DETECTING DEPRESSION VIA MOBILE DEVICE DATA

• US 20160262681A1
• Filed: 03/13/2015
• Published: 09/15/2016
• Est. Priority Date: 03/13/2015
• Status: Abandoned Application

• Current Assignee: AT&T Mobility II LLC (AT&T, Inc.)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.), AT&T Mobility II LLC (AT&T, Inc.)
• Inventors: PATTERSON, DAVID, Fix, Jeremy, Meredith, Sheldon Kent
• Application Number:
  US14/657,707
• Publication Number:
  US 20160262681A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• 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: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A method, computer-readable medium, and apparatus for detecting a likelihood of depression of a user are disclosed. A method includes a processor for determining a calling pattern and a mobility pattern of a mobile device of the user during a first time period, detecting a likelihood of depression when the calling pattern of the mobile device during the first time period is indicative of a decline in communications as compared to a reference calling pattern and when the mobility pattern of the mobile device during the first time period is indicative of a decline in movement as compared to a reference mobility pattern, and generating a warning message when the likelihood of depression is detected.

Claims

1. A method for detecting a likelihood of depression of a user, comprising:

determining, by a processor, a calling pattern of a mobile device of the user during a first time period;

determining, by the processor, a mobility pattern of the mobile device of the user during the first time period;

detecting, by the processor, the likelihood of depression when the calling pattern of the mobile device during the first time period is indicative of a decline in communications as compared to a reference calling pattern and when the mobility pattern of the mobile device during the first time period is indicative of a decline in movement as compared to a reference mobility pattern; and

generating, by the processor, a warning message when the likelihood of depression is detected.

2. The method of claim 1, wherein the reference calling pattern is based upon historic calling records of a plurality of mobile devices during a second time period, and wherein the reference mobility pattern is based upon historic mobility records of the plurality of mobile devices during the second time period.

3. The method of claim 1, wherein the reference calling pattern is based upon historic calling records of the mobile device during a second time period, and wherein the reference mobility pattern is based upon historic mobility records of the mobile device during the second time period.

4. The method of claim 1, wherein the detecting comprises:

calculating a depression score, wherein the depression score is based on;

a comparison of the calling pattern of the mobile device during the first time period with the reference calling pattern; and

a comparison of the mobility pattern of the mobile device during the first time period with the reference mobility pattern; and

detecting the likelihood of depression when the depression score exceeds a threshold.

5. The method of claim 4, wherein the comparison of the calling pattern of the mobile device during the first time period with the reference calling pattern comprises:

comparing an average number of minutes of calls during a time interval of a second time period associated with the reference calling pattern with an average number of minutes of calls of the mobile device during a same time interval of the first time period.

6. The method of claim 5, wherein the average number of minutes of calls during the time interval of the second time period associated with the reference calling pattern comprises an average number of minutes of calls involving non-family members and non-work contacts during the time interval of the second time period associated with the reference calling pattern, and wherein the average number of minutes of calls of the mobile device during the same time interval of the first time period comprises an average number of minutes of calls involving non-family members and non-work contacts during the same time interval of the first time period.

7. The method of claim 4, wherein the comparison of the calling pattern of the mobile device during the first time period with the reference calling pattern comprises:

comparing an average number of calls during a time interval of a second time period associated with the reference calling pattern with an average number of calls of the mobile device during a same time interval of the first time period.

8. The method of claim 7, wherein the average number of calls during the time interval of the second time period associated with the reference calling pattern comprises an average number of calls involving non-family members and non-work contacts during the time interval of the second time period associated with the reference calling pattern, and wherein the average number of calls of the mobile device during the same time interval of the first time period comprises an average number of calls involving non-family members and non-work contacts during the same time interval of the first time period.

9. The method of claim 4, wherein the comparison of the mobility pattern of the mobile device during the first time period with the reference mobility pattern comprises:

comparing an average distance travelled during a time interval of a second time period associated with the reference mobility pattern with a distance travelled by the mobile device during a same time interval of the first time period.

10. The method of claim 4, wherein the comparison of the mobility pattern of the mobile device during the first time period with the reference mobility pattern comprises:

comparing a measure of time spent away from areas surrounding a home location and a work location during a time interval of a second time period associated with the reference mobility pattern with a measure of time spent away from areas surrounding the home location and the work location by the mobile device during a same time interval of the first time period.

11. The method of claim 1, wherein the first time period is associated with weekend days, wherein the reference calling pattern and the reference mobility pattern are associated with a second time period, and wherein the second time period is associated with the weekend days.

12. The method of claim 4, wherein the decline in the calling pattern and the decline in the mobility pattern are weighted parameters that contribute to the depression score.

13. The method of claim 12, wherein the depression score is further based on:

a comparison of a number of email messages associated with the mobile device during the first time period with an average number of email messages during a time interval of a second time period associated with the reference calling pattern.

14. The method of claim 12, wherein the depression score is further based on:

a comparison of a number of text messages associated with the mobile device during the first time period with a number of text messages during a second time period.

15. The method of claim 1, further comprising:

sending the warning message to a device associated with a medical professional;

or

sending the warning message to a device associated with a caregiver of the user of the mobile device.

16. The method of claim 1, further comprising:

performing a remedial action in response to the detecting the likelihood of depression, wherein the remedial action comprises;

presenting a media item on the mobile device;

or

sending a message to a contact of the user of the mobile device suggesting to the contact to communicate with the user.

17. A tangible computer-readable medium storing instructions which, when executed by a processor, cause the processor to perform operations for detecting a likelihood of depression of a user, the operations comprising:

determining a calling pattern of a mobile device of the user during a first time period;

determining a mobility pattern of the mobile device of the user during the first time period;

detecting the likelihood of depression when the calling pattern of the mobile device during the first time period is indicative of a decline in communications as compared to a reference calling pattern and when the mobility pattern of the mobile device during the first time period is indicative of a decline in movement as compared to a reference mobility pattern; and

generating a warning message when the likelihood of depression is detected.

18. The tangible computer-readable medium of claim 17, wherein the processor is deployed in the mobile device.

19. A device for detecting a likelihood of depression of a user, comprising:

a processor; and

a computer-readable medium storing instructions which, when executed by the processor, cause the processor to perform operations, the operations comprising;

determining a calling pattern of a mobile device of the user during a first time period;

determining a mobility pattern of the mobile device of the user during the first time period;

detecting the likelihood of depression when the calling pattern of the mobile device during the first time period is indicative of a decline in communications as compared to a reference calling pattern and when the mobility pattern of the mobile device during the first time period is indicative of a decline in movement as compared to a reference mobility pattern; and

generating a warning message when the likelihood of depression is detected.

20. The device of claim 19, wherein the processor is deployed in an application server of a communication network.