Systems and Methods for Generating Synthetic Cardio-Respiratory Signals
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Solution Overview
Problem
Existing cardiac and respiratory signal monitoring technologies require electrical equipment and sensors connected via wires, belts, or attachments, limiting mobility and repeatability, especially in non-hospital settings, and are inconvenient for long-term use.
Innovation Solution
Generating synthetic cardio-respiratory signals from ballistocardiogram (BCG) sensors, using non-contact sensors like pressure, load, weight, force, motion, or accelerometer sensors to capture mechanical vibrations, transforming them into electrical and audio signals that mimic heart and lung functions, enabling contactless monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrical sensors connected via wires, belts, or attachments are used for cardiac and respiratory signal monitoring, then measurement precision can be maintained, but subject mobility is limited and long-term monitoring convenience deteriorates
Solution Approach 1:
The patent replaces traditional electrical sensors with mechanical sensors that detect ballistocardiogram signals through physical contact with the subject's body. The mechanical sensor system uses force-sensitive resistors or piezoelectric elements to capture mechanical vibrations from the heart and respiratory movements, eliminating the need for wired electrical connections while maintaining measurement capability
Solution Approach 2:
The patent introduces an intermediary processing system that converts mechanical sensor outputs into synthetic electrocardiogram and respiratory signals. The system uses signal processing algorithms to transform the mechanical vibration data into clinically recognizable waveforms, serving as a mediator between the mechanical sensing approach and the electrical signal output format
2Measurement precision
If contact sensors are used for cardiac and respiratory monitoring, then signal quality can be maintained, but the need for re-attachment limits repeatability and consistency over long periods
Solution Approach 1:
The patent enables continuous monitoring by using mechanical sensors that remain in constant contact with the subject throughout the monitoring period. The sensors are positioned on the chest or back and continuously capture ballistocardiogram signals without requiring periodic re-attachment, ensuring uninterrupted data collection and maintaining consistent measurement conditions over extended periods
3Measurement precision
If wired electrical equipment is used for monitoring, then diagnostic accuracy can be achieved, but mobility and ability to use in non-hospital settings is reduced
Solution Approach 1:
The patent replaces wired electrical monitoring equipment with wireless mechanical sensing technology. The mechanical sensors detect body movements and vibrations related to cardiac and respiratory function, transmitting data wirelessly to analysis systems. This substitution enables monitoring in diverse settings including homes, clinics, and mobile environments while maintaining diagnostic capability through accurate signal capture
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 continuous, mobile, and long-term monitoring of cardiac and respiratory conditions, detecting conditions like atrial fibrillation, apnea, and heart murmurs, providing accurate spatial maps for diagnosis, and allowing remote analysis and reporting.
Implementation Method 1
obtain ballistocardiogram (BCG) data from one or more sensors, where the one or more sensors capture BCG data for one or more subjects
Data Source
AI summary
Devices and methods for generating synthetic cardio-respiratory signals from one or more ballistocardiogram (BCG) sensors. A method for determining item specific parameters includes obtaining ballistocardiogram (BCG) data from one or more sensors, where the one or more sensors capture BCG data for one or more subjects in relation to a substrate. For each subject, the captured BCG data is pre-processed to obtain cardio-respiratory BCG data. The cardio-respiratory BCG data is sub-sampled to generate the cardio-respiratory BCG data at a cardio-respiratory sampling rate conducive to cardio-respiratory signal generation. The sub-sampled cardio-respiratory BCG data is cardio-respiratory processed to generate a cardio-respiratory parameter set. A synthetic cardio-respiratory signal is generated from at least the cardio-respiratory parameter set and a cardio-respiratory event morphology template. A condition of the subject is determined based on the synthetic cardio-respiratory signal.


