The MAGIC of E-Health: A Gesture-Based Approach to Estimate Understanding and Performance in Remote Ultrasound Tasks

摘要

This work presents an approach to estimate task understanding and performance during a remote ultrasound training task via gestures. These task understanding insights are obtained through the PIA metric, a score that represents how well are gestures being used to complete a shared task. To evaluate our hypothesis, 20 participants performed a remote ultrasound training task consisting of three subtasks: vessel detection, blood extraction, and foreign body detection. Afterwards, their task understanding and performance was estimated using our PIA metric and three other metrics: error rate, idle time rate, and task completion percentage. After performing a correlation analysis, we found significant correlations between the PIA metric and all the other metrics for task understanding estimation. In addition, the insights generated from our PIA score explained inconsistencies in the participants' scores that were not expressed using the other metrics. Finally, we used two post-experiment questionnaires to subjectively evaluate the participants' perceived understanding and performance, and found that the PIA score was significantly correlated with the participants' overall task understanding. All these results indicate that a gesture-based metric can be used to estimate task understanding, which can have a positive impact in the way remote ultrasound tasks are performed and assessed.