Method and system for measuring and ranking an “engagement” response to audiovisual or interactive media, products, or activities using physiological signals

1. A method for rating media, the method comprising:

obtaining a first signal from a brain of an individual produced substantially while the individual is exposed to the media;

obtaining a second signal from a heart of the individual produced substantially concurrently with the first signal from the brain;

decomposing the first signal and the second signal into a frequency domain;

calculating with a processor, an engagement value based on a first mathematical relationship between (1) a first frequency and (2) a second frequency from the frequency domain of the first signal and a second mathematical relationship between (1) a third frequency from the frequency domain of the second signal and (2) a result of the first mathematical relationship;

comparing the engagement value with a reference value to determine a difference; and

rating the media based on the difference between the engagement value and the reference value.

2. The method of claim 1 , wherein at least one of the first frequency and the second frequency includes one or more of an alpha frequency or a theta frequency.

3. The method of claim 1 , wherein the engagement value is associated with an event in the media.

4. The method of claim 1 , wherein the second signal is sampled via a photoplethysmograph attached to a head of the individual.

5. The method of claim 1 , wherein multiple engagement values from multiple individuals associated with an event in the media are aggregated to form an engagement response to the event.

6. The method of claim 1 , wherein multiple engagement values from multiple individuals are included in a summated response vector identifying the number of persons that responded with engagement to the media.

7. The method of claim 1 , wherein the decomposing is accomplished using a Fast Fourier transform or a wavelet analysis.

8. The method of claim 7 , wherein the wavelet analysis is accomplished using a wavelet selected from a Mexican hat wavelet, a morlet wavelet, a daubechies wavelet, a beta wavelet, and a coiflet wavelet.

9. The method of claim 1 , further comprising calculating a derivative of the engagement value representing a change in engagement over time.

10. The method of claim 2 , wherein the engagement value is determined by calculating [heart rate/50]−[(theta−alpha)/(theta+alpha)].

11. The method of claim 1 , wherein a length of each heart beat is monitored.

12. The method of claim 1 wherein the first signal includes an alpha frequency, a beta frequency, a delta frequency, a theta frequency and a total EEG power, the second signal includes a heart rate, and the engagement value is calculated by contrasting the heart rate with one or more of:

θ−α,

θ,

θ/α,

Δ/α,

β/α, or

total EEG power/α.

13. The method of claim 1 wherein the first signal includes an alpha frequency, a beta frequency, a delta frequency, a theta frequency and a total EEG power, the second signal includes a heart beat, and the engagement value is calculated by contrasting a length of the heart beat with one or more of:

α,

α/θ,

α/β,

α/Δ,

α/total EEG power, or

(α−θ)/(α+θ).

14. The method of claim 1 , wherein the media includes one or more of a television broadcast, a video game, an audiovisual advertisement, a board game, a card game, a live action event, a print advertisement or a web advertisement.

15. The method of claim 1 , further comprising:

identifying a point in time corresponding to the engagement value;

identifying an event of the media occurring substantially concurrently with the point in time;

correlating the engagement value with the event; and

aligning the engagement value to the media.

16. A tangible machine readable storage medium comprising machine readable instructions which, when read, cause a machine to at least:

decompose a first signal from a brain of an individual and a second signal from a heart of the individual into a frequency domain, the first and second signal produced substantially concurrently and while the individual is exposed to media;

calculate an engagement value based on: (1) a first mathematical relationship between (a) a first frequency and (b) a second frequency from the frequency domain of the first signal and (2) a second mathematical relationship between (a) a third frequency from the frequency domain of the second signal and (b) a result of the first mathematical relationship;

compare the engagement value with a reference value to determine a difference; and

rate the media based on the difference between the engagement value and the reference value.

17. The medium of claim 16 , wherein at least one of the first frequency and the second frequency includes one or more of an alpha frequency or a theta frequency.

18. The medium of claim 16 , wherein the first signal includes an alpha frequency, a beta frequency, a delta frequency, a theta frequency and a total EEG power, the second signal includes a heart beat, and the engagement value is calculated by contrasting a length of the heart beat with one or more of:

α,

α/θ,

α/β,

α/Δ,

α/total EEG power, or

(α−θ)/(α+θ), wherein α, β, Δ, & θ are each found in the first signal.

19. The medium of claim 16 , wherein the decomposing of the first signal and the second signal comprises using one or more of a fast Fourier transform or a wavelet analysis.

20. The medium of claim 16 , wherein the media includes one or more of a television program, a video game, an audiovisual advertisement, a board game, a card game, a live action event, a print advertisement or a web advertisement.

21. The medium of claim 16 , wherein the machine is further caused to:

align the signal relative to the media;

create a first aligned engagement value corresponding to a first event based on the alignment; and

compare the first aligned engagement value with a second aligned engagement value corresponding to a second event in time.

22. A system for rating media, the system comprising:

a data collector to obtain a first signal from a brain of an individual produced substantially while the individual is exposed to the media and a second signal from a heart of the individual produced substantially while the individual is exposed to the media; and

a processor to:

decompose the first signal and the second signal into a frequency domain;

calculate an engagement value based on a first mathematical relationship between (1) a first frequency and (2) a second frequency from the frequency domain of the first signal and a second mathematical relationship between (1) a third frequency from the frequency domain of the second signal and (2) a result of the first mathematical relationship;

compare the engagement value with a reference value to determine a difference; and

rate the media based on the difference between the engagement value and the reference.

23. The system of claim 22 , wherein the data collector comprises one or more sensors included in an integrated sensor headset to measure a signal from the individual stimulated by the media.

24. The method of claim 1 , wherein the reference value is determined by a developer of the media.

25. The method of claim 1 , wherein the reference value is an average of a plurality of previously calculated engagement values for the media.

26. The method of claim 1 , wherein the first mathematical relationship includes a ratio of (1) a first difference between the second frequency and the first frequency to (2) a sum of the first frequency and the second frequency.

27. The method of claim 26 , wherein the second mathematical relationship includes a second difference between the third frequency and the result of the first mathematical relationship.

28. The method of claim 27 , wherein the second mathematical relationship includes a percentage of the third frequency.

29. The method of claim 3 , wherein the event is classified as a specific type of event using a mathematical transform to compare the event with one or more other events.

30. The method of claim 29 , wherein the mathematical transform includes using an average.

31. The method of claim 29 , wherein the mathematical transform includes a first order derivative.

32. The method of claim 29 , wherein the mathematical transform includes a second order derivative.

33. The method of claim 29 , wherein the mathematical transform includes a polynomial approximation.

34. The method of claim 29 , wherein the mathematical transform includes a standard deviation from a mean.

35. The method of claim 29 , wherein the mathematical transform includes a standard deviation of derivatives from a mean.

36. The method of claim 29 , wherein the mathematical transform includes vectors and a positive derivative vector indicates an exciting type of event and a negative derivative vector indicates an unexciting type of event.