Systems, devices, and methods for detecting brain conditions from cranial movement due to blood flow in the brain

Patent metadata

Field	Value
Publication number	US-12575796-B2
Application number	US-202017423281-A
Country	US
Kind code	B2
Filing date	Jan 16, 2020
Priority date	Jan 17, 2019
Publication date	Mar 17, 2026
Grant date	Mar 17, 2026

Abstract

A headset, configured to be attached to a human head, includes an accelerometer providing a signal indicative of head acceleration due to blood flow through the brain. An analyzer evaluates a plurality of samples indicative of acceleration over time where each sample corresponds to the head movement resulting from a cardiac contraction. The analyzer identifies brain conditions at least partially based on a level of chaos of the plurality samples. The algorithm applied by the analyzer is partially formulated based on clinical data and examination of a plurality of subjects. In one example, the plurality of samples evaluated by the analyzer are indicative of the head accelerometer only in a single axis. In some situations, the analyzer identifies brain conditions further based on contemporaneous neurological examination of the subject.

First claim

What is claimed is:

1 . A system comprising:
a headset, the headset housing a three-dimensional accelerometer configured to generate three orthogonal signals, each orthogonal signal indicative of acceleration in an axis orthogonal to two other axes of a motion of the three-dimensional accelerometer due to head movement in a brain due to heartbeat; an analyzer having an input configured to receive a plurality of data samples based on each orthogonal accelerometer signal, each data sample indicative of the head movement associated with a different heartbeat in a single axis, the analyzer configured to determine a level of chaos of the plurality of data samples and indicate that a large vessel occlusion (LVO) has occurred in the brain when the level of chaos exceeds a threshold, wherein the level of chaos is at least partially based on a difference between signal levels at a plurality of selected times of each of a plurality of acceleration versus time functions of the plurality of data samples, wherein the level of chaos is at least partially based on a calculation of the plurality of acceleration versus time functions, and wherein the calculation comprises determining a difference function for each data sample at a plurality of times, each difference function comprising a difference between the data sample and an average of all data samples.

2 . The system in accordance with claim 1 , wherein the calculation further comprises:
rectifying and summing each difference function to generate a plurality of results; summing the plurality of results to generate a sum of results; and normalizing the sum of results to a number of data samples or normalizing the sum of results to a minimum and a maximum of the average of data samples at a plurality of time points.

3 . The system in accordance with claim 1 , wherein the calculation comprises:
determining a root-mean-square of the difference function.

4 . The system in accordance with claim 3 , wherein the calculation further comprises:
summing the root-mean-square of the difference function to generate a sum; and normalizing the sum to a minimum and a maximum of the average of the data samples at a plurality of time points.

5 . The system in accordance with claim 1 , wherein the calculation comprises:
applying a cross-correlation function to each data sample of the plurality of data samples to an average of all data samples of the plurality of data samples; or determining a number of times of the plurality of times that differ from an average.

6 . The system in accordance with claim 1 , wherein the processor is configured to determine the level of chaos at least partially based on a shape of an acceleration versus time function of each data sample of the plurality of data samples.

7 . The system in accordance with claim 1 , wherein the analyzer is configured to time align the plurality of the acceleration versus time functions based on information from the plurality of the acceleration versus time functions.

8 . The system in accordance with claim 1 , wherein the analyzer is configured to time align the plurality of the acceleration versus time functions, at least partially, from an electrocardiogram (ECG) or photoplethysmograph (PPG) signal indicative of cardiac contractions.

9 . The system in accordance with claim 1 , further comprising:
a transmitter configured to transmit a wireless signal indicative of the plurality of data samples; and a receiver configured to receive the wireless signal and provide the plurality of data samples to the analyzer.

10 . The system in accordance with claim 9 , further comprising:
an analog to digital converter (ADC) configured to sample each orthogonal accelerometer signal to generate the plurality of data samples.

11 . The system in accordance with claim 10 , further comprising:
a controller configured to time align the plurality of data samples before transmission of the wireless signal comprising time aligned data samples.

12 . The system of claim 1 , wherein the headset further comprises the analyzer.

Assignees

• Univ California

Inventors

• Smith Wade
• Lovoi Paul

Classifications

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title

• A61B5/1102

  Ballistocardiography · CPC title

• A61B5/24

  Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof · CPC title

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B5/6814 Primary

  Head · CPC title