The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 16, 2026

Filed:

May. 31, 2023
Applicant:

Strong Force Iot Portfolio 2016, Llc, Fort Lauderdale, FL (US);

Inventors:

Charles Howard Cella, Pembroke, MA (US);

Gerald William Duffy, Jr., Philadelphia, PA (US);

Jeffrey P. Mcguckin, Philadelphia, PA (US);

Mehul Desai, Oak Brook, IL (US);

Assignee:

Strong Force IoT Portfolio 2016, LLC, Fort Lauderdale, FL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/006 (2023.01); B62D 15/02 (2006.01); G01M 13/028 (2019.01); G01M 13/04 (2019.01); G01M 13/045 (2019.01); G05B 13/02 (2006.01); G05B 19/418 (2006.01); G05B 23/02 (2006.01); G06F 18/21 (2023.01); G06N 3/02 (2006.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/047 (2023.01); G06N 3/084 (2023.01); G06N 3/088 (2023.01); G06N 5/046 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2023.01); G06Q 10/0639 (2023.01); G06Q 30/02 (2023.01); G06Q 30/06 (2023.01); G06Q 50/00 (2012.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G16Z 99/00 (2019.01); H02M 1/12 (2006.01); H03M 1/12 (2006.01); H04B 17/23 (2015.01); H04B 17/345 (2015.01); H04L 1/00 (2006.01); H04L 1/18 (2023.01); H04L 1/1867 (2023.01); H04L 67/1097 (2022.01); H04L 67/12 (2022.01); H04W 4/38 (2018.01); H04W 4/70 (2018.01); B62D 5/04 (2006.01); G05B 19/042 (2006.01); G06F 17/18 (2006.01); G06F 18/25 (2023.01); G06N 3/126 (2023.01); H01B 17/40 (2006.01); H04B 17/40 (2015.01); H04L 5/00 (2006.01); H04L 67/306 (2022.01);
U.S. Cl.
CPC ...
G05B 19/4183 (2013.01); B62D 15/0215 (2013.01); G01M 13/028 (2013.01); G01M 13/04 (2013.01); G01M 13/045 (2013.01); G05B 13/028 (2013.01); G05B 19/4184 (2013.01); G05B 19/41845 (2013.01); G05B 19/4185 (2013.01); G05B 19/41865 (2013.01); G05B 19/41875 (2013.01); G05B 23/0221 (2013.01); G05B 23/0229 (2013.01); G05B 23/024 (2013.01); G05B 23/0264 (2013.01); G05B 23/0283 (2013.01); G05B 23/0286 (2013.01); G05B 23/0289 (2013.01); G05B 23/0291 (2013.01); G05B 23/0294 (2013.01); G05B 23/0297 (2013.01); G06F 18/2178 (2023.01); G06N 3/006 (2013.01); G06N 3/02 (2013.01); G06N 3/084 (2013.01); G06N 3/088 (2013.01); G06N 5/046 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06Q 10/0639 (2013.01); G06Q 30/02 (2013.01); G06Q 30/0278 (2013.01); G06Q 30/06 (2013.01); G06Q 50/00 (2013.01); G06V 10/7784 (2022.01); G06V 10/82 (2022.01); G16Z 99/00 (2019.02); H02M 1/12 (2013.01); H03M 1/12 (2013.01); H04B 17/23 (2015.01); H04B 17/345 (2015.01); H04L 1/0002 (2013.01); H04L 1/0041 (2013.01); H04L 1/18 (2013.01); H04L 1/1874 (2013.01); H04L 67/1097 (2013.01); H04L 67/12 (2013.01); H04W 4/38 (2018.02); H04W 4/70 (2018.02); B62D 5/0463 (2013.01); G05B 19/042 (2013.01); G05B 23/02 (2013.01); G05B 23/0208 (2013.01); G05B 2219/32287 (2013.01); G05B 2219/35001 (2013.01); G05B 2219/37337 (2013.01); G05B 2219/37351 (2013.01); G05B 2219/37434 (2013.01); G05B 2219/37537 (2013.01); G05B 2219/40115 (2013.01); G05B 2219/45004 (2013.01); G05B 2219/45129 (2013.01); G06F 17/18 (2013.01); G06F 18/21 (2023.01); G06F 18/217 (2023.01); G06F 18/25 (2023.01); G06N 3/126 (2013.01); H01B 17/40 (2013.01); H04B 17/40 (2015.01); H04L 1/0009 (2013.01); H04L 5/0064 (2013.01); H04L 67/306 (2013.01); Y02P 80/10 (2015.11); Y02P 90/02 (2015.11); Y02P 90/80 (2015.11); Y04S 50/00 (2013.01); Y04S 50/12 (2013.01); Y10S 707/99939 (2013.01);
Abstract

Platforms and methods for improving correspondence between sensor data and haptic output are disclosed. A platform may include a haptic user device and a data collection system to collect sensor data. The haptic user interface may provide different types of haptic stimulation to a user based on the sensor data. The data collection system has a cognitive input selection system with machine learning to improve the effectiveness of the haptic output to the user. The machine learning is trained on feedback of user behavior. The machine learning improves the effectiveness of the haptic output by determining which type of haptic simulation to provide such that the haptic output logically corresponds to the sensor data, or by determining to vary one or more of a timing, an intensity level, or a duration of the haptic output based on the sensor data.


Find Patent Forward Citations

Quick Actions:

Cella, Charles. (2026). Platforms and methods for improving correspondence of haptic output to sensor data (U.S. Patent No. 12656757). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12656757

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