On Extended Reality Objective Performance Metrics for Neurosurgical Training

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Abstract

The adoption of Extended Reality (XR) technologies for supporting learning processes is an increasingly popular research topic for a wide variety of domains, including medical education. Currently, within this community, the metrics applied to quantify the potential impact these technologies have on procedural knowledge acquisition are inconsistent. This paper proposes a practical definition of standard metrics for the learning goals in the application of XR to surgical training. Their value in the context of previous research in neurosurgical training is also discussed. Objective metrics of performance include: spatial accuracy and precision, time-to-task completion, number of attempts. The objective definition of what the learner’s aims are enables the creation of comparable XR systems that track progress during training. The first impact is to provide a community-wide metric of progress that allows for consistent measurements. Furthermore, a measurable target opens the possibility for automated performance assessments with constructive feedback.

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APA

Iop, A., Viberg, O., Elmi-Terander, A., Edström, E., & Romero, M. (2023). On Extended Reality Objective Performance Metrics for Neurosurgical Training. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14200 LNCS, pp. 573–579). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-42682-7_44

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