The puzzle of RehbeCa: an exergame for assessing cervicalgia

Abstract Neck range of motion (ROM) and pain assessment are crucial aspects of cervical examination. The goal is to match a patient’s clinical presentation with an appropriate treatment. We developed and evaluated a mobile puzzle-based exergame for assessing cervicalgia. An exploratory experiment with healthy participants and simulated neck mobility restrictions investigated the relationship between task performance and neck ROM. Insights from this phase led to refinement of the experimental design and apparatus. In a subsequent experiment, the exergame was tested on participants with neck pain to analyze how their neck ROM and pain condition affect task performance. Results indicate that participants suffering from neck pain maintained similar task performance metrics, such as selection rate, but exhibited greater variability in ROM, reflecting their adaptation to pain and mobility limitations. Results also indicate that pain condition significantly influences completion time: Participants with neck pain took longer to complete puzzles than participants with no pain. In the last stage, the data from both experiments were used to feed a machine learning model to test the automatic prediction of cervicalgia assessment parameters. This work advances rehabilitation technologies by integrating tools to automatically adapt and combine exercise and parameters of cervical rehabilitation enabling functional assessment without needing external sensors, distinguishing it from many existing approaches. The system is not only a rehabilitation tool, but also a method for evaluating cervical pain and mobility based on user interaction data.