SYSTEMS AND METHODS FOR COMPUTER-IMPLEMENTED SURVEYS

20250060813

18/940667

November 07, 2024

A survey method includes presenting a participant with a calibrating stimulus through a survey channel, wherein the survey channel can measure a reactive aspect of the participant's response to stimuli, measuring the reactive aspect of the participant's response to the calibrating stimulus through the survey channel, presenting the participant with a survey stimulus through the survey channel, measuring the reactive aspect of the participant's response to the survey stimulus through the survey channel, and evaluating the reactive aspect of the participant's response to the survey stimulus based on the reactive aspect of the participant's response to the calibrating stimulus. A computer-implemented survey method includes calibrating a survey system to determine individual cutoff times for individual participants in a survey, presenting survey content to the participants, monitoring the participants' responses to the survey content, and evaluating the individual participants' responses to the survey content based on the individual participants' cutoff times.

InsightsNow, Inc. (Corvallis, OR, US)

1. A method to measure a response to one or more stimuli, wherein the method is implemented by a computer, the method comprising: downloading an application on the computer; accessing the application on the computer, wherein the application is to monitor activities and provide one or more calibration stimuli; presenting a participant, via an interface communicatively coupled to the computer, with the one or more calibration stimuli through a channel comprising software, electronic hardware or a combination of them, wherein the channel is capable of measuring a reactive aspect of a response of the participant to the one or more calibration stimuli, wherein the channel is coupled to the computer; measuring the reactive aspect of the response of the participant to the one or more calibration stimuli through the channel, wherein the reactive aspect is independent of correctness of the response; storing, in an electronic memory, the reactive aspect of the response of the participant to the one or more calibration stimuli; defining the reactive aspect as fast based on a target percentile cutoff of response times to the one or more calibration stimuli for the participant; presenting, via the interface, the participant with one or more test stimuli through the channel; measuring with the computer a speed of the response of the participant independent of correctness of the response; measuring the reactive aspect of the response of the participant to the one or more test stimuli through the channel based on the speed; storing, in the electronic memory, the reactive aspect of the response of the participant to the one or more test stimuli; evaluating the reactive aspect of the response of the participant which are stored to the one or more test stimuli based on the reactive aspect of the response of the participant which is stored to the one or more calibration stimuli, wherein the reactive aspect of the one or more test stimuli is slow if a response time of the participant to the one or more test stimuli is above the target percentile cutoff and fast if the response time is equal or below the target percentile cutoff; measuring, with the computer, a substantive aspect of the response of the participant to the one or more test stimuli; evaluating, with the computer, the substantive aspect of the response of the participant to the one or more test stimuli based on the reactive aspect of the response of the participant to the one or more calibration stimuli; aggregating responses from multiple participants to the one or more test stimuli based on an individual reactive aspect and an individual substantive aspect of an individual response from an individual participant of the multiple participants, wherein the participant is one of the multiple participants; applying weights to the responses which are aggregated to generate weighted responses; and summing the weighted responses to generate a response value indicative of the response of the participant to the one or more test stimuli.

2. The method of claim 1, wherein accessing comprises executing a weblink followed by entering authentication information of the participant.

3. The method of claim 1, wherein the participant is one of a human, an animal, or an artificial intelligence generated persona.

4. The method of claim 1, wherein the interface is one of graphical user interface (GUI), an optical interface, an acoustic interface, a verbal interface, a tactile interface, or an auditory interface.

5. The method of claim 1, wherein the target percentile cutoff is in a range from 85% percentile to 99th percentile.

6. The method of claim 1, wherein the one or more calibration stimuli and the one or more test stimuli comprise one or more questions.

7. The method of claim 1, wherein the one or more calibration stimuli and the one or more test stimuli comprise images.

8. The method of claim 1 further comprising: receiving, from a first machine coupled to the computer, a first passive information related to a sample subject whose response is being measured, wherein the first machine is to generate the first passive information faster than an awareness of the participant to the one or more calibration stimuli via the response of the participant through the interface.

