通过一个案例研究来说明这一方法,该案例研究涉及上肢康复,由Pac-Man游戏的定制控制员负责。一个与职业治疗师共同参与的设计讲习班确定了游戏游戏和康复调整的两种互动参数。参数对互动的影响是实验性地与12名参与者一起测量的。我们表明,使用用户输入行为和内部游戏状态的低延迟模型,确定了在退化控制下复制基线游戏的交互参数值。我们讨论如何应用这一方法来系统地平衡涉及物理要求和主观参与经验之间的权衡问题。