Image overlay surgery based on augmented reality : a systematic review

Acknowledgements We thank the staff of the Medical Library of the University of Aberdeen for their advice and Prof. Jennifer Cleland and Dr Jenny Gregory for discussion and support. This work was funded by the Roland Sutton Academic Trust (0053/R/17) and an Elphinstone PhD Scholarship from the University of Aberdeen.Postprin

Invasiveness of decompression surgery affects modeled lumbar spine kinetics in patients with degenerative spondylolisthesis.

Introduction: The surgical treatment of degenerative spondylolisthesis with accompanying spinal stenosis focuses mainly on decompression of the spinal canal with or without additional fusion by means of a dorsal spondylodesis. Currently, one main decision criterion for additional fusion is the presence of instability in flexion and extension X-rays. In cases of mild and stable spondylolisthesis, the optimal treatment remains a subject of ongoing debate. There exist different opinions on whether performing a fusion directly together with decompression has a potential benefit for patients or constitutes overtreatment. As X-ray images do not provide any information about internal biomechanical forces, computer simulation of individual patients might be a tool to gain a set of new decision criteria for those cases. Methods: To evaluate the biomechanical effects resulting from different decompression techniques, we developed a lumbar spine model using forward dynamic-based multibody simulation (FD_MBS). Preoperative CT data of 15 patients with degenerative spondylolisthesis at the level L4/L5 who underwent spinal decompression were identified retrospectively. Based on the segmented vertebrae, 15 individualized models were built. To establish a reference for comparison, we simulated a standardized flexion movement (intact) for each model. Subsequently, we performed virtual unilateral and bilateral interlaminar fenestration (uILF, bILF) and laminectomy (LAM) by removing the respective ligaments in each model. Afterward, the standardized flexion movement was simulated again for each case and decompression method, allowing us to compare the outcomes with the reference. This comprehensive approach enables us to assess the biomechanical implications of different surgical approaches and gain valuable insights into their effects on lumbar spine functionality. Results: Our findings reveal significant changes in the biomechanics of vertebrae and intervertebral discs (IVDs) as a result of different decompression techniques. As the invasiveness of decompression increases, the moment transmitted on the vertebrae significantly rises, following the sequence intact ➝ uILF ➝ bILF ➝ LAM. Conversely, we observed a reduction in anterior-posterior shear forces within the IVDs at the levels L3/L4 and L4/L5 following LAM. Conclusion: Our findings showed that it was feasible to forecast lumbar spine kinematics after three distinct decompression methods, which might be helpful in future clinical applications

Augmented reality in spine surgery: in-view visualization of virtually created osteotomy planes

Reg Gale's Meteorite - MT1 - photographed 1976

IEEE 802.11 CSI randomization to preserve location privacy: An empirical evaluation in different scenarios

Passive, device-free localization of a person exploiting the Channel State Information (CSI) from Wi-Fi signals is quickly becoming a reality. While this capability would enable new applications and services, it also raises concerns about citizens’ privacy. In this work, we propose a carefully-crafted obfuscating technique against one of such CSI-based localization methods. In particular, we modify the transmitted I/Q samples by leveraging an irreversible randomized sequence. I/Q symbol manipulation at the transmitter distorts the location-specific information in the CSI while preserving communication, so that an attacker can no longer derive information on user's location. We test this technique against a Neural Network (NN)-based localization system and show that the randomization of the CSI makes undesired localization practically unfeasible. Both the localization system and the CSI randomization are implemented on real devices. The experimental results obtained in our laboratories show that the considered localization method works smoothly regardless of the environment, and that adding random information to the CSI prevents the localization, thus providing the community with a system that preserve location privacy and communication performance at the same time

An Experimental Study of CSI Management to Preserve Location Privacy

Passive device-free localization of a person exploiting the Channel State Information (CSI) from Wi-Fi signals is quickly becoming a reality. While this capability would enable new applications and services, it also raises concerns about citizens' privacy. In this work, we propose a carefully-crafted obfuscating technique against one of such CSI-based localization methods. In particular, we modify the transmitted I/Q samples by leveraging an irreversible randomized sequence. I/Q symbol manipulation at the transmitter distorts the location-specific information in the CSI while preserving communication, so that an attacker can no longer derive information on user's location. We test this technique against a Neural Network (NN)-based localization system and show that the randomization of the CSI makes undesired localization practically unfeasible. Both the localization system and the randomization CSI management are implemented in real devices. The experimental results obtained in our laboratory show that the considered localization method (first proposed in an MSc thesis) works smoothly regardless of the environment, and that adding random information to the CSI mess up the localization, thus providing the community with a system that preserve location privacy and communication performance at the same time