Letter to the Editor on “Augmented Reality Based Navigation for Computer Assisted Hip Resurfacing: A Proof of Concept Study”

AR-Supported Supervision of Conditional Autonomous Robots: Considerations for Pedicle Screw Placement in the Future

Robotic assistance is applied in orthopedic interventions for pedicle screw placement (PSP). While current robots do not act autonomously, they are expected to have higher autonomy under surgeon supervision in the mid-term. Augmented reality (AR) is promising to support this supervision and to enable human–robot interaction (HRI). To outline a futuristic scenario for robotic PSP, the current workflow was analyzed through literature review and expert discussion. Based on this, a hypothetical workflow of the intervention was developed, which additionally contains the analysis of the necessary information exchange between human and robot. A video see-through AR prototype was designed and implemented. A robotic arm with an orthopedic drill mock-up simulated the robotic assistance. The AR prototype included a user interface to enable HRI. The interface provides data to facilitate understanding of the robot’s ”intentions”, e.g., patient-specific CT images, the current workflow phase, or the next planned robot motion. Two-dimensional and three-dimensional visualization illustrated patient-specific medical data and the drilling process. The findings of this work contribute a valuable approach in terms of addressing future clinical needs and highlighting the importance of AR support for HRI.

Parallax Free Registration for Augmented Reality Optical See-Through Displays in the Peripersonal Space

Egocentric augmented reality (AR) interfaces are quickly becoming a key asset for assisting high precision activities in the peripersonal space in several application fields. In these applications, accurate and robust registration of computer-generated information to the real scene is hard to achieve with traditional Optical See-Through (OST) displays given that it relies on the accurate calibration of the combined eye-display projection model. The calibration is required to efficiently estimate the projection parameters of the pinhole model that encapsulate the optical features of the display and whose values vary according to the position of the user's eye. In this article, we describe an approach that prevents any parallax-related AR misregistration at a pre-defined working distance in OST displays with infinity focus; our strategy relies on the use of a magnifier placed in front of the OST display, and features a proper parameterization of the virtual rendering camera achieved through a dedicated calibration procedure that accounts for the contribution of the magnifier. We model the registration error due to the viewpoint parallax outside the ideal working distance. Finally, we validate our strategy on a OST display, and we show that sub-millimetric registration accuracy can be achieved for working distances of ±100 mm around the focal length of the magnifier.

Evaluation of a Wearable AR Platform for Guiding Complex Craniotomies in Neurosurgery

Today, neuronavigation is widely used in daily clinical routine to perform safe and efficient surgery. Augmented reality (AR) interfaces can provide anatomical models and preoperative planning contextually blended with the real surgical scenario, overcoming the limitations of traditional neuronavigators. This study aims to demonstrate the reliability of a new-concept AR headset in navigating complex craniotomies. Moreover, we aim to prove the efficacy of a patient-specific template-based methodology for fast, non-invasive, and fully automatic planning-to-patient registration. The AR platform navigation performance was assessed with an in-vitro study whose goal was twofold: to measure the real-to-virtual 3D target visualization error (TVE), and assess the navigation accuracy through a user study involving 10 subjects in tracing a complex craniotomy. The feasibility of the template-based registration was preliminarily tested on a volunteer. The TVE mean and standard deviation were 1.3 and 0.6 mm. The results of the user study, over 30 traced craniotomies, showed that 97% of the trajectory length was traced within an error margin of 1.5 mm, and 92% within a margin of 1 mm. The in-vivo test confirmed the feasibility and reliability of the patient-specific template for registration. The proposed AR headset allows ergonomic and intuitive fruition of preoperative planning, and it can represent a valid option to support neurosurgical tasks.

Augmented reality in robotic assisted orthopaedic surgery: A pilot study

BACKGROUND

The research and development of augmented-reality (AR) technologies in surgical applications has seen an evolution of the traditional user-interfaces (UI) utilised by clinicians when conducting robot-assisted orthopaedic surgeries. The typical UI for such systems relies on surgeons managing 3D medical imaging data in the 2D space of a touchscreen monitor, located away from the operating site. Conversely, AR can provide a composite view overlaying the real surgical scene with co-located virtual holographic representations of medical data, leading to a more immersive and intuitive operator experience.

MATERIALS AND METHODS

This work explores the integration of AR within an orthopaedic setting by capturing and replicating the UI of an existing surgical robot within an AR head-mounted display worn by the clinician. The resulting mixed-reality workflow enabled users to simultaneously view the operating-site and real-time holographic operating informatics when carrying out a robot-assisted patellofemoral-arthroplasty (PFA). Ten surgeons were recruited to test the impact of the AR system on procedure completion time and operating surface roughness.

