Evaluation Challenges for the Application of Extended Reality Devices in Medicine.

Augmented and virtual reality devices are being actively investigated and implemented for a wide range of medical uses. However, significant gaps in the evaluation of these medical devices and applications hinder their regulatory evaluation. Addressing these gaps is critical to demonstrating the devices' safety and effectiveness. We outline the key technical and clinical evaluation challenges discussed during the US Food and Drug Administration's public workshop, "Medical Extended Reality: Toward Best Evaluation Practices for Virtual and Augmented Reality in Medicine" and future directions for evaluation method development. Evaluation challenges were categorized into several key technical and clinical areas. Finally, we highlight current efforts in the standards communities and illustrate connections between the evaluation challenges and the intended uses of the medical extended reality (MXR) devices. Participants concluded that additional research is needed to assess the safety and effectiveness of MXR devices across the use cases.

Cognitive task analysis and workload classification.

Automation can be utilized to relieve humans of difficult and repetitive tasks in many domains, presenting the opportunity for safer and more efficient systems. This increase in automation has led to new supervisory roles for human operators where humans monitor feedback from autonomous systems and provide input when necessary. Optimizing these roles requires tools for evaluation of task complexity and resulting operator cognitive workload. Cognitive task analysis is a process for modeling the cognitive actions required of a human during a task. This work presents an enhanced version of this process: Cognitive Task Analysis and Workload Classification (CTAWC). The goal of developing CTAWC was to provide a standardized process to decompose cognitive tasks in enough depth to allow for precise identification of sources of cognitive workload. CTAWC has the following advantages over conventional CTA methodology:•Integrates standard terminology from existing taxonomies for task classification to describe expected operator cognitive workload during task performance.•Provides a framework to evaluate adequate cognitive depth when decomposing cognitive tasks.•Provides a standard model upon which to build an empirical study to evaluate task complexity.

Virtual Reality Provides an Effective Platform for Functional Evaluations of Closed-Loop Neuromyoelectric Control.

Although recent advances in neuroprostheses offer opportunities for improved and intuitive control of advanced motorized and sensorized robotic arms, practical complications associated with such hardware can impede the research necessary for clinical translation. These hurdles potentially can be reduced with virtual reality environments (VREs) with embedded physics engines using virtual models of physical robotic hands. These software suites offer several advantages over physical prototypes, including high repeatability, reduced human error, elimination of many secondary sensory cues, and others. There are limited demonstrations of closed-loop prostheses in the VRE, and it is unclear whether VRE performance translates to the physical world. Here we describe how two trans-radial amputees with neural and intramuscular implants identified objects and performed activities of daily living with closed-loop control of prostheses in the VRE. Our initial evidence further suggests that capabilities with virtual prostheses may be predictors of physical prosthesis performance, demonstrating the utility of VREs for neuroprosthetic research.