Methods and apparatus to adjust content presented to an individual

• US 9,936,250 B2
• Filed: 05/16/2016
• Issued: 04/03/2018
• Est. Priority Date: 05/19/2015
• Status: Active Grant

• Current Assignee: Nielsen Consumer LLC (Nielsen Holdings plc)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Marci, Carl, Levine, Brian, Murray, Brendan
• Primary Examiner(s): Chin, Ricky
• Application Number:
  US15/155,543
• Publication Number:
  US 20160345060A1
• Time in Patent Office: 687 Days
• Field of Search: None
• CPC Class Codes: A61B 2503/12 Healthy persons not otherwise provided for, e.g. subjects of a marketing survey
• CPC Class Codes: A61B 3/112 for measuring diameter of pupils
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/0064 Body surface scanning
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• 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: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G06F 3/01 Input arrangements or combined input and output arrangements for interaction between user and computer G06F3/16 takes precedence
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/16 Human faces, e.g. facial parts, sketches or expressions
• CPC Class Codes: H04N 21/42201 biosensors, e.g. heat sensor for presence detection, EEG sensors or any limb activity sensors worn by the user input arrangements for interaction with the human body based on nervous system activity detection G06F3/015
• CPC Class Codes: H04N 21/4223 Cameras H04N23/00 takes precedence
• CPC Class Codes: H04N 21/4415 using biometric characteristics of the user, e.g. by voice recognition or fingerprint scanning cryptography using biological data H04L9/3231; authentication in networks using biometric H04L63/0861
• CPC Class Codes: H04N 21/44204 Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched monitoring of user activities for profile generation for accessing a video database G06F16/739; protecting generic digital content where the protection is independent of the precise nature of the content G06F21/10; arrangements for monitoring the use made of the broadcast services in broadcast systems H04H60/31
• CPC Class Codes: H04N 21/44213 Monitoring of end-user related data arrangements for monitoring the users' behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/44218 Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV program methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45
• CPC Class Codes: H04N 21/458 Scheduling content for creating a personalised stream, e.g. by combining a locally stored advertisement with an incoming stream; Updating operations, e.g. for OS modules ; time-related management operations arrangements for replacing or switching information during the broadcast or during the distribution H04H20/10
• CPC Class Codes: H04N 21/812 : involving advertisement data advertising per se G06Q30/02

Abstract

Methods, apparatus, systems and articles of manufacture to adjust content presented to an individual are disclosed. An example method includes measuring, via sensors, responses of an individual to content during a first time, determining response classifications based on a comparison of the responses and respective thresholds, determining a first mental classification of the individual based on combining the response classifications, determining a baseline during the first time, measuring additional responses to the content during a second time, determining additional response classifications based on a comparison of the additional responses to respective additional thresholds, adjusting the baseline based on the additional responses in the second time, determining a second mental classification of the individual based on combining the additional response classifications, determining a mental state of a user based on a similarity of the first mental classification and the second mental classification, and modifying the content based on the mental state.

Claims

1. A method to adjust content presented to an individual, the method comprising:

measuring, via a first modality sensor, a first response of the individual to first content during a first time frame;

determining a first response classification based on a first comparison of the first response and a first threshold;

measuring, via a second modality sensor, a second response of the individual to the first content during the first time frame;

determining a second response classification based on a second comparison of the second response to a second threshold;

determining a first mental classification of the individual based on combining the first response classification and the second response classification;

determining a first baseline during the first time frame, at least one of the first threshold or second threshold based on the first baseline;

measuring, via the first modality sensor, a third response of the individual to the first content during a second time frame;

measuring, via the second modality sensor, a fourth response of the individual to the first content during the second time frame;

adjusting the first baseline to a second baseline based on at least one of the third response or the fourth response in the second time frame;

adjusting at least one of the first threshold to a third threshold or second threshold to a fourth threshold based on the second baseline;

determining a third response classification based on a third comparison of the third response and the third threshold;

determining a fourth response classification based on a fourth comparison of the fourth response and the fourth threshold;

determining a second mental classification of the individual based on combining the third response classification and the fourth response classification;

determining a mental state of a user based on a degree of similarity between the first mental classification and the second mental classification; and

at least one of modifying the first content to include second content or replacing the first content with second content based on the mental state.

2. The method of claim 1, the first modality sensor including a galvanic skin response sensor.

3. The method of claim 2, the second modality sensor including a pupil dilation sensor.

4. The method of claim 3, further including generating a cognitive load index based on data from the pupil dilation sensor, the cognitive load index representative of how much of a maximum information processing capacity of the individual is being used.

5. The method of claim 1, the second time frame partially overlapping the first time frame.

6. The method of claim 1 further including:

measuring, via a third modality sensor, a fifth response of the individual to the first content during the first time frame;

determining a fifth response classification based on a fifth comparison of the fifth response and a fifth threshold, the first mental classification of the individual based on combining the first response classification and the second response classification further with the fifth response classification;

measuring, via the third modality sensor, a sixth response of the individual to the first content during the second time frame; and

determining a sixth response classification based on a sixth comparison of the sixth response and the fifth threshold, the second mental classification of the individual based on combining the third response classification and the fourth response classification further with the sixth response classification.

