Carotid Vibration Monitoring for Haemorrhagic Stroke Prediction
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Solution Overview
Problem
Existing systems fail to effectively predict the risk of hemorrhagic stroke by correlating the biomechanical properties of the carotid wall with blood pressure data, limiting targeted therapeutic interventions.
Innovation Solution
A system comprising a monitoring device with vibration sensors and an automatic blood pressure measuring device, synchronized with artificial intelligence, to analyze the correlation between biomechanical signals and blood pressure data for predicting hemorrhagic stroke risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a system combines vibration sensors and blood pressure measuring devices with AI analysis to predict hemorrhagic stroke risk, then prediction reliability is improved, but device complexity increases
Solution Approach 1:
The system is divided into separate functional modules: a monitoring device for vibration sensing, an automatic blood pressure measuring device, and a computing unit for AI analysis. This segmentation allows each component to be optimized independently while maintaining overall system reliability, addressing the contradiction between prediction accuracy and device complexity.
Solution Approach 2:
The computing unit acts as an intermediary that receives data from multiple sensors, processes them through trained AI algorithms, and generates prediction results. This intermediary layer integrates complex functions centrally, allowing the sensor devices to remain relatively simple while achieving high prediction reliability through sophisticated analysis.
2Measurement precision
If continuous monitoring of carotid wall biomechanical state is implemented, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
The monitoring device performs measurements at regular intervals rather than continuously, with the vibration sensor and blood pressure device synchronized to collect data periodically. This periodic monitoring maintains measurement precision for detecting biomechanical changes while significantly reducing energy consumption compared to truly continuous monitoring.
Solution Approach 2:
The system maintains continuous monitoring capability through synchronized periodic measurements, ensuring that useful data is continuously collected without requiring constant high-power operation. The AI analysis continuously processes the accumulated data to maintain prediction accuracy while the devices operate in energy-efficient periodic mode.
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
Enables reliable prediction of hemorrhagic stroke risk, facilitating targeted therapeutic interventions and post-therapeutic evaluations, applicable to both clinical settings and home use.
Implementation Method 1
at least one vibration sensor configured to measure mechanical waves propagated in said wall
Implementation Method 2
The automatic blood pressure measuring device comprises a pressure sensor reacting to variations in the blood pressure of said patient
Data Source
AI summary
System (1) for predicting the risk of occurrence of a hemorrhagic stroke by analyzing the correlation between the carotid biomechanics, sentinel of the cerebral vascular system, and the blood pressure profile of a patient, comprising:a monitoring device (2) capable of being positioned close to a carotid wall, the device comprising at least one vibration sensor (4) configured to measure mechanical waves generated by the arterial pulse wave or any other shear or compression wave propagated in said wall, a memory (8) capable of storing signals transmitted by the at least one vibration sensor, a communication interface (9), an energy source (7) configured to supply power to the at least one vibration sensor (4) and the communication interface (9),an automatic blood pressure measuring device (20) for automatic measurement of the patient's blood pressure, said device being configured to emit a signal representative of the patient's blood pressure over time, the measurement device (20) being synchronized with the monitoring device (2),a computing unit (10) for communicating with the monitoring device (2) and the automatic blood pressure measuring device (20) and configured to analyze measurements from the monitoring device (2) and the automatic blood pressure measuring device (20) through artificial intelligence trained to correlate the measurements representative of the biomechanical state of the wall and the measurements representative of the blood pressure, in order to detect whether there is a risk of occurrence or recurrence of a hemorrhagic stroke in the patient.