Abstract
This study aimed to develop and evaluate a remote damage control surgery (DCS) real-time guidance system based on HoloLens 2 for low-speed network environments. The system design follows a layered architecture model where the core logic is divided into network, data, service, and user layers. Data transmission in low-speed network environments is realized through multidimensional injury data encoding technology, combined with a WebSocket long-link protocol and fragmentation transmission technology. Multi-modal deep learning and decision tree algorithms are used to build an intelligent auxiliary model for injury assessment. Based on this, the HoloLens 2 immersive head-mounted display device is integrated via the Wi-Fi communication protocol to achieve multi-modal, real-time interactive surgical guidance. After the system development was completed, it was applied to four surgical teams composed of 28 students who were randomly divided into remote and control groups. An animal injury platform was used to construct a cranial trauma model for practical assessment. The remote and control groups used a guidance system and video call methods, respectively, to perform simulated remote surgery guidance. The differences in injury judgment, surgical operations, overall effectiveness scores, surgical time, and animal survival time between the two groups were compared. After the assessment, a self-made questionnaire was used for a satisfaction survey. In the remote group, the surgery operation scores were higher and the surgical time was shorter than in the control group (both P < 0.05). There were no significant differences between the two groups in injury assessment, overall effectiveness scores, or animal survival time (P > 0.05). The students scored the system’s necessity, effectiveness, compatibility, and deployment environment above 5 points. The remote DCS guidance system based on HoloLens 2 can provide remote real-time interactive guidance for DCS using mixed reality technology. The proposed method can mitigate data transmission delays in low-speed, complex network environments. In addition, the surgical guidance system can assist surgeons in improving their ability in DCS and provide real-time, efficient decision-making support, making it worthy of further application and popularization.
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Data availability
The datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request.
Code availability
The code used in this study has been included in the supplementary materials.
Abbreviations
- DCS:
-
Damage control surgery
- MR:
-
Mixed reality
- GAN:
-
Generative adversarial network
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Acknowledgements
We would like to thank anonymous reviewers and the editor for their comments. In addition, we want to express special thanks to Professor Huang Hongcheng and his team at Chongqing University of Posts and Telecommunications for their technical support in the field of artificial intelligence.
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C. C. and K. N. performed the validation and wrote the manuscript; Z. X. and J. Y. J. contributed to the practical assessment; J. R. Q. and D. C. L. prepared the tables and tures; Y. H. Y. analyzed the data; C. L. edited the manuscript; and Z. Z. W. and D. W. Q. contributed to the study concept, data interpretation, and final revision of the manuscript.
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This study was approved by the Ethics Committee of the Army Medical University (Clinical trial number: not applicable). All methods were used in accordance with the corresponding guidelines and regulations provided by the ethics and research committees. All participants provided their informed consent to participate in the study.
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Chen, C., Kang, N., Zhong, X. et al. Design and evaluation of a remote damage control surgery real-time guidance system based on HoloLens 2 in low-speed network environments. Sci Rep (2026). https://doi.org/10.1038/s41598-025-34705-w
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DOI: https://doi.org/10.1038/s41598-025-34705-w
