An agent-based game for the predictive diagnosis of parkinson's disease

Abstract

Existing Parkinson's Disease (PD) diagnosis relies heavily on doctors' observations combined with neurological exams. Such a technique is often inconvenient, infrequent, and subjective, which leads to a high misdiagnosis rate. As several cardinal symptoms of PD require long term observations, a technology platform which allows potential PD patients to exhibit related behaviors in a natural setting over long period of time is needed. In this paper, we describe an agent-based game for the predictive diagnosis of PD. Agents in this tablet based game provide companionship, encouragement, and analysis capabilities to help retain users' interest, and analyze their risk of developing PD symptoms based on their in-game behavior. The game has been launched together with a world renowned PD research centre for clinical trial. It can potentially provide a new dimension of longitudinal interactive behavior data to assist early and more accurate PD diagnosis in the future.

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