Relationship analysis utilizing biofeedback information

• US 10,089,074 B2
• Filed: 07/07/2017
• Issued: 10/02/2018
• Est. Priority Date: 07/08/2016
• Status: Active Grant

• Current Assignee: Ontolead, Inc.
• Original Assignee: Ontolead, Inc.
• Inventors: Motamedi, Firoozeh, Yadegari, Shahrokh
• Primary Examiner(s): Negin, Russell S
• Application Number:
  US15/644,601
• Publication Number:
  US 20180011689A1
• Time in Patent Office: 452 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/167 Personality evaluation
• CPC Class Codes: G06F 7/02 Comparing digital values G06F7/06, G06F7/22, G06F7/38 take precedence

Abstract

First sensor data may be acquired from a first galvanic skin response sensor monitoring a first user. Second sensor data may be acquired from a second galvanic skin response sensor monitoring a second user. At least one programmable processor may generate a compatibility score between the first user and the second user. The generating may include executing a compatibility algorithm to generate the compatibility score based at least on a comparison of at least one type of response contained in the first sensor data and the second sensor data. A client device may generate an electronic indication of the compatibility score.

Claims

1. A computer program product comprising a non-transitory, machine-readable medium storing instructions which, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:

receiving, at the at least one programmable processor, first sensor data acquired from a first galvanic skin response sensor monitoring a first user;

receiving, at the at least one programmable processor, second sensor data acquired from a second galvanic skin response sensor monitoring a second user;

receiving user input from the first user specifying a desired feature of the second user;

generating, at the at least one programmable processor, a compatibility score between the first user and the second user, the generating comprising;

executing a compatibility algorithm that performs an ongoing analysis of the first sensor data to generate the compatibility score based at least on a comparison of at least one type of response contained in the first sensor data and the second sensor data, where the monitoring of the first user is performed simultaneous with the ongoing analysis of the first sensor data; and

increasing, by the compatibility algorithm, the compatibility score when the second sensor data reflects the desired feature; and

generating, at a client device, an electronic indication of the compatibility score.

2. The computer program product of claim 1, wherein the at least one type of response includes a tonic response and a phasic response, wherein the first sensor data includes first phasic data and first tonic data, and wherein the second sensor data includes second phasic data and second tonic data, the phasic data corresponding to the phasic response and the tonic data corresponding to the tonic response, the operations further comprising:

separating, by at least a first discrete decomposition analysis, the first sensor data into a first tonic response and a first phasic response; and

separating, by at least a second discrete decomposition analysis, the second sensor data into a second tonic response and a second phasic response.

3. The computer program product of claim 1, further comprising extracting first tonic data and second tonic data from the first sensor data and the second sensor data, wherein the comparison is further based on the first tonic data and the second tonic data.

4. The computer program product of claim 3, further comprising extracting first phasic data and second phasic data from the first sensor data and the second sensor data, wherein the comparison is further based on the first phasic data and the second phasic data.

5. The computer program product of claim 4, further comprising generating the compatibility score by at least performing statistical analysis of first tonic data and second tonic data extracted from the first sensor data and the second sensor data.

6. The computer program product of claim 1, further comprising generating the compatibility score by at least performing statistical analysis of first phasic data and second phasic data extracted from the first sensor data and the second sensor data.

7. The computer program product of claim 1, further comprising:

performing a first statistical analysis of first tonic data and second tonic data extracted from the first sensor data and the second sensor data; and

performing a second statistical analysis of first phasic data and second phasic data extracted from the first sensor data and the second sensor data, wherein the compatibility score is based at least on the first statistical analysis and the second statistical analysis.

8. The computer program product of claim 7, the generating of the compatibility score further comprising:

performing a first linear regression analysis of the tonic data of the first user and the second user; and

calculating a first ratio of a tonic variance between the first user and the second user.

9. The computer program product of claim 8, the generating of the compatibility score further comprising:

performing a second linear regression analysis of the phasic data of the first user and the second user; and

calculating a second ratio of a phasic variance between the first user and the second user.

10. The computer program product of claim 9, wherein the compatibility score is proportional to an average of the first ratio and the second ratio, and the compatibility score is proportional to a measure of agreement in the first linear regression analysis or the second linear regression analysis for the first user and the second user.

11. The computer program product of claim 10, wherein at least one of the first sensor data or the second sensor data includes an event window containing a number of peaks in the first sensor data or the second sensor data.

12. The computer program product of claim 11, further comprising clustering the number of peaks in the first sensor data or the second sensor data to generate an event value for a portion of the first sensor data or the second sensor data, the clustering comprising:

filtering the first sensor data or the second sensor data to identify the number of peaks in the first sensor data or the second sensor data present in the event window that have an amplitude of at least a threshold value; and

generating the event value based on the number of the peaks in the event window, wherein the first ratio, the second ratio, or the linear regression analysis is based at least on the event value.

13. The computer program product of claim 1, further comprising:

receiving, from an input device, an evaluation characterizing the first sensor data or the second sensor data in an event window, wherein the compatibility score is based in part on the evaluation.

14. The computer program product of claim 1, further comprising:

selecting, by a first user at a graphical interface of an input device, the desired feature of the second user from a predefined list that includes a calmness or an excitability, wherein the compatibility algorithm generates the compatibility score based at least on an objective determination that the second user has the desired feature through analysis of the second sensor data.

15. The computer program product of claim 14, wherein the calmness or the excitability are determined based at least on statistical analysis of the tonic data or the phasic data of the second user.

16. The computer program product of claim 1, further comprising:

receiving permission settings entered at an input device by the first user; and

restricting, based at least on the permission settings, access by the second user to at least one of first sensor data or analyzed first sensor data generated by the compatibility algorithm when generating the compatibility score.

17. The computer program product of claim 1, further comprising:

filtering, by at least applying principle component analysis, the sensor data to exclude one or more types of the sensor data, the filtering removing at least one component of the sensor data as identified by the principle component analysis.

18. A system comprising:

a first galvanic skin response sensor configured to monitor a first user;

a second galvanic skin response sensor configured to monitor a second user;

at least one programmable processor; and

a non-transient machine-readable medium storing instructions which, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising;

receiving, at the at least one programmable processor, first sensor data acquired from the first galvanic skin response sensor monitoring the first user;

receiving, at the at least one programmable processor, second sensor data acquired from the second galvanic skin response sensor monitoring the second user;

receiving user input from the first user specifying a desired feature of the second user;

generating, at the at least one programmable processor, a compatibility score between the first user and the second user, the generating comprising;

executing a compatibility algorithm that performs an ongoing analysis of the first sensor data to generate the compatibility score based at least on a comparison of at least one type of response contained in the first sensor data and the second sensor data, where the monitoring of the first user is performed simultaneous with the ongoing analysis of the first sensor data; and

increasing, by the compatibility algorithm, the compatibility score when the second sensor data reflects the desired feature; and

generating, at a client device, an electronic indication of the compatibility score.

19. The system of claim 18, further comprising a complementary device configured to receive user input and add an evaluation to the first sensor data or the second sensor data, the evaluation providing a numerical weight to the first sensor data or the second sensor data when generating the compatibility score.