Geoffrey Tien

What Do Surgeons See: Capturing and Synchronizing Eye Gaze for Surgery Applications

Recording eye motions in surgical environments is challenging. This study describes the authors’ experiences with performing eye-tracking for improving surgery training, both in the laboratory and in the operating room (OR). Three different eye-trackers were used, each with different capabilities and requirements. For monitoring eye gaze shifts over the room scene in a simulated OR, a head-mounted system was used. The number of surgeons’ eye glances on the monitor displaying patient vital signs was successfully captured by this system. The resolution of the head-mounted eye-tracker was not sufficient to obtain the gaze coordinates in detail on the surgical display monitor. The authors then selected a high-resolution eye-tracker built in to a 17-inch computer monitor that is capable of recording gaze differences with resolution of 1° of visual angle. This system enables one to investigate surgeons’ eye–hand coordination on the surgical monitor in the laboratory environment. However, the limited effective tracking distance restricts the use of this system in the dynamic environment in the real OR. Another eye-tracker system was found with equally high level of resolution but with more flexibility on the tracking distance, as the eye-tracker camera was detached from the monitor. With this system, the surgeon’s gaze during 11 laparoscopic procedures in the OR was recorded successfully. There were many logistical challenges with unobtrusively integrating the eye-tracking equipment into the regular OR workflow and data processing issues in the form of image compatibility and data validation. The experiences and solutions to these challenges are discussed.

Saccadic delays on targets while watching videos

To observe whether there is a difference in eye gaze between doing a task, and watching a video of the task, we recorded the gaze of 17 subjects performing a simple surgical eye-hand coordination task. We also recorded eye gaze of the same subjects later while they were watching videos of their performance. We divided the task into 9 or more sub-tasks, each of which involved a large hand movement to a new target location. We analyzed the videos manually and located the video frame for each sub-task where the operators saccadic movement began, and the frame where the watchers eye movement began. We found a consistent delay of about 600 ms between initial eye movement when doing the task, and initial eye movement when watching the task, observed in 96.3% of the sub-tasks. For the first time, we have quantified the differences between doing and watching a manual task. This will help develop gaze-based training strategies for manual tasks.

Evaluating Eyegaze Targeting to Improve Mouse Pointing for Radiology Tasks

In current radiologists’ workstations, a scroll mouse is typically used as the primary input device for navigating image slices and conducting operations on an image. Radiological analysis and diagnosis rely on careful observation and annotation of medical images. During analysis of 3D MRI and CT volumes, thousands of mouse clicks are performed everyday, which can cause wrist fatigue. This paper presents a dynamic control-to-display (C-D) gain mouse movement method, controlled by an eyegaze tracker as the target predictor. By adjusting the C-D gain according to the distance to the target, the mouse click targeting time is reduced. Our theoretical and experimental studies show that the mouse movement time to a known target can be reduced by up to 15%. We also present an experiment with 12 participants to evaluate the role of eyegaze targeting in the realistic situation of unknown target positions. These results indicate that using eyegaze to predict the target position, the dynamic C-D gain method can improve pointing performance by 8% and reduce the error rate over traditional mouse movement.

Improving Mouse Pointing for Radiology Tasks

Radiologists make their main analysis and diagnosis based on careful observation of medical images, although there are all kinds of automatic methods under development. Radiologists typically use a scroll mouse to click on an image when they find something interesting, and they also use the mouse to navigate through the image slices in volumetric scans. Thus they perform many thousands of mouse clicks every day, causing wrist fatigue. This paper presents a method of improving the mouse pointing performance by reducing the time taken to move the mouse to a target. We use a dynamic Control-to-Display (C-D) ratio of the mouse, by adjusting the C-D ratio according to the current distance to the target. In theory this reduces the difficulty of the target selection, and also reduces the movement time. The result of preliminary study demonstrates that the speed of pointing can be improved under certain conditions, particularly for small targets and for long distances to move. In addition, all participants claim that this mouse speed change reduces the difficulty of selecting a small target.