VisCoMET: Visually Analyzing Team Collaboration in Medical Emergency Trainings

Handling emergencies requires efficient and effective collaboration of medical professionals. To analyze their performance, in an application study, we have developed VisCoMET, a visual analytics approach displaying interactions healthcare personnel triage training mass casualty incident. The scenario stems from social interaction research, where the teams is studied different perspectives. We integrate recorded annotations multiple sources, such as videos sessions, transcribed communication, eye-tracking information. For each session, information-rich timeline visualizes events across these channels, specifically highlighting between team members. provide algorithmic support to identify frequent event patterns search for user-defined sequences. Comparing teams, overview visualization aggregates session glyph node, connected similar sessions through edges. An example shows usage comparative analysis encountered same scene, highlights discovered insights. was evaluated feedback experts. results show that supports reflecting on teams' performance by exploratory behavior while particularly enabling comparison sessions.