IP Library Granted Patent US 12,451,256
Granted Patent B2
US 12,451,256 · App. 18/591,668 · Granted Oct 21, 2025

Distributed network for the secured collection, analysis, and sharing of data across platforms

Inventors: H. Leroux Jooste (Arden, NC); Mae-ellen Gavin (Arlington, MA); Kristin Zibell (Boston, MA); Matthew Omernick (Larkspur, CA); Jeffrey Steinmetz (San Francisco, CA)
Assignee: Akili Interactive Labs, Inc.
G16H50/30G16H10/60G16H20/10G16H40/20G16H50/20G16H50/70G16H80/00
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Quick Facts
Patent No.
US 12,451,256
App. No.
18/591,668
Granted
Oct 21, 2025
Kind
B2
Abstract

Computer-implemented methods and systems for managing the collection of and access to behavior assessment data. In an embodiment, a first user having authority to act on behalf of an individual under study identifies a second and third user role, specifies behavior data, symptom measurement data, and/or medicine regimen data associated with the individual under study, and defines access permissions for the second and third user roles with respect to the behavior data and symptom measurement data. The symptoms and behaviors to be measured are specified based on a condition of the individual. Users provide behavior data and symptom measurement data observed from the individual. An analytics module performs computational analysis on the behavior data and symptom measurement data, thereby producing behavior assessment data. A reporting module presents the behavior assessment data to the users in a manner consistent with the defined access permissions.

Claims (33)

1. A system comprising:

one or more processors; and

a non-transitory computer-readable memory device communicably coupled with the one or more processors;

wherein the one or more processors are configured to execute a plurality of modules stored in the non-transitory computer-readable memory device, and wherein the plurality of modules comprises:

a cognitive training application comprising a plurality of computerized stimuli or interactions configured to be presented to an individual under study at a display of a computing device,

wherein the computing device comprises a motion sensor and/or a position sensor,

wherein the plurality of computerized stimuli or interactions comprise a primary task configured to elicit a physical action from the individual under study at an input device of the computing device, and a secondary task configured to distract the individual under study from performing the primary task,

wherein the cognitive training application is configured to simultaneously measure data indicative of a first response from the individual under study to the primary task and a second response from the individual under study to the secondary task;

an end user application configured to render a graphical user interface to a first user at a first user device, wherein the end user application is configured to enable the first user to:

configure one or more user roles for one or more other users of the end user application, wherein the one or more other users comprise a healthcare practitioner user;

provide one or more user-generated inputs associated with one or more of behavior data and symptom measurement data associated with a condition of the individual under study, and define access permissions for the one or more user roles;

an authentication module configured to execute one or more operations for enforcing the access permissions such that the one or more user roles are selectively limited to providing and accessing a first subset of the behavior data and symptom measurement data within the end user application;

an analytics module configured to execute one or more operations for:

receiving a plurality of user activity data from an instance of the cognitive training application,

wherein the plurality of user activity data comprises motion sensor data and/or position sensor data received via the computing device in response to one or more motion-specific responses and/or position-specific responses from the individual under study; and

analyzing the plurality of user activity data, the behavior data and the symptom measurement data according to a machine learning framework comprising a classifier model configured to classify the plurality of user activity data, the behavior data and the symptom measurement data to generate a composite profile comprising one or more composite variables,

wherein the one or more composite variables comprise a measure of correlation with therapy compliance or treatment response based on a training dataset comprising training measurement data from subjects that are classified as to a known measure of therapy compliance or treatment response; and

a reporting module configured to execute one or more operations for:

processing the classified plurality of user activity data, the behavior data and the symptom measurement data to generate an analysis report for the individual under study,

wherein the symptom measurement data comprises physiological signals selected from electrical activity, heart rate, blood flow, and oxygenation levels, received from a physiological measurement component,

wherein the analysis report comprises an indication of a cognitive measure of the individual under study based on the composite profile, and

presenting the analysis report, including the classification, to the healthcare practitioner user via a role-based user instance of the end user application,

wherein the healthcare practitioner user modifies a course of treatment for the individual under study according to the analysis report.

2. The system of claim 1 wherein the classifier model is configured to identify a correlation between (i) the behavior data and symptom measurement data and (ii) data collected in connection with individuals who have exhibited desirable treatment response times.

3. The system of claim 2 wherein the correlation identifies at least one of an effective intervention, treatment efficacy, and drug performance.

4. The system of claim 1 wherein the composite profile is configured to classify the individual under study with respect to a likelihood of at least one of an onset or a progression of the condition of the individual under study.

5. The system of claim 1 further comprising a usage analytics database communicably engaged with the analytics module, wherein the usage analytics database is configured to store usage analytics data and provide the usage analytics data to the analytics module.

6. The system of claim 1 further comprising a content module configured to generate one or more content queries based at least in part on the classified behavior data.

7. The system of claim 6 wherein the content module is further configured to:

submit the one or more content queries to at least one content library comprising a content index; and

analyze content received from the at least one content library to determine a relevance to a status of the individual determined based on the classified behavior data.

8. The system of claim 1 wherein processing the classified user activity data and the classified behavior data comprises analyzing one or more contextual input or domain input according to at least one machine learning model to generate at least one predictive content for the analysis report.

9. The system of claim 1 wherein the access permissions are configured to selectively restrict access to or input of one or more of the behavior data, the symptom measurement data and medicine regimen data for the one or more other users.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 4, 2024
From: JOOSTE, H. LEROUX; GAVIN, MAE-ELLEN; ZIBELL, KRISTIN; OMERNICK, MATTHEW; STEINMETZ, JEFFREY
To: AKILI INTERACTIVE LABS, INC.
Reel/Frame 066639/0838 →
Continuity (3)
Continuation 16603193
Provisional Application 62482648 · Apr 6, 2017
Related Publication 20240282456A1 · Aug 22, 2024
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