Granted Patent B2

US 12,554,326 · App. 18/062,376 · Granted Feb 17, 2026

Inventors: Peter Eli Yoo (Fitzroy North, AU); Thomas James Oxley (Dover, DE)

Assignee: Synchron Australia Pty Limited

G06F3/015A61B5/6876

Abstract

Claims (32)

1 . A method of controlling a device, comprising:

detecting an increase in an intensity of a neural-related signal of a subject beyond a baseline level measured, wherein the neural-related signal is a neural oscillation of the subject, and wherein detecting the increase in the intensity of the neural-related signal comprises detecting an increase in a power of the neural oscillation beyond a baseline oscillation power level;

detecting a reduction in the intensity of the neural-related signal below the baseline level measured following the increase; and

transmitting an input command to the device upon the detection of the reduction in the intensity of the neural-related signal following the increase in the intensity of the neural-related signal.

2 . The method of claim 1 , wherein detecting the reduction in the intensity of the neural-related signal comprises detecting a decrease in the power of the neural oscillation.

3 . The method of claim 2 , wherein the power is a power spectral density.

4 . The method of claim 1 , wherein the neural-related signal is measured or monitored using an endovascular device implanted within the subject, and wherein the steps of detecting the increase or reduction in the intensity of the neural-related signal and transmitting the input command are performed using one or more processors.

5 . The method of claim 4 , further comprising:

filtering, using one or more processors of an apparatus implanted within the subject, raw neural-related signals obtained from the endovascular device using one or more software filters; and

feeding filtered signals into a classification layer to automatically detect the reduction and increase in the intensity of the neural-related signal using a machine learning classifier.

6 . The method of claim 1 , wherein the increase in the intensity of the neural-related signal is caused by the subject mentally releasing a first thought, and wherein the reduction in the intensity of the neural-related signal is caused by the subject conjuring and holding a second thought.

7 . The method of claim 6 , wherein at least one of the first thought and the second thought is a task-relevant thought, and wherein the input command is a command to the device to accomplish at least part of a task associated with the task-relevant thought.

8 . The method of claim 6 , wherein at least one of the first thought and the second thought is a task-irrelevant thought, and wherein the input command is a command to the device to accomplish at least part of a task not associated with the task-irrelevant thought.

9 . The method of claim 8 , wherein the task-irrelevant thought is a thought related to a body function of the subject.

10 . The method of claim 1 , wherein the device is at least one of a personal computing device, an internet-of-things (IoT) device, and a mobility vehicle.

11 . A system for controlling a device, comprising:

an endovascular device configured to measure or monitor a neural-related signal of a subject, wherein the neural-related signal of the subject is a neural oscillation of the subject; and

an apparatus comprising one or more processors and wherein the one or more processors are programmed to:

detect an increase in an intensity of a neural-related signal beyond a baseline level measured, wherein detecting the increase in the intensity of the neural-related signal comprises detecting an increase in a power of the neural oscillation beyond a baseline oscillation power level,

detect a reduction in the intensity of the neural-related signal below the baseline level measured following the increase, and

transmit an input command to the device upon the detection of the reduction in the intensity of the neural-related signal following the increase in the intensity of the neural-related signal.

12 . The system of claim 11 , wherein the one or more processors are programmed to detect the reduction in the intensity of the neural-related signal by detecting a decrease in the power of the neural oscillation.

13 . The system of claim 12 , wherein the power is a power spectral density.

14 . The system of claim 11 , wherein the endovascular device is configured to be implanted within a vein or sinus of the brain of the subject.

15 . The system of claim 11 , wherein the one or more processors are further programmed to:

filter raw neural-related signals obtained from the endovascular device using one or more software filters; and

feed filtered signals into a classification layer to automatically detect the reduction and increase in the intensity of the neural-related signal using a machine learning classifier.

16 . The system of claim 11 , wherein the increase in the intensity of the neural-related signal is caused by the subject mentally releasing a first thought, and wherein the reduction in the intensity of the neural-related signal is caused by the subject conjuring and holding a second thought.

17 . The system of claim 16 , wherein at least one of the first thought and the second thought is a task-relevant thought, and wherein the input command is a command to the device to accomplish at least part of a task associated with the task-relevant thought.

18 . The system of claim 16 , wherein at least one of the first thought and the second thought is a task-irrelevant thought, and wherein the input command is a command to the device to accomplish at least part of a task not associated with the task-irrelevant thought.

19 . The system of claim 18 , wherein the task-irrelevant thought is a thought related to a body function of the subject.

20 . The system of claim 11 , wherein the device is at least one of a personal computing device, an internet-of-things (IoT) device, and a mobility vehicle.

Assignments (1)

Continuity (4)

References Cited (94)