Systems and methods for secure processing of eye tracking data

• US 10,685,748 B1
• Filed: 02/12/2020
• Issued: 06/16/2020
• Est. Priority Date: 02/12/2020
• Status: Active Grant

• Current Assignee: EyeTech Digital Systems Inc.
• Original Assignee: EyeTech Digital Systems Inc.
• Inventors: Chappell, Robert C, Manning, Miles, Kalbande, Sonal
• Primary Examiner(s): Burgess, Joseph D
• Application Number:
  US16/788,770
• Time in Patent Office: 125 Days
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 21/6245 Protecting personal data, e.g. for financial or medical purposes
• CPC Class Codes: G06F 2221/2107 File encryption
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 2220/00 Business processing using cryptography postage metering system using cryptography G06Q2250/05
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: H04L 9/50 using hash chains, e.g. blockchains or hash trees

Abstract

Systems and methods are provided for processing and storing eye-tracking data. A visual stimulus is provided to an experimental subject on a display. Eye-tracking data associated with the behavior of the experimental subject is acquired and stored while observing the visual stimulus on the display. The eye-tracking data is stored as primary data and secondary data, wherein the primary data is stored in an encrypted form using a secret key associated with the experimental subject. In response to a research request, the secondary data is transmitted for storage in a research database and, in response to a second research request authorized by the experimental subject, the primary data is transmitted for storage in the research database subsequent to decrypting the primary data using the secret key.

Claims

1. A method of securely processing and storing medical-related eye-tracking data, the method comprising:

presenting to an experimental subject, on a display of a computing device, a visual stimulus;

acquiring storing eye-tracking data associated with the behavior of the experimental subject during the presentation of the visual stimulus, wherein the eye-tracking data includes fixations data, saccade data, pupil-size data, and image data associated with the facial region and eyes of the experimental subject;

storing the image data as primary data and storing the fixations data, saccade data, and pupil-size data as secondary data, wherein the primary data is stored in an encrypted form using a secret key associated with the experimental subject;

transmitting, in response to a research request, the secondary data for storage in a research database;

transmitting, in response to a second research request authorized by the experimental subject, the primary data for storage in the research database subsequent to decrypting the primary data using the secret key;

implementing a machine learning model trained using the eye-tracking data stored in the research database to predict the likelihood of a patient having a neurogenerative disease; and

providing, to a subscriber system, a dashboard user interface that includes a visual representation of the visual stimulus, a visual representation of the eye-tracking data, and a prediction resulting from applying the previously-trained machine learning model to eye-tracking data generated by the behavior of a second experimental subject during presentation of the visual stimulus.

2. The method of claim 1, wherein the secondary data includes micro-saccade data.

3. The method of claim 1, wherein the research request is a digital form transmitted over a network and includes criteria for selecting the eye-tracking data to be provided to the research database.

4. The method of claim 1, wherein the experimental subject is prompted to complete a digital questionnaire that is subsequently stored by the eye-tracking analytics system and selectively provided to the research database.

5. The method of claim 4, wherein the machine learning model additionally uses data derived from the completed digital questionnaire for training.