Stroke Detection via Passive Mobile Sensor Monitoring
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Solution Overview
Problem
Patients often fail to seek timely medical attention due to unrecognized stroke symptoms, misperception of symptoms, or other reasons, leading to potential permanent tissue loss.
Innovation Solution
A stroke detection device that passively monitors user characteristics using a cell phone with sensors and apps, providing notifications and instructions for tests to assess potential stroke symptoms, and optionally contacting medical facilities if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passive monitoring is used to detect stroke symptoms, then early detection capability is improved, but device complexity increases
Solution Approach 1:
The patent applies multi-functionality by integrating multiple sensor types (accelerometer, gyroscope, microphone, image sensor) into a single mobile device that can perform diverse stroke detection functions including gait analysis, speech assessment, facial expression monitoring, and arm movement tracking. This unified approach improves detection reliability while managing complexity through consolidation rather than requiring separate specialized devices for each monitoring function.
Solution Approach 2:
The system implements self-service by enabling the mobile device to autonomously monitor user characteristics, automatically compare current data against baseline profiles, detect stroke symptoms without human intervention, and provide notifications or emergency alerts. This automation improves detection reliability while the use of readily available mobile device components keeps the overall system complexity manageable.
2Measurement precision
If multiple sensors are integrated into the mobile device, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent leverages the multi-functional capabilities of standard mobile device sensors to achieve precise stroke monitoring. The accelerometer and gyroscope serve dual purposes for gait analysis and arm movement assessment, the microphone captures speech patterns for stroke detection, and the image sensor monitors facial expressions. This approach achieves measurement precision using existing components rather than requiring specialized precision sensors, thereby managing integration complexity.
Solution Approach 2:
The system merges the functionality of multiple separate monitoring devices into a single integrated mobile platform. By combining gait analysis, speech assessment, facial monitoring, and arm movement tracking into one device that patients carry daily, the patent achieves comprehensive precise measurement while avoiding the complexity of synchronizing and integrating multiple standalone devices with their own power sources and processing units.
3Loss of time
If automated notification and testing is implemented, then response time is improved, but ease of operation decreases
Solution Approach 1:
The system implements self-service automation where the mobile device continuously monitors user characteristics, automatically compares current readings against stored baseline profiles, detects stroke symptoms without user input, and triggers notifications or emergency alerts autonomously. This dramatically reduces response time to stroke events while requiring minimal user interaction beyond the initial device setup and baseline profile creation.
Solution Approach 2:
The patent applies preliminary action by having the system continuously monitor and compare user characteristics against pre-established baseline profiles in real-time. This proactive approach allows the system to detect deviations indicating stroke symptoms before the user consciously perceives them, enabling automated early intervention. The baseline profiles are created during normal operation, and the automated comparison continues uninterrupted, reducing response time while maintaining ease of use through background processing.
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
Encourages timely medical assistance by accurately identifying stroke symptoms through passive monitoring and testing, potentially reducing stroke severity and tissue loss.
Implementation Method 1
The sensor is an accelerometer and the characteristic monitored by the sensor is a gait of the cell phone user
Implementation Method 2
the user speaking a specific phrase into a microphone of the cell phone wherein the controller compares a current sound sample generated from the user speaking the specific phrase into the microphone to a past sound sample
Implementation Method 3
the user making a requested facial expression while a current image of the user is captured by an image sensor of the cell phone
Data Source
AI summary
A stroke detection device includes a cell phone having a sensor adapted to sense a characteristic of the user of the cell phone. An app executed by the cell phone passively monitors the characteristic to determine if the user has experienced a stroke. The app requests that the user take one or more tests using the cell phone if the presence of a stroke is possible. The tests include the user speaking a specific phrase into the cell phone that is compared to a previously recorded sound sample of the user; the user taking a picture of himself or herself with the cell phone that the app compares to a previous picture of the user; and the user attempting to hold his or her arm out straight while holding the cell phone wherein accelerometers in the phone measure the steadiness of his or her arm.