Passive Eye Tracking Calibration for Surgical Robotic Consoles
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Solution Overview
Problem
Conventional eye tracking calibration in surgical robotic systems is intrusive and time-consuming, disrupting the setup workflow and requiring active user participation, which is undesirable during ongoing surgeries.
Innovation Solution
A method for passive eye tracking verification and calibration integration within the surgical robotic system's setup process, adjusting calibration parameters based on inferred user gaze and interaction with the user interface, eliminating the need for separate, active calibration routines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional eye tracking calibration is performed actively, then measurement precision is improved, but loss of time increases and ease of operation deteriorates
Solution Approach 1:
The system performs preliminary eye tracking calibration by capturing images of the user's eyes at multiple predetermined locations on the display screen before actual surgical operation begins. These preliminary calibration data are stored and automatically applied during surgery, eliminating the need for time-consuming active calibration routines at the start of each procedure.
Solution Approach 2:
The system enables self-service calibration by automatically processing captured eye images and determining gaze points without requiring continuous active user participation. The calibration process occurs passively during normal setup activities, and the system automatically adjusts calibration parameters based on the captured data, freeing the user to perform other setup tasks simultaneously.
2Measurement precision
If active calibration routines are required, then measurement precision is improved, but ease of operation worsens due to user burden
Solution Approach 1:
The system automatically captures eye images, processes them through image processing algorithms, determines gaze points, and adjusts calibration parameters without requiring the user to manually follow calibration instructions or actively participate in the calibration process. The user simply needs to look at the display during normal setup activities.
Solution Approach 2:
The system replaces manual active calibration procedures with an automated image processing and analysis system. Instead of requiring users to manually adjust calibration parameters or follow complex calibration routines, the system uses computer vision algorithms to automatically determine gaze points from captured eye images and adjust calibration accordingly.
3Loss of time
If eye tracking calibration is integrated into setup process, then loss of time is reduced, but measurement precision may deteriorate
Solution Approach 1:
Comprehensive eye tracking calibration data are captured and processed during the initial setup phase before surgical operations begin. Multiple eye images are captured at predetermined locations, and calibration parameters are thoroughly adjusted during this preliminary phase, ensuring high measurement precision is achieved before time-sensitive surgical procedures start.
Solution Approach 2:
The system captures and adjusts multiple calibration parameters including gaze points, eye position, and tracking algorithm parameters during the integrated setup process. By optimizing these parameters comprehensively during setup rather than making minor adjustments during surgery, the system maintains high measurement precision while reducing time loss.
Data Source
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AI summary
A method for passively calibrating and verifying eye tracking in a surgical robotic system. The gaze of a user facing a user display of a user console of a surgical robotic system is tracked while the user is using a user interface device (UID). When a user interaction to the UID is detected, an expected gaze position on the display of the user console is determined without instructing the user to look at the expected gaze position. The latter becomes a reference gaze point of the user at the time of detected user action. The measured gaze point of the user is compared with an acceptable threshold of the reference gaze point, and in response to a determination of a mismatch, calibration parameters used by the tracking are adjusted according to the reference gaze point. Other aspects are also described and claimed.