Remote Stroke Diagnosis via Sensor Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for diagnosing cerebral stroke are inefficient in reducing the time to treatment, as they often require on-site neurological assessment and lack real-time, remote monitoring capabilities.
Innovation Solution
A system and method that utilize a patient database and processor to analyze clinical measurement data from sensors acquiring image, sound, and tactile data, extracting potential stroke features and comparing them to classified datasets to determine the likelihood and location of a stroke, enabling immediate remote assessment and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-site neurological assessment is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent introduces an intermediary system consisting of sensors, processors, and communication modules that bridge the gap between remote locations and medical professionals. This intermediary automatically collects clinical data via sensors, processes it through algorithms, and transmits results to physicians, eliminating the need for physical presence while maintaining diagnostic accuracy
Solution Approach 2:
The patent replaces the mechanical system of on-site physical assessment with an automated electronic system. Sensors substitute for manual neurological examinations, processors substitute for physician analysis, and communication networks substitute for physical transport, thereby maintaining measurement precision while eliminating time loss
2Loss of time
If remote monitoring capabilities are added, then loss of time is reduced, but device complexity increases
Solution Approach 1:
The patent employs universal components that perform multiple functions: sensors collect various clinical parameters (vital signs, neurological data), the processor handles data analysis and algorithm execution, and the communication module enables both data transmission and receipt of medical advice, thereby reducing overall system complexity through functional consolidation
Solution Approach 2:
The system incorporates self-service capabilities where the automated processing algorithm independently analyzes sensor data, generates diagnostic results, and transmits them without requiring constant human intervention. This self-service approach reduces the operational complexity of managing the remote monitoring system
3Measurement precision
If multiple sensors are deployed, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple sensor functions into an integrated system where sensors collectively capture comprehensive clinical data. The processor consolidates data from various sensors, applies unified processing algorithms, and generates integrated diagnostic results, thereby maintaining high measurement precision while managing complexity through consolidation
Data Source
AI summary
A method for estimating a likelihood of a stroke condition of a subject, the method comprising: acquiring clinical measurement data pertaining to said subject, said clinical measurement data including at least one of image data, sound data, movement data, and tactile data; extracting from said clinical measurement data, potential stroke features according to at least one predetermined stroke assessment criterion; comparing said potential stroke features with classified sampled data acquired from a plurality of subjects, each positively diagnosed with at least one stroke condition, defining a positive stroke dataset; and determining, according to said comparing, a probability of a type of said stroke condition, and a probability of a corresponding stroke location of said stroke condition with respect to a brain location of said subject.