Wearable Stroke Detection Through Stimulus-Response Monitoring
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Solution Overview
Problem
Stroke detection is challenging due to its asymptomatic nature, heterogeneous presentation, and the difficulty in distinguishing it from other health events, leading to delayed interventions and suboptimal outcomes, especially when it occurs during sleep or with minimal symptoms.
Innovation Solution
A wearable device with physiological sensors and a stimulus source applies a stimulus to invoke a physiological response, monitoring tissue sites for heart rate variability and skin temperature changes, using machine learning to generate a classifier for early detection of anomalous biologic events like stroke.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If periodic manual assessment is used for stroke detection, then device complexity is reduced, but measurement precision and reliability deteriorate due to subjectivity and periodic sampling gaps
Solution Approach 1:
The patent replaces manual mechanical assessment with automated optical imaging and computational analysis. The system uses photograph capture, image processing algorithms, and automated scoring to substitute human clinician evaluation, thereby eliminating subjectivity while maintaining simplicity in device operation.
Solution Approach 2:
The system enables continuous monitoring by capturing images at frequent intervals (e.g., every 5 minutes) rather than periodic manual assessments. This continuous data collection allows for real-time detection of neurological changes, improving measurement precision without requiring complex continuous monitoring equipment.
2Measurement precision
If continuous physiological monitoring with stimulus application is implemented, then stroke detection precision improves, but device complexity and energy consumption increase
Solution Approach 1:
The wearable device integrates multiple functions into a single unit: stimulus delivery (thermal or electrical), physiological parameter sensing (heart rate, temperature, blood flow), and data processing. This multi-functionality improves stroke detection precision while minimizing the number of separate devices required.
Solution Approach 2:
The system uses the patient's own physiological responses to external stimuli as the measurement mechanism. By applying a stimulus and monitoring the body's natural reaction (e.g., vasodilation, heart rate change), the system eliminates the need for complex external measurement equipment while maintaining high detection precision.
3Reliability
If frequent manual neurological assessments are performed, then detection reliability improves, but loss of time for patient care increases and productivity decreases
Solution Approach 1:
The patent replaces time-consuming manual neurological assessments with automated image-based evaluation. The system captures photographs and uses algorithmic analysis to assess neurological status, reducing the time required per assessment from minutes to seconds while maintaining or improving detection reliability.
Solution Approach 2:
The system establishes baseline neurological measurements early in the patient's course and continuously compares subsequent measurements against this baseline. This preliminary action allows for rapid detection of deviations without requiring full re-assessment protocols, thereby improving both reliability and care efficiency.
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
Enhances the ability to detect strokes promptly by identifying subtle physiological changes, reducing the risk of undetected neurological decline through continuous and personalized monitoring, thereby improving patient outcomes.
Implementation Method 1
a stimulus source configured to apply a stimulus at the at least one tissue site to invoke a physiological response at the least one tissue site
Implementation Method 2
the second data includes data associated with a skin temperature at two different locations on a body of the person
Implementation Method 3
at least one of the extracted set of features comprises a metric corresponding to heart rate variability
Data Source
AI summary
A system for detecting an anomalous biologic event in a person includes a wearable device for monitoring skin surface sites of a person. The wearable device includes an electrode for contacting skin sites, an electronic stimulus source with a surface area to provide stimulus, and a sensor placed adjacent the skin sites to sense physiological data. A processor is coupled to the wearable device and is configured to: cause the stimulus source to generate a stimulus; excite the electrode to trigger monitoring the skin sites; cause operation of the sensor; receive bioelectrical data from each skin site; receive physiological data from the sensor; continuously compute a difference in the received bioelectrical data for a duration; compute a difference in the received physiological data at time intervals; and generate, based on the computation, an assessment including a likelihood of occurrence of the anomalous biologic event.