Multisensor Patient Monitoring for Thoracic Fluid Trend Detection
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Solution Overview
Problem
Existing monitoring systems for patients with cardiac pathologies, such as congestive heart failure and chronic kidney disease, fail to accurately predict and manage acute episodes due to inadequate integration of bio-vibrational and radio frequency data, leading to frequent hospitalizations and poor prognosis.
Innovation Solution
A patient monitoring system that combines ECG, vibrational, and radio frequency sensors to generate combinational physiological parameters, performing predictive and trend analyses using machine learning and correlation techniques to identify clinically actionable events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor sources (ECG, vibrational, radio frequency) are integrated to monitor physiological status, then measurement precision and reliability of acute episode prediction are improved, but device complexity increases
Solution Approach 1:
The patent combines ECG sensors, vibrational sensors, and radio frequency sensors into a single integrated monitoring system. The processor receives and analyzes signals from all three sensor types simultaneously, generating combinational physiological parameters that provide more accurate prediction of acute episodes compared to any single sensor type alone.
Solution Approach 2:
The monitoring system is designed to perform multiple functions: ECG monitoring for cardiac rhythm, vibrational sensing for cardiac and respiratory mechanics, and radio frequency sensing for thoracic fluid detection. This multi-functional approach allows one system to comprehensively monitor various physiological parameters related to heart failure and acute episodes.
2Reliability
If continuous monitoring of multiple physiological parameters is performed, then reliability of clinical condition assessment is improved, but use of energy increases
Solution Approach 1:
The system performs continuous monitoring of ECG signals, vibrational signals, and radio frequency signals to track physiological parameters over time. This continuous action enables reliable detection of trends and acute episode predictions, though it does consume energy continuously. The system manages energy by processing signals in real-time and generating actionable insights without requiring constant high-power operations.
3Measurement precision
If bio-vibrational and radio frequency data are integrated for physiological monitoring, then measurement precision of thoracic fluid and bio-vibrational changes is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The processor acts as an intermediary that receives raw signals from ECG, vibrational, and radio frequency sensors, processes them into combinational physiological parameters, and generates clinically actionable outputs. This intermediary processing layer simplifies the complexity by systematically integrating multiple data sources through defined algorithms and analysis techniques.
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
Enhances the accuracy of predicting and managing acute episodes by providing personalized treatment regimens and reducing hospitalizations through continuous, non-invasive monitoring of thoracic fluid and bio-vibrational changes.
Implementation Method 1
produce radio frequency information responsive to reflected radio frequency electromagnetic energy received through the one or more radio frequency antennas and reflected from within the thoracic cavity of the patient
Implementation Method 2
a vibrational sensor coupled to the patient and configured to detect one or more cardio-vibrational signals of the patient
Data Source
AI summary
A patient monitoring device includes an ECG sensor coupled to a patient, a sensor coupled to the patient and configured to detect bio-vibrational signals, and a radiofrequency monitoring device configured to produce information responsive to electromagnetic energy reflected from the patient's thoracic cavity. A processor processes the ECG signals, the bio-vibrational signals, and the radio frequency information to generate a plurality of physiological parameters of the patient. The processor also performs at least one of a predictive analysis and a trend analysis of the plurality of physiological parameters to determine a current clinical condition of the patient. The trend analysis includes determining a substantial relationship between changes in the plurality of physiological parameters. The processor can also compare the current clinical condition of the patient to predetermined clinically actionable criteria to determine one or more clinically actionable events and provide an output relating to one or more clinically actionable events.