Wearable HRV Monitoring for Acute Cardiopulmonary Event Prediction
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Solution Overview
Problem
Current triage systems for acute cardiopulmonary events are subjective and inefficient, relying on clinical judgment and traditional vital signs that fail to accurately predict severe outcomes with time specificity, and existing wearable devices struggle with noise susceptibility and limited predictive accuracy.
Innovation Solution
A wearable device combining heart rate variability (HRV) with other vital signs, using an artificial neural network to predict acute cardiopulmonary events by integrating ECG sensors, pulse oximeters, and impedance plethysmography, and employing signal processing to filter noise and analyze HRV parameters, along with vital signs like blood pressure and respiratory rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vital signs and clinical judgment are used for triage, then the system is simple to operate, but the prediction accuracy and time specificity are poor
Solution Approach 1:
The patent combines multiple sensing modalities (ECG, pulse oximetry, impedance plethysmography) into a single integrated wearable device. This merging of sensors allows the system to capture comprehensive physiological data simultaneously, improving prediction accuracy through multi-parameter analysis while consolidating what would otherwise be separate complex systems into one unified device.
Solution Approach 2:
The patent replaces subjective clinical judgment with automated computational analysis using artificial neural networks. The system processes physiological signals through algorithmic analysis rather than relying on clinician interpretation, thereby improving measurement precision and time specificity while maintaining ease of operation through automatic processing.
2Measurement precision
If multiple sensors are integrated to improve prediction accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The wearable device is designed as a multi-functional platform that simultaneously performs ECG monitoring, pulse oximetry, and impedance plethysmography. This universal design allows a single device to execute multiple sensing functions without requiring separate specialized equipment, thereby improving prediction accuracy while maintaining ease of operation through consolidated functionality.
Solution Approach 2:
The system incorporates automated signal processing and artifact rejection algorithms that enable the device to self-calibrate and self-validate its measurements. The artificial neural network automatically processes raw physiological signals, filters noise, and generates predictions without requiring manual intervention, thus improving measurement precision while keeping the device easy to operate.
3Measurement precision
If signal processing is applied to filter noise, then the measurement precision improves, but the processing time increases
Solution Approach 1:
The system performs preliminary signal conditioning and filtering at the point of data acquisition, preparing signals for analysis before they are passed to the artificial neural network. By pre-processing signals to remove obvious artifacts and normalize data formats in advance, the system reduces the computational burden during critical prediction phases, thereby improving signal accuracy without significantly increasing overall processing time.
Solution Approach 2:
The patent implements continuous real-time processing of physiological signals with streamlined algorithms that maintain constant monitoring without interruption. The signal processing is optimized to operate continuously at high speed, filtering noise and analyzing data in real-time rather than through batch processing, thus improving measurement precision while minimizing time loss through uninterrupted continuous analysis.
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
Provides robust, portable prediction of acute cardiopulmonary events with improved accuracy and time specificity, enabling timely triage and treatment in emergency situations.
Implementation Method 1
ECG sensors
Implementation Method 2
The sensor may be a pulse oximeter. The sensor may measure the perfusion status of the microvasculature.
Implementation Method 3
impedance plethysmography
Data Source
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AI summary
According to the invention, there is provided a system for the detection of impending acute cardiopulmonary medical events that, left untreated, would with a reasonable likelihood result in either severe injury or death comprising: an electro-cardiogram (ECG) module including a plurality of electrodes for sensing a patient's ECG and having an ECG output; a sensor for sensing a patient's physiologic parameter other than ECG; a first input for receiving the ECG output; a second input for receiving signals from the sensor for sensing a patient's physiologic parameter other than ECG; a third input constructed and arranged to receive: parametric information describing at least one element of a patient's demographic information; and parametric information describing a patient's medical history; a digitizing unit for digitizing the ECG and the physiologic signal other than ECG; a housing containing a memory unit and processing unit, for storing and processing, respectively, the ECG, the physiologic signal other than ECG, patient demographic information and medical history; and a user communication unit; wherein the processing unit calculates at least one measure of heart rate variability (HRV), combines that at least one measure of HRV with at least one parameter each of patient demographic information and medical history, and calculates a statistical probability of an ACP event within 72 hours of the calculation.