Haptic feedback for influencing user engagement level with remote educational content

Patent metadata

Field	Value
Publication number	US-12340708-B2
Application number	US-202117566194-A
Country	US
Kind code	B2
Filing date	Dec 30, 2021
Priority date	Dec 30, 2021
Publication date	Jun 24, 2025
Grant date	Jun 24, 2025

Abstract

Techniques are provided that employ haptic feedback to influence an engagement level of a remote user. One method comprises obtaining sensor data associated with a remote user interacting with educational content items; applying the sensor data to an analytics engine to obtain an engagement status indicating an engagement level of the remote user with the educational content items; and automatically initiating a provision of a haptic feedback signal to the remote user based on the engagement status. The engagement status may comprise an engagement score, and the haptic feedback signal may be sent to the remote user based on an evaluation of the engagement score relative to one or more threshold-based criteria. A type and/or an intensity of the haptic feedback signal can be based on one or more user preferences of the remote user.

First claim

What is claimed is:

1. A method, comprising:
obtaining sensor data associated with a plurality of remote users interacting with one or more educational content items;
applying the sensor data to at least one analytics engine to obtain an engagement status indicating a measured engagement level of the plurality of remote users interacting with the one or more educational content items, wherein the at least one analytics engine analyzes at least some of the applied sensor data to generate the measured engagement level of the plurality of remote users interacting with the one or more educational content items and compares (i) the measured engagement level of a first remote user of the plurality of remote users interacting with the one or more educational content items to (ii) the measured engagement level of one or more additional users of the plurality of remote users interacting with the one or more educational content items, wherein the generation of the measured engagement level of the plurality of remote users and the comparison of (i) the measured engagement level of the first remote user and (ii) the measured engagement level of the one or more additional users are performed substantially close in time to the plurality of remote users interacting with the one or more educational content items;
automatically initiating a provision of at least one haptic feedback signal to the first remote user, based at least in part on the engagement status, to increase the engagement status of the first remote user, wherein the at least one haptic feedback signal is provided to the first remote user in accordance with a haptic feedback plan of the first remote user, wherein the haptic feedback plan of the first remote user is generated during a training phase using (i) one or more machine learning models of the at least one analytics engine that generate the haptic feedback plan to increase the engagement status of the first remote user interacting with the one or more educational content items and (ii) training data labeled with a classification indicating the engagement level of a plurality of the remote users interacting with one or more educational content items; and
modifying at least one property, in the haptic feedback plan of the first remote user, of the at least one haptic feedback signal provided to the first remote user to increase the engagement status of the first remote user interacting with the one or more educational content items, wherein the modifying is based at least in part on feedback from one or more of the first remote user and a second user;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

2. The method of claim 1 , wherein the automatically initiating the provision of the at least one haptic feedback signal to the first remote user further comprises initiating the provision of one or more of an audio signal and a visual signal to the first remote user.

3. The method of claim 1 , wherein the engagement status comprises an engagement score and wherein the automatically initiating the provision of the at least one haptic feedback signal to the first remote user is performed based on an evaluation of the engagement score relative to one or more threshold-based criteria.

4. The method of claim 1 , further comprising applying the measured engagement level of the one or more additional users to the at least one analytics engine.

5. The method of claim 1 , further comprising employing feedback, from one or more of the first remote user and another user, indicating whether the engagement status of the first remote user generated by the at least one analytics engine is accurate, to update the at least one analytics engine.

6. The method of claim 1 , wherein one or more of a type and an intensity of the at least one haptic feedback signal provided to the first remote user is based on one or more user preferences of the first remote user.

7. The method of claim 1 , further comprising updating at least one of the one or more educational content items based at least in part on the measured engagement level of the first remote user and the one or more additional users.

8. An apparatus comprising:
at least one processing device comprising a processor coupled to a memory;
the at least one processing device being configured to implement the following steps:
obtaining sensor data associated with a plurality of remote users interacting with one or more educational content items;
applying the sensor data to at least one analytics engine to obtain an engagement status indicating a measured engagement level of the plurality of remote users interacting with the one or more educational content items, wherein the at least one analytics engine analyzes at least some of the applied sensor data to generate the measured engagement level of the plurality of remote users interacting with the one or more educational content items and compares (i) the measured engagement level of a first remote user of the plurality of remote users interacting with the one or more educational content items to (ii) the measured engagement level of one or more additional users of the plurality of remote users interacting with the one or more educational content items, wherein the generation of the measured engagement level of the plurality of remote users and the comparison of (i) the measured engagement level of the first remote user and (ii) the measured engagement level of the one or more additional users are performed substantially close in time to the plurality of remote users interacting with the one or more educational content items;
automatically initiating a provision of at least one haptic feedback signal to the first remote user, based at least in part on the engagement status, to increase the engagement status of the first remote user, wherein the at least one haptic feedback signal is provided to the first remote user in accordance with a haptic feedback plan of the first remote user, wherein the haptic feedback plan of the first remote user is generated during a training phase using (i) one or more machine learning models of the at least one analytics engine that generate the haptic feedback plan to increase the engagement status of the first remote user interacting with the one or more educational content items and (ii) training data labeled with a classification indicating the measured engagement level of a plurality of the remote users interacting with the one or more educational content items; and
modifying at least one property, in the haptic feedback plan of the first remote user, of the at least one haptic feedback signal provided to the first remote user to increase the engagement status of the first remote user interacting with the one or more educational content items, wherein the modifying is based at least in part on feedback from one or more of the first remote user and a second user.

9. The apparatus of claim 8 , wherein the automatically initiating the provision of the at least one haptic feedback signal to the first remote user further comprises initiating the provision of one or more of an audio signal and a visual signal to the first remote user.

10. The apparatus of claim 8 , wherein the engagement status comprises an engagement score and wherein the automatically initiating the provision of the at least one haptic feedback signal to the first remote user is performed based on an evaluation of the engagement score relative to one or more threshold-based criteria.

11. The apparatus of claim 8 , further comprising employing feedback, from one or more of the first remote user and another user, indicating whether the engagement status of the first remote

Assignees

• Dell Products Lp

Inventors

• Sha Danqing
• Bruno Eric
• Seibel Amy
• Jia Zhen

Classifications

• G06F3/016

  Input arrangements with force or tactile feedback as computer generated output to the user · CPC title

• G09B5/08

  providing for individual presentation of information to a plurality of student stations · CPC title

• G06F3/013

  Eye tracking input arrangements (G06F3/015 takes precedence) · CPC title

• G06F3/012

  Head tracking input arrangements · CPC title

• G06F3/011

  Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00) · CPC title