Methods and apparatus for identifying potentially seizure-inducing virtual reality content

• US 10,067,565 B2
• Filed: 09/29/2016
• Issued: 09/04/2018
• Est. Priority Date: 09/29/2016
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Ramaprakash, Nishanth, Rao, Sreenidhi Koti Ananda
• Primary Examiner(s): MARINELLI, PATRICK
• Application Number:
  US15/279,820
• Publication Number:
  US 20180088669A1
• Time in Patent Office: 705 Days
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/378 Visual stimuli
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61M 2021/0027 by the hearing sense
• CPC Class Codes: A61M 2021/005 images, e.g. video
• CPC Class Codes: A61M 21/00 Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/3317 Electromagnetic, inductive or dielectric measuring means
• CPC Class Codes: A61M 2205/3375 Acoustical, e.g. ultrasonic, measuring means
• CPC Class Codes: A61M 2205/3561 local, e.g. within room or hospital
• CPC Class Codes: A61M 2205/3584 using modem, internet or bluetooth
• CPC Class Codes: A61M 2205/3592 using telemetric means, e.g. radio or optical transmission
• CPC Class Codes: A61M 2205/505 Touch-screens; Virtual keyboard or keypads; Virtual buttons; Soft keys; Mouse touches
• CPC Class Codes: A61M 2205/507 Head Mounted Displays [HMD]
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/702 automatically during use
• CPC Class Codes: A61M 2205/80 : voice-operated command
• CPC Class Codes: A61M 2230/005 : Parameter used as control input for the apparatus
• CPC Class Codes: A61M 2230/04 : Heartbeat characteristics, e.g. ECG, blood pressure modulation
• CPC Class Codes: A61M 2230/10 : Electroencephalographic signals
• CPC Class Codes: A61M 2230/14 : Electro-oculogram [EOG]
• CPC Class Codes: A61M 2230/65 : Impedance, e.g. conductivity, capacity
• CPC Class Codes: G06F 1/163 : Wearable computers, e.g. on a belt
• 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 2218/12 : Classification; Matching
• CPC Class Codes: G06F 3/011 : Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• 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: G06T 11/60 : Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/20208 : High dynamic range [HDR] image processing
• CPC Class Codes: G06T 5/92 : based on global image properties
• CPC Class Codes: G06V 20/46 : Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
• CPC Class Codes: G06V 40/15 : Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

Methods and apparatus for identifying potentially seizure-inducing virtual reality content are disclosed herein. An example apparatus includes a virtual reality presentation device to display virtual reality content for exposure to a user and a neurological data collector to access first neurological response data collected from the user during exposure to the virtual reality content. The example apparatus includes a predictor to generate a prediction on a likelihood that a portion of the virtual reality content will trigger a seizure based on a first vector characterizing the portion and the first neurological response data. The example apparatus includes a content modifier to modify the portion of the virtual reality content into modified virtual reality content in response to the prediction. The content modifier is to transmit the modified virtual reality content to the virtual reality presentation device.

Claims

1. An apparatus for analyzing virtual reality content, the apparatus comprising:

a virtual reality presentation device to display the virtual reality content for exposure to a user;

a neurological data collector to access first neurological response data collected from the user during exposure to the virtual reality content;

a predictor to generate a prediction on a likelihood that a portion of the virtual reality content will trigger a seizure based on a first vector characterizing the portion and the first neurological response data; and

a content modifier to modify the portion of the virtual reality content into modified virtual reality content in response to the prediction, the content modifier to transmit the modified virtual reality content to the virtual reality presentation device.

2. The apparatus of claim 1, further including a video analyzer to generate the first vector based on a visual parameter of the portion of the virtual reality content.

3. The apparatus of claim 1, wherein the predictor is to further generate the prediction based on a second vector and second neurological response data, the second vector and the second neurological response data associated with a second portion of the virtual reality content presented prior to the presentation of the portion of the virtual reality content.

4. The apparatus of claim 1, wherein the portion of the virtual reality content includes a plurality of video frames and the content modifier is to modify the portion of the virtual reality content by adjusting at least one of a saturation value, a hue value, or a luminance of at least one of the video frames.

5. The apparatus of claim 1, wherein the neurological data collector is to access second neurological response data collected from the user, the second neurological response data collected during presentation of the modified virtual reality content, and further including a feedback analyzer, the feedback analyzer to determine a modification for the modified virtual reality content based on the second neurological response data.

6. The apparatus of claim 5, wherein the content modifier is to stop a transmission of the virtual reality content based on the second neurological response data.

7. The apparatus of claim 1, further including an alert generator to generate an alert based on the prediction.

8. A method for analyzing virtual reality content, the method comprising:

accessing, by executing an instruction with at least one processor, first neurological data collected from a user during exposure of the user to the virtual reality content;

generating, by executing an instruction with the at least one processor, a prediction on a likelihood that a portion of the virtual reality content will trigger a seizure based on a first vector characterizing the portion of the virtual reality content and first neurological response data;

modifying, by executing an instruction with the at least one processor, the portion of the virtual reality content to generate modified virtual reality content in response to the prediction; and

transmitting, by executing an instruction with the at least one processor, the modified virtual reality content to a virtual reality presentation device.

9. The method of claim 8, further including generating the first vector based on a visual parameter or an audio parameter of the portion of the virtual reality content.

10. The method of claim 8, wherein the generating of the prediction is further based on a second vector and second neurological response data, the second vector and the second neurological response data associated with a second portion of the virtual reality content presented prior to the presentation of the portion of the virtual reality content.

11. The method of claim 8, wherein the portion of the virtual reality content includes a plurality of video frames and the modifying of the portion of the virtual reality content includes adjusting at least one of a saturation value, a hue value, or a luminance of at least one of the video frames.

12. The method of claim 8, further including:

accessing second neurological response data collected during presentation of the modified virtual reality content; and

modifying the modified virtual reality content based on the second neurological data.

13. The method of claim 12, wherein the modifying of the modified virtual reality content includes stopping a transmission of the virtual reality content.

14. The method of claim 8, further including generating an alert based on the prediction.

15. A non-transitory computer readable storage medium comprising instructions that, when executed, cause a machine to at least:

access first neurological data collected from a user during exposure of the user to virtual reality content;

generate a prediction on a likelihood that the virtual reality content will trigger a seizure based on a first vector characterizing the virtual reality content and the first neurological response data;

modify at least a portion of the virtual reality content to generate modified virtual reality content in response to the prediction; and

transmit the modified virtual reality content to a virtual reality presentation device.

16. The non-transitory computer readable storage medium of claim 15, wherein the instructions, when executed, further cause the machine to generate the first vector based on a visual parameter or an audio parameter of the virtual reality content.

17. The non-transitory computer readable storage medium of claim 15, wherein the instructions, when executed, further cause the machine to generate the prediction based on a second vector and second neurological response data, the second vector and the second neurological response data associated with earlier presented virtual reality content.

18. The non-transitory computer readable storage medium of claim 15, wherein the virtual reality content includes a plurality of video frames, and the instructions, when executed, further cause the machine to modify the at least the portion of the virtual reality content by adjusting at least one of a saturation value, a hue value, or a luminance of at least one of the frames.

19. The non-transitory computer readable storage medium of claim 18, wherein the instructions, when executed, further cause the machine to access second neurological response data collected during presentation of the modified virtual reality content and to modify the modified virtual reality content based on the second neurological data.

20. The non-transitory computer readable storage medium of claim 15, wherein the instructions, when executed, further cause the machine to generate an alert based on the prediction.