7. The method of claim 6, the third modality sensor including a facial action coding sensor.

8. The method of claim 6, the third modality sensor including an eye tracking sensor.

9. The method of claim 1, the second content to increase a positivity level of the mental state.

10. The method of claim 9, the second content to at least one of induce a purchase or increase a total spend amount on a purchase.

11. A system comprising:

a first modality sensor;

a second modality sensor;

a processor to;

measure, via the first modality sensor, a first response of an individual to first content during a first time frame;

determine a first response classification based on a first comparison of the first response and a first threshold;

measure, via the second modality sensor, a second response of the individual to the first content during the first time frame;

determine a second response classification based on a second comparison of the second response to a second threshold;

determine a first baseline during the first time frame, at least one of the first threshold or second threshold based on the first baseline;

determine a first mental classification of the individual based on combining the first response classification and the second response classification;

measure, via the first modality sensor, a third response of the individual to the first content during a second time frame;

measure, via the second modality sensor, a fourth response of the individual to the first content during the second time frame;

adjust the first baseline to a second baseline based on at least one of the third response or the fourth response in the second time frame;

adjust at least one of the first threshold to a third threshold or the second threshold to a fourth threshold based on the second baseline;

determine a third response classification based on a third comparison of the third response and the third threshold;

determine a fourth response classification based on a fourth comparison of the fourth response to the fourth threshold;

determine a second mental classification of the individual based on combining the third response classification and the fourth response classification;

determine a mental state of a user based on a degree of similarity between the first mental classification and the second mental classification; and

at least one of modify the first content to include second content or replace the first content with second content based on the mental state.

12. The system of claim 11, the first modality sensor including a galvanic skin response sensor.

13. The system of claim 12, the second modality sensor including a pupil dilation sensor, and the processor is to generate a cognitive load index based on data from the pupil dilation sensor, the cognitive load index representative of how much of a maximum information processing capacity of the individual is being used.

14. The system of claim 11, the second time frame partially overlapping the first time frame.

15. The system of claim 11, the processor to further:

measure, via a third modality sensor, a fifth response of the individual to the first content during the first time frame;

determine a fifth response classification based on a fifth comparison of the fifth response and a fifth threshold, the first mental classification of the individual based on combining the first response classification and the second response classification further with the fifth response classification;

measure, via the third modality sensor, a sixth response of the individual to the first content during the second time frame; and

determine a sixth response classification based on a sixth comparison of the sixth response and the fifth threshold, the second mental classification of the individual based on combining the third response classification and the fourth response classification further with the sixth response classification.

16. The system of claim 15, the third modality sensor including at least one of a facial action coding sensor or an eye tracking sensor.

17. The system of claim 11, the second content to increase a positivity level of the mental state, the second content to at least one of induce a purchase or increase a total spend amount on a purchase.

18. A tangible computer readable storage medium comprising instructions that, when executed, causes a processor of a content presentation device to at least:

measure, via a first modality sensor, a first response of an individual to first content during a first time frame;

determine a first response classification based on a first comparison of the first response and a first threshold;

measure, via a second modality sensor, a second response of the individual to the first content during the first time frame;

determine a second response classification based on a second comparison of the second response to a second threshold;

determine a first baseline during the first time frame, at least one of the first threshold or second threshold based on the first baseline;

determine a first mental classification of the individual based on combining the first response classification and the second response classification;

measure, via the first modality sensor, a third response of the individual to the first content during a second time frame;

measure, via the second modality sensor, a fourth response of the individual to the first content during the second time frame;

adjust the first baseline to a second baseline based on the third response or the fourth response in the second time frame;

adjust at least one of the first threshold to a third threshold or the second threshold to a fourth threshold based on the second baselines;

determine a third response classification based on a third comparison of the third response and the third threshold;

determine a fourth response classification based on a fourth comparison of the fourth response to the fourth threshold;

determine a second mental classification of the individual based on combining the third response classification and the fourth response classification;

determine a mental state of a user based on a degree of similarity between the first mental classification and the second mental classification; and

at least one of modify the first content to include second content or replace the first content with second content based on the mental state.

19. The medium of claim 18, wherein the instructions, when executed, further cause the processor to:

measure, via a third modality sensor, a fifth response of the individual to the first content during the first time frame;

determine a fifth response classification based on a fifth comparison of the fifth response and a fifth threshold, the first mental classification of the individual based on combining the first response classification and the second response classification further with the fifth response classification;

measure, via the third modality sensor, a sixth response of the individual to the first content during the second time frame; and

determine a sixth response classification based on a sixth comparison of the sixth response and the fifth threshold, the second mental classification of the individual based on combining the third response classification and the fourth response classification further with the sixth response classification.

20. The medium of claim 18, wherein the instructions, when executed, further cause the processor to generate a cognitive load index based on data from a pupil dilation sensor, the cognitive load index representative of how much of a maximum information processing capacity of the individual is being used.