IP Library › Granted Patent US 9,538,948
Granted Patent B2
US 9,538,948 · App. 15/214,130 · Granted Jan 10, 2017

Method and system for assessment of cognitive function based on mobile device usage

Inventor: Paul Dagum (Los Altos Hills, CA)
Assignee: Mindstrong, LLC
A61B5/16A61B5/0022A61B5/01A61B5/021A61B5/0476A61B5/1112A61B5/1118A61B5/1123A61B5/14532A61B5/14551A61B5/4815A61B5/4866A61B5/4872A61B5/6898A61B5/7267A61B5/749G06F19/345G06N5/022G09B5/125A61B2562/0219
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Quick Facts
Patent No.
US 9,538,948
App. No.
15/214,130
Granted
Jan 10, 2017
Kind
B2
Abstract

A system and method that enables a person to unobtrusively assess their cognitive function from mobile device usage. The method records on the mobile device the occurrence and timing of user events comprising the opening and closing of applications resident on the device, the characters inputted, touch-screen gestures made, and voice inputs used on those applications, performs the step of learning a function mapping from the mobile device recordings to measurements of cognitive function that uses a loss function to determine relevant features in the recording, identifies a set of optimal weights that produce a minimum of the loss function, creates a function mapping using the optimal weights, and performs the step of applying the learned function mapping to a new recording on the mobile device to compute new cognitive function values.

Claims (34)

1. A computer implemented method to quantify the effect of social interaction, mobility, physiology, cognitive stimulation, and diet on a person's brain health, said method comprising the steps of:

a. recording at a mobile computing device an in vivo input associated with a measurement of one of social interaction, mobility, physiology, cognitive stimulation, and diet;

b. recording interaction inputs associated with one or more interactions of the person with said mobile computing device;

c. executing a learning function mapping to compute a brain health measure based on said person's interaction inputs, wherein said brain health measure is one of a neuropsychological benchmark test;

d. performing the learning function mapping from said recording associated with the in vivo input to said computed brain health measure; and

e. outputting an attribution to said brain health measure that is explained by said in vivo input.

2. The method of claim 1 , wherein the one or more interactions includes at least one of: applications opened, inputs typed, gesture patterns used on a touch screen, body motions, and voice input.

3. The method of claim 1 , wherein the mobile computing device is one of: a smart phone, a tablet computer, and a wearable mobile computing device.

4. The computer implemented method of claim 1 , wherein the social interaction measurement is one of length, duration, frequency, volume, sentiment, and mood associated with an incoming call, an outgoing call, a text, and an email message.

5. The computer implemented method of claim 1 , wherein the social interaction measurement is from one of an email, text, phone, or other communication application on said mobile computing device.

6. The computer implemented method of claim 1 , wherein the mobility measurement is one of intensity, duration, and frequency of locomotor activity.

7. The computer implemented method of claim 1 , wherein the mobility measurement is from one of an accelerometer application and a gyroscope application on said mobile computing device.

8. The computer implemented method of claim 1 , wherein the physiology measurement is one of a heart rate, a blood pressure, a blood oxymetry, a blood glucose, a body temperature, a body fat, a body weight, a sleep duration and quality, and an electroencephalogram.

9. The computer implemented method of claim 1 , wherein the cognitive stimulation measurement is one of URLs visited, books and articles read online, and games played on said mobile computing device.

10. The computer implemented method of claim 1 , wherein the cognitive stimulation measurement is one of a setting of, or a recording from, a brain stimulation device.

11. The computer implemented method of claim 1 , wherein the diet measurement is one of a caloric intake, a nutritional value, a food type, alcohol, caffeine, a drug, a medication, and a vitamin consumed.

12. A computer-readable medium comprising instructions that when executed by a processor running on a computing device perform a method to quantify the effect of social interaction, mobility, physiology, cognitive stimulation, and diet on a person's brain health, said method comprising the steps of:

a. recording at a mobile computing device an in vivo input associated with a measurement of one of social interaction, mobility, physiology, cognitive stimulation, and diet;

b. recording interaction inputs associated with one or more interactions of the person with said mobile computing device;

c. executing a learning function mapping to compute a brain health measure based on said person's interaction inputs, wherein said brain health measure is one of a neuropsychological benchmark test;

d. performing the learning function mapping from said recording associated with the in vivo input to said computed brain health measure; and

e. outputting an attribution to said brain health measure that is explained by said in vivo input.

13. The computer-readable medium of claim 12 , wherein the one or more interactions includes at least one of: applications opened, inputs typed, gesture patterns used on a touch screen, body motions, and voice input.

14. The computer-readable medium of claim 12 , wherein the mobile computing device is one of: a smart phone, a tablet computer, and a wearable mobile computing device.

15. A computer-implemented system for assessing the effect of social interaction, mobility, physiology, cognitive stimulation, and diet on a person's brain health, the system comprising:

a. a mobile computing device that:

records an in vivo input associated with a measurement of one of social interaction, mobility, physiology, cognitive stimulation, and diet; and

records interaction inputs associated with one or more interactions of the person with said mobile computing device; and

b. a computing system comprising a processor, said computing system:

computing a brain health measure by performing a learning function mapping from said interaction inputs to said brain health measure, wherein said brain health measure is a neuropsychological benchmark test;

performing the learning function mapping from said in vivo input to said computed brain health measure; and

outputting an attribution to said brain health measure that is explained by said in vivo input.

16. The system of claim 15 , wherein the one or more interactions includes at least one of: applications opened, inputs typed, gesture patterns used on a touch screen, body motions, and voice input.

17. The system of claim 15 , wherein the mobile computing device is one of: a smart phone, a tablet computer, and a wearable mobile computing device.

Assignments (6)
RELEASE OF SECURITY INTEREST Recorded Jul 21, 2026
From: JPMORGAN CHASE BANK
To: SONDERMIND INC.
Reel/Frame 075344/0500 →
SECURITY INTEREST Recorded Jul 14, 2026
From: SONDERMIND INC.; SONDERMIND PROVIDER NETWORK, LLC
To: HERCULES CAPITAL, INC., AS AGENT
Reel/Frame 075267/0062 →
SECURITY INTEREST Recorded Jun 11, 2024
From: SONDERMIND INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 067691/0035 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 17, 2023
From: MINDSTRONG, INC.
To: SONDERMIND INC.
Reel/Frame 063673/0023 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2020
From: MINDSTRONG, LLC
To: MINDSTRONG, INC.
Reel/Frame 051750/0160 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 5, 2016
From: PAUL DAGUM
To: MINDSTRONG, LLC
Reel/Frame 040817/0290 →
Continuity (2)
Continuation 14059682 · Oct 22, 2013
Related Publication 20160324457A1 · Nov 10, 2016