Method and system for modeling behavior and heart disease state

• US 10,265,028 B2
• Filed: 08/24/2016
• Issued: 04/23/2019
• Est. Priority Date: 08/16/2012
• Status: Active Grant

• Current Assignee: OrangeDot, Inc.
• Original Assignee: Ginger.io, Inc. (OrangeDot, Inc.)
• Inventors: Moturu, Sai, Madan, Anmol
• Primary Examiner(s): Tomaszewski, Michael
• Application Number:
  US15/245,571
• Publication Number:
  US 20170000422A1
• Time in Patent Office: 972 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61M 2021/0027 by the hearing sense
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A method for evaluating cardiovascular health of a patient includes receiving a log of use dataset associated with patient digital communication behavior at a mobile computing device, wherein the log of use dataset is associated with a time period, receiving a supplementary dataset associated with the time period, generating a survey dataset based on a patient response to a survey, generating a cardiovascular health predictive model based upon at least one of the log of use dataset, the supplementary dataset, and the survey dataset, extracting a cardiovascular health metric from at least one of an output of the cardiovascular health predictive model, the log of use dataset, the supplementary dataset, and the survey dataset, wherein the cardiovascular health metric is associated with the time period; providing a cardiovascular-related notification to the patient; and automatically providing a cardiovascular therapeutic intervention at a cardiovascular device for the patient.

Claims

1. A method for therapeutic intervention provision for cardiovascular health of a patient, the method comprising:

receiving a first log of use dataset associated with patient digital communication behavior at a mobile computing device, wherein the first log of use dataset corresponds to a time period;

receiving a supplementary dataset associated with the mobile computing device, wherein the supplementary dataset corresponds to the time period;

generating a cardiovascular health predictive model based upon the first log of use dataset and the supplementary dataset;

extracting a cardiovascular health metric from at least one of an output of the cardiovascular health predictive model, the first log of use dataset, and the supplementary dataset, wherein the cardiovascular health metric is associated with the time period; and

in response to the cardiovascular health metric satisfying a cardiovascular health threshold condition, automatically administering a cardiovascular therapeutic intervention at a cardiovascular device for the patient, for improvement of the cardiovascular health of the patient.

2. The method of claim 1, further comprising:

presenting a cardiovascular evaluation digital survey to the patient at the mobile computing device; and

generating a survey dataset from a patient response to the cardiovascular evaluation digital survey,

wherein extracting the cardiovascular health metric comprises extracting the cardiovascular health metric from at least one of the survey dataset, the output of the cardiovascular health predictive model, the first log of use dataset, and the supplementary dataset.

3. The method of claim 2, further comprising:

assigning the patient to a cardiovascular subgroup of a set of cardiovascular subgroups, based on the survey dataset to the cardiovascular evaluation digital survey; and

retrieving a subgroup predictive model corresponding to the cardiovascular subgroup, wherein generating the cardiovascular health metric is in response to retrieving the subgroup predictive model, and wherein the cardiovascular health predictive model comprises the subgroup predictive model.

4. The method of claim 1, wherein the cardiovascular therapeutic intervention comprises a cardiovascular-related notification, and wherein automatically providing the cardiovascular therapeutic intervention comprises automatically providing the cardiovascular-related notification at the cardiovascular device.

5. The method of claim 1, wherein the cardiovascular health metric comprises at least one of a blood pressure metric, a heartbeat metric, and a respiration metric.

6. The method of claim 1, wherein the first log of use dataset indicates at least one of phone call-related data and text messaging data.

7. The method of claim 1, wherein the cardiac device comprises the mobile computing device.

8. The method of claim 1, further comprising:

generating a psychological health metric from a psychological health predictive model and a second log of use dataset; and

providing a health-related notification to the patient at the mobile computing device, wherein the health-related notification is based on at least one of the cardiovascular health metric and the psychological health metric.

9. The method of claim 8, wherein the first and the second log of use datasets are identical.

10. The method of claim 8, further comprising:

in response to the psychological health metric satisfying a psychological health threshold condition, automatically providing a psychological therapeutic intervention at the cardiovascular device for the patient.

11. A method for therapeutic intervention provision for cardiovascular health of a patient, the method comprising:

receiving a log of use dataset associated with patient digital communication behavior at a mobile computing device, wherein the log of use dataset corresponds to a time period;

determining digital communication behavior features based on the log of use dataset;

generating a cardiovascular health metric from the digital communication behavior features, wherein the cardiovascular health metric indicates the cardiovascular health of the patient during the time period; and

in response to generating the cardiovascular health metric, administering a cardiovascular therapeutic intervention to the patient at a cardiovascular device, wherein the cardiovascular therapeutic intervention is based on the cardiovascular health metric, for improvement of the cardiovascular health of the patient.

12. The method of claim 11, wherein administering the cardiovascular therapeutic intervention comprises:

in response to the cardiovascular health metric satisfying a cardiovascular health threshold condition, automatically administering the cardiovascular therapeutic intervention for the patient at the mobile computing device.

13. The method of claim 12, wherein the cardiovascular therapeutic intervention comprises an audio therapy configured to improve the cardiovascular health metric, and wherein providing the cardiovascular therapeutic intervention comprises controlling the mobile computing device to emit the audio therapy.

14. The method of claim 11, wherein the cardiovascular therapeutic intervention comprises a digital telemedicine communication with a health professional, and wherein providing the cardiovascular therapeutic intervention comprises:

automatically establishing a wireless communicable link with a health professional computing device associated with the health professional; and

facilitating the digital telemedicine communication using the wireless communicable link.

15. The method of claim 11, further comprising:

receiving a patient mobility behavior supplementary dataset comprising a travel metric indicating a distance traveled by the patient during the time period, wherein the patient mobility behavior supplementary dataset corresponds to the time period,

wherein generating the cardiovascular health metric comprises generating the cardiovascular health metric from at least one of the patient mobility behavior supplementary dataset and the digital communication behavior features.

16. The method of claim 11, further comprising:

receiving a heart rate supplementary dataset collected at a heart rate sensor of a cardiovascular device, wherein the heart rate supplementary dataset corresponds to the time period,

wherein generating the cardiovascular health metric comprises generating the cardiovascular health metric from the digital communication behavior features and the heart rate supplementary dataset.

17. The method of claim 11, wherein the time period is subsequent to patient consumption of a cardiovascular medication, and wherein generating the cardiovascular health metric comprises generating a treatment response metric indicating treatment response to the cardiovascular medication during the time period.

18. The method of claim 17, further comprising:

presenting a cardiovascular evaluation digital survey to the patient at the mobile computing device;

generating a survey dataset based on a patient response to the cardiovascular evaluation digital survey; and

identifying cardiovascular medication data associated with the cardiovascular medication, based on the survey dataset,

wherein generating the treatment response metric is based on the digital communication behavior features and the cardiovascular medication data.

19. The method of claim 11, wherein the cardiac device comprises the mobile computing device.

20. The method of claim 11, further comprising:

in response to the cardiovascular health metric satisfying a cardiovascular health threshold condition, automatically establishing a wireless communicable link with a cardiovascular device associated with the patient;

delivering, through the wireless communicable link, a cardiovascular therapeutic intervention to the patient at the cardiovascular device.

21. The method of claim 11, wherein providing the cardiovascular therapeutic intervention comprises providing a haptic alert to the patient at the cardiovascular device in response to the cardiovascular health metric satisfying a cardiovascular threshold condition.