Cranial Accelerometer Headset for Prehospital LVO Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting Large Vessel Occlusion (LVO) in acute ischemic stroke are inefficient and inaccurate in prehospital settings, particularly due to the limitations of brain imaging and neurological examinations by non-medical professionals, leading to delayed treatment and worsened patient outcomes.
Innovation Solution
A system utilizing a headset with a 3-axis accelerometer to measure head movements caused by blood flow, analyzing the chaos in acceleration patterns through algorithms that incorporate clinical data, to determine the likelihood of LVO by comparing chaos levels to thresholds, potentially enhancing diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If brain imaging and neurological examinations are used by non-medical professionals in prehospital settings, then LVO detection can be performed, but accuracy and efficiency are insufficient leading to delayed treatment
Solution Approach 1:
The patent replaces complex medical imaging systems and professional neurological examination procedures with a simple accelerometer-based mechanical sensing system. The accelerometer measures head movements caused by blood flow, providing an automated objective metric for LVO detection that does not require medical professional interpretation, thereby improving both accuracy and reducing treatment delays
Solution Approach 2:
The system enables non-medical professionals (such as first responders or family members) to perform LVO detection themselves using the accelerometer device. The automated chaos analysis algorithm processes the accelerometer data without requiring medical expertise, allowing anyone to accurately detect LVO and initiate appropriate emergency response, thus eliminating treatment delays associated with waiting for medical professionals
2Reliability
If current prehospital LVO detection methods are used, then treatment can be initiated, but diagnostic accuracy is insufficient leading to inappropriate triage
Solution Approach 1:
The patent replaces subjective neurological examination procedures with an objective accelerometer-based measurement system. The device automatically measures head movements and applies chaos analysis algorithms to provide a reliable diagnostic indicator of LVO, eliminating the variability and inaccuracy associated with non-professional examinations while maintaining ease of operation
Solution Approach 2:
The system changes the diagnostic parameter from subjective neurological signs to an objective quantitative measure of head movement chaos. By measuring the chaos in accelerometer signals during blood flow, the system provides a reliable binary indicator (LVO present or absent) that is both accurate and easy to interpret for triage decisions, improving both reliability and operational ease
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves the accuracy of LVO detection in prehospital settings, enabling more efficient triage and timely transport of patients to appropriate medical facilities for thrombectomy, thereby reducing brain injury and improving clinical outcomes.
Implementation Method 1
Ballistocardiography is the measure of movement of the human body in response to the heartbeat (cardiac contraction). This process measures whole body movement. The heartbeat produces a force on the head and neck through the cerebral vasculature. The force on the brain matter produced by the heartbeat is translated to the skull.
Implementation Method 2
Cranial accelerometry is a method used to measure forces on the head and neck produced by the force of the heartbeat.
Data Source
AI summary
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.