9. The method of claim 8, wherein the first machine is one of an EEG machine, an fMRI machine, a PET machine, an EMG machine, a facial recognition camera, an eye tracker, a heat sensor, a machine to measure skin conductance, a machine to measure heart rate, a machine to measure breathing, or a speech recognition machine.

10. The method of claim 8 further comprising: receiving, from a second machine, a second passive information, wherein the second machine is configured to generate the second passive information faster than the awareness of the participant to the one or more test stimuli via the response of the participant through the interface.

11. The method of claim 10, wherein the second machine is same as the first machine or separate from the first machine.

12. The method of claim 10, wherein measuring of the reactive aspect to the one or more test stimuli is based on the first passive information, the second passive information, and/or the interface.

13. The method of claim 8, wherein the sample subject is one of an animal or an artificial intelligence generated persona.

14. The method of claim 1, wherein the substantive aspect is a first substantive aspect, wherein the one or more test stimuli is a first one or more test stimuli, wherein the response of the participant to the one or more test stimuli is a first response, wherein the method further comprises: measuring, with the computer, a second substantive aspect of a second response of the participant to a second one or more test stimuli; and evaluating, with the computer, the second substantive aspect of the second response of the participant to the second one or more test stimuli based on the reactive aspect of the response of the participant to the one or more calibration stimuli.

15. The method of claim 1, wherein aggregating the responses includes: dividing the multiple participants into groups based on discrete characterizations of the individual reactive aspect and the individual substantive aspect of the individual response of the individual participant of the multiple participants.

16. The method of claim 1, wherein the responses which are aggregated are arranged in a two-dimensional representation, and wherein the method further comprises transforming the two-dimensional representation to a one-dimensional representation.

17. The method of claim 1, further comprising dynamically adjusting, in real time, the one or more test stimuli based on the reactive aspect or the substantive aspect of the response of the participant to the one or more test stimuli.

18. The method of claim 1, further comprising dynamically adjusting, in real time, the one or more test stimuli based on characterization of the participant.

19. The method of claim 1, wherein the computer is one of a desktop computer, a laptop, a server, a cloud, or a smart device.

20. A non-transitory machine-readable storage media having machine-readable instructions stored thereon that when executed cause one or more machines to perform a method to measure a response to one or more stimuli, the method comprising: downloading an application on a computer; accessing the application on the computer, wherein the application is to monitor activities and provide one or more calibration stimuli; presenting a participant, via an interface communicatively coupled to the computer, with the one or more calibration stimuli through a channel comprising software, electronic hardware or a combination of them, wherein the channel is capable of measuring a reactive aspect of a response of the participant to the one or more calibration stimuli, wherein the channel is coupled to the computer; measuring the reactive aspect of the response of the participant to the one or more calibration stimuli through the channel, wherein the reactive aspect is independent of correctness of the response; storing, in an electronic memory, the reactive aspect of the response of the participant to the one or more calibration stimuli; defining the reactive aspect as fast based on a target percentile cutoff of response times to the one or more calibration stimuli for the participant; presenting, via the interface, the participant with one or more test stimuli through the channel; measuring with the computer a speed of the response of the participant independent of correctness of the response; measuring the reactive aspect of the response of the participant to the one or more test stimuli through the channel based on the speed; storing, in the electronic memory, the reactive aspect of the response of the participant to the one or more test stimuli; evaluating the reactive aspect of the response of the participant which are stored to the one or more test stimuli based on the reactive aspect of the response of the participant which is stored to the one or more calibration stimuli, wherein the reactive aspect of the one or more test stimuli is slow if a response time of the participant to the one or more test stimuli is above the target percentile cutoff and fast if the response time is equal or below the target percentile cutoff; measuring, with the computer, a substantive aspect of the response of the participant to the one or more test stimuli; evaluating, with the computer, the substantive aspect of the response of the participant to the one or more test stimuli based on the reactive aspect of the response of the participant to the one or more calibration stimuli; aggregating responses from multiple participants to the one or more test stimuli based on an individual reactive aspect and an individual substantive aspect of an individual response from an individual participant of the multiple participants, wherein the participant is one of the multiple participants; applying weights to the responses which are aggregated to generate weighted responses; and summing the weighted responses to generate a response value indicative of the response of the participant to the one or more test stimuli.

