Pain Marker Evaluation Application in Augmented Reality and Mobile Platforms

Pain evaluation methods can represent pain information clearly yet inefficiently; they also cannot effectively display long-term pain records for review or comparison. They often must be supplemented by multidimensional scales with descriptors and labeled body figures. Pain is complicated to describe accurately, has a variety of causes, is related to pathology, and, in pain evaluation, needs improvements in information loss or incompleteness, dynamic pattern, long-term history tracking, and complexity and convenience of recording and maintaining this information. We propose a novel pain recording and tracking system using augmented reality (AR) that is complete and direct to use. Results show this app is reliable and appeals to users.

Duke Scholars

Author Ming-Chun Huang DKU Faculty