RESULTS AND DISCUSSION

The integration of AR did not appear to require subjects to significantly alter their surgical techniques, which was demonstrated by non-significant changes to the study's clinical metrics, with a statistically insignificant mean increase in operating time (+0.778 s, p = 0.488) and a statistically insignificant change in mean surface roughness (p = 0.274). Additionally, a post-operative survey indicated a positive consensus on the usability of the AR system without incurring noticeable physical distress such as eyestrain or fatigue.

CONCLUSIONS

Overall, these study results demonstrated a successful integration of AR technologies within the framework of an existing robot-assisted surgical platform with no significant negative effects in two quantitative metrics of surgical performance, and a positive outcome relating to user-centric and ergonomic evaluation criteria.

Optical See-Through Head-Mounted Displays With Short Focal Distance: Conditions for Mitigating Parallax-Related Registration Error

Optical see-through (OST) augmented reality head-mounted displays are quickly emerging as a key asset in several application fields but their ability to profitably assist high precision activities in the peripersonal space is still sub-optimal due to the calibration procedure required to properly model the user's viewpoint through the see-through display. In this work, we demonstrate the beneficial impact, on the parallax-related AR misregistration, of the use of optical see-through displays whose optical engines collimate the computer-generated image at a depth close to the fixation point of the user in the peripersonal space. To estimate the projection parameters of the OST display for a generic viewpoint position, our strategy relies on a dedicated parameterization of the virtual rendering camera based on a calibration routine that exploits photogrammetry techniques. We model the registration error due to the viewpoint shift and we validate it on an OST display with short focal distance. The results of the tests demonstrate that with our strategy the parallax-related registration error is submillimetric provided that the scene under observation stays within a suitable view volume that falls in a ±10 cm depth range around the focal plane of the display. This finding will pave the way to the development of new multi-focal models of OST HMDs specifically conceived to aid high-precision manual tasks in the peripersonal space.

Ambiguity-Free Optical-Inertial Tracking for Augmented Reality Headsets

The increasing capability of computing power and mobile graphics has made possible the release of self-contained augmented reality (AR) headsets featuring efficient head-anchored tracking solutions. Ego motion estimation based on well-established infrared tracking of markers ensures sufficient accuracy and robustness. Unfortunately, wearable visible-light stereo cameras with short baseline and operating under uncontrolled lighting conditions suffer from tracking failures and ambiguities in pose estimation. To improve the accuracy of optical self-tracking and its resiliency to marker occlusions, degraded camera calibrations, and inconsistent lighting, in this work we propose a sensor fusion approach based on Kalman filtering that integrates optical tracking data with inertial tracking data when computing motion correlation. In order to measure improvements in AR overlay accuracy, experiments are performed with a custom-made AR headset designed for supporting complex manual tasks performed under direct vision. Experimental results show that the proposed solution improves the head-mounted display (HMD) tracking accuracy by one third and improves the robustness by also capturing the orientation of the target scene when some of the markers are occluded and when the optical tracking yields unstable and/or ambiguous results due to the limitations of using head-anchored stereo tracking cameras under uncontrollable lighting conditions.

Off-Line Camera-Based Calibration for Optical See-Through Head-Mounted Displays

In recent years, the entry into the market of self contained optical see-through headsets with integrated multi-sensor capabilities has led the way to innovative and technology driven augmented reality applications and has encouraged the adoption of these devices also across highly challenging medical and industrial settings. Despite this, the display calibration process of consumer level systems is still sub-optimal, particularly for those applications that require high accuracy in the spatial alignment between computer generated elements and a real-world scene. State-of-the-art manual and automated calibration procedures designed to estimate all the projection parameters are too complex for real application cases outside laboratory environments. This paper describes an off-line fast calibration procedure that only requires a camera to observe a planar pattern displayed on the see-through display. The camera that replaces the user’s eye must be placed within the eye-motion-box of the see-through display. The method exploits standard camera calibration and computer vision techniques to estimate the projection parameters of the display model for a generic position of the camera. At execution time, the projection parameters can then be refined through a planar homography that encapsulates the shift and scaling effect associated with the estimated relative translation from the old camera position to the current user’s eye position. Compared to classical SPAAM techniques that still rely on the human element and to other camera based calibration procedures, the proposed technique is flexible and easy to replicate in both laboratory environments and real-world settings.