21. The non-transitory machine-readable storage media of claim 20, wherein accessing comprises executing a weblink followed by entering authentication information of the participant.

22. The non-transitory machine-readable storage media of claim 20, wherein the participant is one of a human, an animal, or an artificial intelligence generated persona.

23. The non-transitory machine-readable storage media of claim 20, wherein the interface is one of graphical user interface (GUI), an optical interface, an acoustic interface, a verbal interface, a tactile interface, or an auditory interface.

24. The non-transitory machine-readable storage media of claim 20, wherein the target percentile cutoff is in a range from 85% percentile to 99th percentile.

25. The non-transitory machine-readable storage media of claim 20 further comprising: receiving, from a first machine coupled to the computer, a first passive information related to a sample subject whose response is being measured, wherein the first machine is to generate the first passive information faster than an awareness of the participant to the one or more calibration stimuli via the response of the participant through the interface.

26. The non-transitory machine-readable storage media of claim 25, wherein the first machine is one of an EEG machine, an fMRI machine, a PET machine, an EMG machine, a facial recognition camera, an eye tracker, a heat sensor, a machine to measure skin conductance, a machine to measure heart rate, a machine to measure breathing, or a speech recognition machine.

27. The non-transitory machine-readable storage media of claim 25 further comprising: receiving, from a second machine, a second passive information, wherein the second machine is configured to generate the second passive information faster than the awareness of the participant to the one or more test stimuli via the response of the participant through the interface.

28. The non-transitory machine-readable storage media of claim 27, wherein the second machine is same as the first machine or separate from the first machine.

29. The non-transitory machine-readable storage media of claim 27, wherein measuring of the reactive aspect to the one or more test stimuli is based on the first passive information, the second passive information, and/or the interface.

30. A system comprising: a memory; a processor coupled to the memory; and a communication interface coupled to the processor and the memory, wherein the processor is operable to: download an application on a cloud; access the application on the cloud, wherein the application is to monitor activities and provide one or more calibration stimuli; present a participant, via an interface communicatively coupled to the cloud, with the one or more calibration stimuli through a channel comprising software, electronic hardware or a combination of them, wherein the channel is capable of measuring a reactive aspect of a response of the participant to the one or more calibration stimuli, wherein the channel is coupled to the cloud; measure the reactive aspect of the response of the participant to the one or more calibration stimuli through the channel, wherein the reactive aspect is independent of correctness of the response; store, in the memory, the reactive aspect of the response of the participant to the one or more calibration stimuli; define the reactive aspect as fast based on a target percentile cutoff of response times to the one or more calibration stimuli for the participant; present, via the interface, the participant with one or more test stimuli through the channel; measure with the cloud a speed of the response of the participant independent of correctness of the response; measure the reactive aspect of the response of the participant to the one or more test stimuli through the channel based on the speed; store, in the memory, the reactive aspect of the response of the participant to the one or more test stimuli; evaluate the reactive aspect of the response of the participant which are stored to the one or more test stimuli based on the reactive aspect of the response of the participant which is stored to the one or more calibration stimuli, wherein the reactive aspect of the one or more test stimuli is slow if a response time of the participant to the one or more test stimuli is above the target percentile cutoff and fast if the response time is equal or below the target percentile cutoff; measure, with the cloud, a substantive aspect of the response of the participant to the one or more test stimuli; evaluate, with the cloud, the substantive aspect of the response of the participant to the one or more test stimuli based on the reactive aspect of the response of the participant to the one or more calibration stimuli; aggregate responses from multiple participants to the one or more test stimuli based on an individual reactive aspect and an individual substantive aspect of an individual response from an individual participant of the multiple participants, wherein the participant is one of the multiple participants; apply weights to the aggregate responses which are aggregated to generate weighted responses; and sum the weighted responses to generate a response value indicative of the response of the participant to the one or more test stimuli.

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edspap.20250060813