Automated systems for improving communication at the human-machine interface

• US 9,355,366 B1
• Filed: 12/12/2012
• Issued: 05/31/2016
• Est. Priority Date: 12/19/2011
• Status: Active Grant

• Current Assignee: Hello-Hello Incorporated
• Original Assignee: Hello-Hello Incorporated
• Inventors: Young, Charles E.
• Primary Examiner(s): Hill, Stanley K
• Assistant Examiner(s): Fink, Thomas
• Application Number:
  US13/712,906
• Time in Patent Office: 1,266 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 18/2413 based on distances to training or reference patterns
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06V 10/82 using neural networks
• CPC Class Codes: G06V 20/41 Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 40/174 Facial expression recognition

Abstract

Apparatuses and methods for measuring audience response to a presentation such as an advertisement. Software is trained using a feedback loop to correlate biometric data, such as eye tracking, facial recognition, or pupil dilation, with emotion, attention, memory, and/or meaning remembered by a viewer as measured by methods related to the Picture Sorts technique. The trained software then enables a device that uses biometric measurement to detect and measure such qualities in a viewer as the presentation is being viewed. In this way, unlike existing systems, the attention, memory and both primary and compound emotions of the viewer can be measured, enabling key moments of the presentation to be detected.

Claims

1. A method for identifying a moment of a presentation, the method comprising:

displaying a presentation to a plurality of viewers;

obtaining biometric data from the plurality of viewers during the displaying step;

showing selections from the presentation to the viewers after the displaying step;

collecting self-reported responses by each viewer regarding the viewer'"'"'s memory of what the viewer'"'"'s state of mind was when the viewer viewed each selection of the presentation during the displaying step;

synchronizing the biometric data and the self-reported responses with the content of the presentation;

training a system to correlate the biometric data obtained from the plurality of viewers with the self-reported responses obtained from the plurality of viewers;

subsequently displaying the presentation to a subsequent viewer;

obtaining biometric data from the subsequent viewer during the step of displaying the presentation to the subsequent viewer;

identifying a time of occurrence of a state of mind of the subsequent viewer from the biometric data obtained from the subsequent viewer using the trained system;

and identifying a moment of the presentation by correlating the time of occurrence of the state of mind with the presentation.

2. The method of claim 1 wherein the state of mind is selected from a group consisting of emotion, positive emotion, negative emotion, simple emotion, primary emotion, compound emotion, memory, semantic memory, episodic memory, procedural memory, attention, engagement, branding, familiarity, liking, confusion, feelings, believability, relevance, persuasiveness, meaning, degree of fit or association with an anchoring concept such as a brand, and combinations thereof.

3. The method of claim 1 wherein the step of obtaining biometric data from the plurality of viewers comprises using a device selected from the group consisting of a brain wave machine, an EEG machine, a device for measuring heart rate, a device for measuring skin conductance, an fMRI machine, and a camera operating in the visible or infrared spectrum for tracking pupil dilation and/or the movements of eyes and/or facial muscles of the viewers.

4. The method of claim 1 wherein the step of obtaining biometric data from the subsequent viewer comprises using a device selected from the group consisting of a brain wave machine, an EEG machine, a device for measuring heart rate, a device for measuring skin conductance, an fMRI machine, and a camera operating in the visible or infrared spectrum for tracking pupil dilation and/or the movements of eyes and/or facial muscles of the viewers.

5. The method of claim 1 further comprising changing the content of the presentation shown to a viewer based on the biometric data obtained from that viewer while the presentation is being displayed to the viewer.

6. The method of claim 1 further comprising optimizing the presentation shown to a viewer with respect to a desired user experience, state of mind, learning or other perceptual effect based on the biometric data obtained from that viewer while the presentation is being displayed to the viewer.

7. The method of claim 1 wherein the system comprises a neural network or artificial intelligence system.

8. The method of claim 1 further comprising performing facial recognition of one of the plurality of viewers or the subsequent viewer.