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Gsaxner C, Li J, Pepe A, Jin Y, Kleesiek J, Schmalstieg D, Egger J. The HoloLens in medicine: A systematic review and taxonomy. Med Image Anal 2023; 85:102757. [PMID: 36706637 DOI: 10.1016/j.media.2023.102757] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 01/05/2023] [Accepted: 01/18/2023] [Indexed: 01/22/2023]
Abstract
The HoloLens (Microsoft Corp., Redmond, WA), a head-worn, optically see-through augmented reality (AR) display, is the main player in the recent boost in medical AR research. In this systematic review, we provide a comprehensive overview of the usage of the first-generation HoloLens within the medical domain, from its release in March 2016, until the year of 2021. We identified 217 relevant publications through a systematic search of the PubMed, Scopus, IEEE Xplore and SpringerLink databases. We propose a new taxonomy including use case, technical methodology for registration and tracking, data sources, visualization as well as validation and evaluation, and analyze the retrieved publications accordingly. We find that the bulk of research focuses on supporting physicians during interventions, where the HoloLens is promising for procedures usually performed without image guidance. However, the consensus is that accuracy and reliability are still too low to replace conventional guidance systems. Medical students are the second most common target group, where AR-enhanced medical simulators emerge as a promising technology. While concerns about human-computer interactions, usability and perception are frequently mentioned, hardly any concepts to overcome these issues have been proposed. Instead, registration and tracking lie at the core of most reviewed publications, nevertheless only few of them propose innovative concepts in this direction. Finally, we find that the validation of HoloLens applications suffers from a lack of standardized and rigorous evaluation protocols. We hope that this review can advance medical AR research by identifying gaps in the current literature, to pave the way for novel, innovative directions and translation into the medical routine.
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Affiliation(s)
- Christina Gsaxner
- Institute of Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria; BioTechMed, 8010 Graz, Austria.
| | - Jianning Li
- Institute of AI in Medicine, University Medicine Essen, 45131 Essen, Germany; Cancer Research Center Cologne Essen, University Medicine Essen, 45147 Essen, Germany
| | - Antonio Pepe
- Institute of Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria; BioTechMed, 8010 Graz, Austria
| | - Yuan Jin
- Institute of Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria; Research Center for Connected Healthcare Big Data, Zhejiang Lab, Hangzhou, 311121 Zhejiang, China
| | - Jens Kleesiek
- Institute of AI in Medicine, University Medicine Essen, 45131 Essen, Germany; Cancer Research Center Cologne Essen, University Medicine Essen, 45147 Essen, Germany
| | - Dieter Schmalstieg
- Institute of Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria; BioTechMed, 8010 Graz, Austria
| | - Jan Egger
- Institute of Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria; Institute of AI in Medicine, University Medicine Essen, 45131 Essen, Germany; BioTechMed, 8010 Graz, Austria; Cancer Research Center Cologne Essen, University Medicine Essen, 45147 Essen, Germany
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Planning Collision-Free Robot Motions in a Human–Robot Shared Workspace via Mixed Reality and Sensor-Fusion Skeleton Tracking. ELECTRONICS 2022. [DOI: 10.3390/electronics11152407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The paper describes a method for planning collision-free motions of an industrial manipulator that shares the workspace with human operators during a human–robot collaborative application with strict safety requirements. The proposed workflow exploits the advantages of mixed reality to insert real entities into a virtual scene, wherein the robot control command is computed and validated by simulating robot motions without risks for the human. The proposed motion planner relies on a sensor-fusion algorithm that improves the 3D perception of the humans inside the robot workspace. Such an algorithm merges the estimations of the pose of the human bones reconstructed by means of a pointcloud-based skeleton tracking algorithm with the orientation data acquired from wearable inertial measurement units (IMUs) supposed to be fixed to the human bones. The algorithm provides a final reconstruction of the position and of the orientation of the human bones that can be used to include the human in the virtual simulation of the robotic workcell. A dynamic motion-planning algorithm can be processed within such a mixed-reality environment, allowing the computation of a collision-free joint velocity command for the real robot.
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Abstract
Augmented reality (AR) is an innovative system that enhances the real world by superimposing virtual objects on reality. The aim of this study was to analyze the application of AR in medicine and which of its technical solutions are the most used. We carried out a scoping review of the articles published between 2019 and February 2022. The initial search yielded a total of 2649 articles. After applying filters, removing duplicates and screening, we included 34 articles in our analysis. The analysis of the articles highlighted that AR has been traditionally and mainly used in orthopedics in addition to maxillofacial surgery and oncology. Regarding the display application in AR, the Microsoft HoloLens Optical Viewer is the most used method. Moreover, for the tracking and registration phases, the marker-based method with a rigid registration remains the most used system. Overall, the results of this study suggested that AR is an innovative technology with numerous advantages, finding applications in several new surgery domains. Considering the available data, it is not possible to clearly identify all the fields of application and the best technologies regarding AR.
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