Mobile Stroke Self-Detection via Sensor Baseline Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current stroke detection methods require a physician's presence and often fail to provide timely intervention, as most patients do not reach a hospital in time for adequate treatment due to the lack of immediate self-detection capabilities.
Innovation Solution
A mobile computing device equipped with sensors such as accelerometers, cameras, and microphones that can self-detect stroke symptoms by comparing patient responses to baseline data, determining a stroke self-detection score, and transmitting alerts if the score exceeds a threshold, allowing for immediate physician contact without requiring a physician's presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a physician's presence is required for stroke detection, then detection accuracy may be improved, but response time deteriorates and timely intervention is delayed
Solution Approach 1:
The system enables patients to perform self-detection of stroke symptoms using a mobile device. The application automatically captures sensor data, processes it through algorithms, and generates detection results without requiring a physician's presence, thus resolving the contradiction between detection accuracy and response time.
Solution Approach 2:
The mobile device acts as an intermediary between the patient and the healthcare system. It collects sensor data, processes it locally, and can transmit results to healthcare providers, enabling timely detection while maintaining diagnostic quality through automated analysis algorithms.
2Reliability
If multiple sensors are used for comprehensive stroke detection, then detection capability is improved, but device complexity increases
Solution Approach 1:
The mobile device leverages its existing multi-functional capabilities by integrating accelerometer, camera, and microphone functions for stroke detection. These sensors serve multiple purposes (e.g., camera for facial imaging and documentation, microphone for speech analysis and communication), reducing the need for specialized hardware while improving detection reliability.
Data Source
AI summary
Disclosed herein are implementations of a method and apparatus for stroke self-detection. The method and apparatus may include a mobile platform for stroke detection. The method may include receiving sensor data. The method may include comparing the sensor data with a baseline test result to determine a test score. The method may include determining a passing test result based on a threshold. The method may include transmitting the results or an alert to one or more of an emergency contact, emergency medical services, a physician, or a telemedicine provider.