US 11,908,585 B2Granted

Method for modeling behavior and depression state

AssigneeOrangeDot, Inc.

InventorsSai Moturu, Anmol Madan, Shishir Dash, Karim Wahba, Gourab De

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Abstract

A method and system for modeling behavior and depression state of an individual, the method comprising: receiving a log of use dataset associated with communication behavior of the individual during a time period; receiving a supplementary dataset characterizing activity of the individual during the time period; receiving a survey dataset including responses, to at least one of a set of depression-assessment surveys, associated with a set of time points of the time period; generating a predictive analysis of a depression-risk state of the individual associated with at least a portion of the time period, from at least one of the log of use dataset, the supplementary dataset, and the survey dataset; and generating an alert upon detection that a set of parameters from the predictive analysis of the depression-risk state satisfy a threshold condition.

Claims18

Dependent claims

A method for improving depression state determination and monitoring for a user, the method comprising:

receiving a first communication dataset from an application executing on a mobile communication device of the user, wherein the first communication dataset comprises a first set of message transcripts associated with a first time period;
with a first model, deriving a first textual content associated with the first set of message transcripts;
with a second model, wherein the second model comprises a trained predictive model, determining a first set of depression risk parameters associated with the user based on the first textual content;
assessing the first set of depression risk parameters to determine a first depression risk state associated with the user;
in response to and based on the first depression risk state, determining and initiating provision of a first therapeutic intervention at the mobile communication device, the first therapeutic intervention operable to improve the depression state of the user;
receiving a second communication dataset from the application, wherein the second communication dataset comprises a second set of message transcripts associated with a second time period, the second time period occurring later in time than the first time period;
with the first model, deriving a second textual content associated with the second set of message transcripts;
with the second model, determining a second depression risk state associated with the user based on the second textual content;
in response to the second depression risk state and based on a change from the first depression risk state to the second depression risk state, determining and initiating provision of a second therapeutic intervention at the mobile communication device, the second therapeutic intervention operable to improve the depression state of the user;
updating the second model based on the change from the first depression risk state to the second depression risk state, wherein updating the second model is operable to increase a predictive accuracy of the second model for the user;
and
with the updated second model, determining a third depression risk state associated with the user based on a third textual content.

9 more elements

A method for improving depression state determination and monitoring for a user, the method comprising:

receiving a first communication dataset from an application executing on a mobile communication device of the user;
with a trained predictive model, determining a first set of depression risk parameters associated with the user based on the first communication dataset;
assessing the first set of depression risk parameters to determine a first depression risk state associated with the user;
in response to and based on the first depression risk state, determining and initiating provision of a first therapeutic intervention at the mobile communication device, the first therapeutic intervention operable to improve the depression state of the user;
receiving a second communication dataset from the application, wherein the second communication dataset is associated with a second time period, the second time period occurring later in time than the first time period;
with the trained predictive model, determining a second depression risk state associated with the user based on the second communication dataset;
in response to and based on the second depression risk state, determining and initiating provision of a second therapeutic intervention at the mobile communication device, the second therapeutic intervention operable to improve the depression state of the user;
and
updating the trained predictive model based on the second depression risk state wherein updating the trained predictive model is operable to increase a predictive accuracy of the trained predictive model to determine a depression risk state associated with the user;
and
with the updated trained predictive model, determining a third depression risk state associated with the user based on a third communication dataset.

8 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/517,561Filed 2 Nov 2021 · continuation
Priority: 16 Aug 2012
Published: US 2022/0059235 A124 Feb 2022
Granted: 20 Feb 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification9 codes

G16H 50/50
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
G16H 10/20
ICT specially adapted for the handling or processing of patient-related medical or healthcare data: for electronic clinical trials or questionnaires
G16H 40/63
For the operation of medical equipment or devices: for local operation
G16H 40/67
For the operation of medical equipment or devices: for remote operation

Family

Application61/683,867Us provisional application · filed 16 Aug 2012
Application61/683,869Us provisional application · filed 16 Aug 2012
Application13/969,339Parent of this continuation-in-part · filed 16 Aug 2013
Application62/043,201Us provisional application · filed 28 Aug 2014
Application62/043,328Us provisional application · filed 28 Aug 2014
Application62/043,566Us provisional application · filed 29 Aug 2014
Application62/069,177Us provisional application · filed 27 Oct 2014
Application14/839,053Parent of this continuation · filed 28 Aug 2015
Application16/056,984Parent of this continuation · filed 7 Aug 2018
US 10,068,670 B2Parent of this continuation · filed 4 Sep 2018
US 2022/0059235 A1Pre-grant publication · published 24 Feb 2022
US 11,195,625 B2Parent of this continuation
Application14/839,053Parent of this continuation-in-part
US 2014/0052474 A1Published application
US 2015/0370993 A1Published application
US 2018/0342326 A1Published application
US 11,908,585 B2This patent

From the US filing history. Foreign family members aren’t listed.

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