IP Library › Granted Patent US 12,564,343
Granted Patent B2
US 12,564,343 · App. 18/093,872 · Granted Mar 3, 2026

Systems and methods for determining actor status according to behavioral phenomena

Inventors: Bradford R. Everman (Haddonfield, NJ); Brian Scott Bradke (Brookfield, VT)
A61B5/165A61B5/163A61B5/4803A61B5/7221A61B5/7267G10L15/063G10L15/22G10L25/63
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Quick Facts
Patent No.
US 12,564,343
App. No.
18/093,872
Granted
Mar 3, 2026
Kind
B2
Abstract

Aspects relate to systems and methods for determining actor status according to behavioral phenomena. An exemplary system includes an eye sensor configured to detect an eye parameter as a function of an eye phenomenon, a speech sensor configured to detect a speech parameter as a function of a speech phenomenon, and a processor in communication with the eye sensor and the speech sensor; the processor is configured to receive the eye parameter and the speech parameter, determine an eye pattern as a function of the eye parameter, determine a speech pattern as a function of the speech parameter, and correlate one or more of the eye pattern and the speech pattern to a cognitive status.

Claims (56)

1 . A system for determining actor status according to behavioral phenomenon, the system comprising:

at least a speech sensor configured to detect at least a speech parameter of a user as a function of at least a speech phenomenon; and

a processor in communication with the at least a speech sensor and configured to:

receive the at least a speech parameter;

determine at least a speech pattern as a function of the at least a speech parameter; and

correlate the at least a speech pattern to a cognitive status, wherein correlating to the cognitive status comprises:

receiving cognitive status training data comprising a plurality of speech patterns correlated to a plurality of cognitive statuses;

training a cognitive status machine learning model as a function of the cognitive status training data; and

determining the cognitive status as a function of the cognitive status machine learning model, wherein the cognitive status is measured relative to a level of cognitive performance required for a given task.

2 . The system of claim 1 , further comprising:

at least an eye sensor configured to detect at least an eye parameter of the user as a function of at least an eye phenomenon; and

wherein the processor is in communication with the at least an eye sensor and configured to:

receive the at least an eye parameter;

determine at least an eye pattern as a function of the at least an eye parameter; and

correlate the at least an eye pattern to the cognitive status.

3 . The system of claim 2 , wherein the cognitive status training data comprises a plurality of eye patterns correlated to the plurality of cognitive statuses.

4 . The system of claim 1 , wherein correlating the at least a speech pattern to a cognitive status further comprises compiling the cognitive status training data from historic information of the user.

5 . The system of claim 1 , wherein determining the at least a speech pattern comprises:

inputting speech pattern training data into a speech pattern machine learning algorithm, wherein the speech pattern training data comprises a plurality of speech parameters correlated to a plurality of speech patterns;

training a speech pattern machine learning model, as a function of the speech pattern machine learning algorithm; and

determining the at least a speech pattern as a function of the speech pattern machine learning model and the at least a speech parameter.

6 . The system of claim 5 , wherein determining the at least a speech pattern further comprises compiling the speech pattern training data from historic information of the user.

7 . The system of claim 2 , wherein determining the at least an eye pattern comprises:

inputting eye pattern training data into an eye pattern machine learning algorithm, wherein the eye pattern training data comprises a plurality of eye parameters correlated to a plurality of eye patterns;

training an eye pattern machine learning model, as a function of the eye pattern machine learning algorithm; and

determining the at least an eye pattern as a function of the eye pattern machine learning model and the at least an eye parameter.

8 . The system of claim 7 , wherein determining the at least an eye pattern further comprises compiling the eye pattern training data from historic information of the user.

9 . The system of claim 2 , wherein the at least an eye sensor comprises an electromyography sensor configured to detect the at least an eye parameter as a function of the at least an eye phenomenon.

10 . The system of claim 1 , wherein the at least a speech sensor comprises a bone conductance transducer configured to detect the at least a speech parameter as a function of the at least a speech phenomenon.

11 . A method of determining actor status according to behavioral phenomena, the method comprising:

detecting, using at least a speech sensor, at least a speech parameter of a user as a function of at least a speech phenomenon;

receiving, using a processor in communication with the at least a speech sensor, the at least a speech parameter;

determining, using the processor, at least a speech pattern as a function of the at least a speech parameter; and

correlating, using the processor, the at least a speech pattern to a cognitive status, wherein correlating to the cognitive status comprises:

receiving cognitive status training data comprising a plurality of speech patterns correlated to a plurality of cognitive statuses;

training a cognitive status machine learning model, as a function of the cognitive status training data; and

determining the cognitive status as a function of the cognitive status machine learning model, wherein the cognitive status is measured relative to a level of cognitive performance required for a given task.

12 . The method of claim 11 , further comprising:

detecting, using at least an eye sensor, at least an eye parameter of the user as a function of at least an eye phenomenon;

receiving, using the processor in communication with the at least an eye sensor, the at least an eye parameter;

determining, using the processor, at least an eye pattern as a function of the at least an eye parameter; and

correlating, using the processor, the at least an eye pattern to the cognitive status.

13 . The method of claim 12 , wherein the cognitive status training data comprises a plurality of eye patterns correlated to the plurality of cognitive statuses.

14 . The method of claim 11 , wherein correlating the at least a speech pattern to a cognitive status further comprises compiling the cognitive status training data from historic information of the user.

15 . The method of claim 11 , wherein determining the at least a speech pattern comprises:

inputting the speech pattern training data into a speech pattern machine learning algorithm, wherein the speech pattern training data comprises a plurality of speech parameters correlated to a plurality of speech patterns;

training a speech pattern machine learning model, as a function of the speech pattern machine learning algorithm; and

determining the at least a speech pattern as a function of the speech pattern machine learning model and the at least a speech parameter.

16 . The method of claim 15 , wherein determining the at least a speech pattern further comprises compiling the speech pattern training data from historic information of the user.

17 . The method of claim 12 , wherein determining the at least an eye pattern comprises:

inputting eye pattern training data into an eye pattern machine learning algorithm, wherein the eye pattern training data comprises a plurality of eye parameters correlated to a plurality of eye patterns;

training an eye pattern machine learning model, as a function of the eye pattern machine learning algorithm; and

determining the at least an eye pattern as a function of the eye pattern machine learning model and the at least an eye parameter.

18 . The method of claim 17 , wherein determining the at least an eye pattern further comprises compiling the eye pattern training data from historic information of the user.

19 . The method of claim 12 , wherein the at least an eye sensor comprises an electromyography sensor configured to detect the at least an eye parameter as a function of the at least an eye phenomenon.

20 . The method of claim 11 , wherein the at least a speech sensor comprises a bone conductance transducer configured to detect the at least a speech parameter as a function of the at least a speech phenomenon.

Continuity (2)
Continuation 17731935 · Apr 28, 2022
Related Publication 20230346277A1 · Nov 2, 2023
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