Utilizing eye tracking to reduce power consumption involved in measuring affective response

• US 9,104,467 B2
• Filed: 10/13/2013
• Issued: 08/11/2015
• Est. Priority Date: 10/14/2012
• Status: Active Grant

• Current Assignee: Affectomatics ltd.
• Original Assignee: Ari M. Frank, Gil Thieberger
• Inventors: Frank, Ari M, Thieberger, Gil
• Primary Examiner(s): BUTLER, DENNIS
• Application Number:
  US14/052,758
• Publication Number:
  US 20140108842A1
• Time in Patent Office: 667 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/28 Supervision thereof, e.g. detecting power-supply failure by out of limits supervision
• CPC Class Codes: G06F 1/3206 Monitoring of events, devices or parameters that trigger a change in power modality
• CPC Class Codes: G06F 1/3212 Monitoring battery levels, e.g. power saving mode being initiated when battery voltage goes below a certain level
• CPC Class Codes: G06F 1/3234 Power saving characterised by the action undertaken
• CPC Class Codes: G06F 1/3296 by lowering the supply or operating voltage
• CPC Class Codes: G06F 2203/011 Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06F 3/015 Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G06F 9/46 Multiprogramming arrangements
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks

Abstract

Systems and methods that enable a reduction of the power consumption involved in measuring a user'"'"'s affective response to content. The reduction in power consumption is achieved by utilizing eye tracking to determine when a user is paying attention to content, and accordingly setting a mode of operation of a device that measures the user. Thus, by using different modes of operation, which are characterized by different energy consumption rates, the total power consumption of the device may be reduced, without loss of relevant measurements.

Claims

1. A controller configured to utilize eye tracking data to reduce power consumption of a device operative to measure affective response, comprising:

a first interface configured to receive a first tag that indicates a first duration during which to measure affective response to a first segment of content by operating the device in a first mode of operation;

a second interface configured to receive first eye tracking data of a user acquired in temporal vicinity of the first duration; and

a processor configured to;

analyze the first eye tracking data, determine that a gaze-based attention level to the first segment reaches a first predetermined threshold, and to select the first mode of operation for operating the device, during the first duration, to measure affective response of the user to the first segment;

the first interface is further configured to receive a second tag that indicates a second duration during which to measure affective response to a second segment of content by operating the device in a first mode of operation;

the second interface is further configured to receive second eye tracking data of the user acquired in temporal vicinity of the second duration;

the processor is further configured to;

analyze the second eye tracking data, determine that a gaze-based attention level to the second segment does not reach a second predetermined threshold, and to select a second mode of operation for operating the device, during the second duration, to measure affective response of the user to the second segment;

wherein power consumption of the device when operating in the first mode of operation is significantly higher than the power consumption of the device when operating in the second mode of operation.

2. The controller of claim 1, wherein the first and second tags further comprise representations of expected emotional responses to the segments.

3. The controller of claim 2, further comprising a training module configured to receive the first tag and measurements taken by the device during the first duration, and to train an emotional response model utilizing the first tag and the measurements.

4. The controller of claim 1, wherein the first tag depends on information conveyed by the first segment, and does not depend mainly on behavior of the user while being exposed to the first segment.

5. The controller of claim 1, wherein the first and second eye tracking data are acquired utilizing an image capturing device, and the device is a battery powered sensor that measures a physiological signal and is coupled to the user.

6. The controller of claim 1, wherein the device is a battery powered sensor that is coupled to the user and measures a physiological signal.

7. The controller of claim 1, wherein the first and second eye tracking data are collected substantially independently of whether the user is exposed to segments of content identified by tags;

and the device is a battery powered sensor that is mainly used to measure affective response of the user while exposed to segments identified by tags.

8. The controller of claim 1, wherein the first and second segments and the first and second tags are generated by an interactive computer game having an element whose actions in the game are at least partially controlled by the user.

9. The controller of claim 1, wherein the power consumption of the device when operating in the second mode of operation is essentially zero.

10. A method for utilizing eye tracking data to reduce power consumption of a device used to measure affective response, comprising:

receiving a first tag that indicates a first duration during which to measure affective response to a first segment of content by operating the device in a first mode of operation;

receiving a first indication, derived from first eye tracking data of a user acquired in temporal vicinity of the first duration, indicating that a gaze-based attention level to the first segment reaches a first predetermined threshold;

configuring the device to operate in the first mode of operation to measure affective response of the user to the first segment;

receiving a second tag that indicates a second duration during which to measure affective response to a second segment of content by operating the device in the first mode of operation;

receiving a second indication, derived from second eye tracking data of the user acquired in temporal vicinity of the second duration, indicating that a gaze-based attention level to the second segment does not reach a second predetermined threshold;

configuring the device to operate in a second mode of operation to measure affective response of the user to the second segment;

wherein power consumption of the device when operating in the first mode of operation is significantly higher than the power consumption of the device when operating in the second mode of operation.

11. The method of claim 10, wherein the first tag further comprises a representation of expected emotional response to being exposed to the first segment.

12. The method of claim 11, further comprising forwarding, to a module that trains an emotional response model, the first tag and measurements of the affective response of the user to being exposed to the first segment.

13. The method of claim 10, wherein the first tag depends on information conveyed by the first segment, and does not depend mainly on behavior of the user while being exposed to the first segment.

14. The method of claim 10, wherein the first and second eye tracking data are acquired utilizing an image capturing device and the device is a battery powered sensor that measures a physiological signal and is coupled to the user.

15. The method of claim 10, wherein the device is a battery powered sensor that is coupled to the user, and measures a physiological signal.

16. The method of claim 10, wherein the first and second eye tracking data are collected substantially independently of whether the user is exposed to segments of content identified by tags;

and the device is a battery powered sensor that is mainly used to measure affective response of the user while exposed to segments identified by tags.

17. The method of claim 10, further comprising generating the first segment and the first tag by an interactive computer game having an element whose actions in the game is at least partially controlled by the user;

wherein the first tag corresponds to a certain event occurring in the first segment.

18. A controller configured to utilize eye tracking data to reduce power consumption of a device operative to measure affective response, comprising:

a first interface configured to receive a first tag that indicates a first duration during which to measure affective response to a first segment of content by operating the device in a first mode of operation;

wherein the device is battery powered and measures a physiological signal;

a second interface configured to receive first eye tracking data of a user acquired in temporal vicinity of the first duration; and

a processor configured to analyze the first eye tracking data and determine that a gaze-based attention level to the first segment reaches a first predetermined threshold, and to select the first mode of operation for operating the device, during the first duration, to measure affective response of the user to the first segment;

the first interface is further configured to receive a second tag that indicates a second duration during which to measure affective response to a second segment of content by operating the device in a first mode of operation;

the second interface is further configured to receive second eye tracking data of the user acquired in temporal vicinity of the second duration;

the processor is further configured to analyze the second eye tracking data and determine that a gaze-based attention level to the second segment does not reach a second predetermined threshold, and to select a second mode of operation for operating the device, during the second duration, to measure affective response of the user to the second segment;

wherein power consumption of the device when operating in the first mode of operation is significantly higher than the power consumption of the device when operating in the second mode of operation.

19. The controller of claim 18, further comprising a training module configured to receive the first tag and measurements taken by the device during the first duration, and to train an emotional response model utilizing the first tag and the measurements;

wherein the first tag comprises a representation of an expected emotional response to the first segment.

20. The controller of claim 18, wherein the first and second tags depend on information conveyed by the first and second segments, and do not depend mainly on behavior of the user while being exposed to the first and second segments.