Wearable Sensor Cardio Profile Vector Estimation
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Solution Overview
Problem
Current methods for measuring cardiopulmonary function are invasive, expensive, inconvenient, and not suitable for long-term surveillance or repeated measurements, often providing noisy and coarse results, which limits their effectiveness in monitoring health changes over time, especially for patients with chronic diseases.
Innovation Solution
A machine learning-based system utilizing wearable sensors to collect data from daily activities, which generates a cardio profile vector through neural networks, allowing for the estimation of VO2Max and cardiopulmonary health status without the need for invasive tests or specific exercise routines, enabling continuous and accurate monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional objective measurements like VAT tests, CPET, or cardiac echo doppler are used, then measurement precision of cardiopulmonary function is improved, but device complexity and ease of operation deteriorate due to invasive procedures, specialty equipment, and laboratory settings required
Solution Approach 1:
The patent replaces complex mechanical measurement systems (breathing masks, exercise equipment, blood sampling apparatus) with wearable electronic sensors that continuously monitor physiological parameters during natural daily activities. This substitution maintains measurement precision while dramatically improving ease of operation and patient comfort.
Solution Approach 2:
The patent creates a simplified copy of laboratory-based cardiopulmonary testing by using wearable sensors to capture equivalent physiological data during everyday activities. Instead of replicating the complex laboratory setup, the system captures the essential physiological responses to exercise and stress that occur naturally during daily life, providing comparable health assessments without the infrastructure requirements.
2Measurement precision
If traditional objective measurements are deployed, then measurement precision is improved, but loss of time and productivity worsen due to the need for specialized equipment setup and laboratory visits
Solution Approach 1:
The patent implements preliminary action by having patients wear the sensor device during their normal daily activities before any clinical assessment is needed. The device continuously collects physiological data during natural exercise and stress events, so that when clinical evaluation is required, the data is already available immediately without requiring time-consuming laboratory testing or equipment setup.
Solution Approach 2:
The patent enables continuous monitoring of cardiopulmonary function throughout the patient's daily life rather than relying on discrete, time-limited laboratory tests. This continuous data collection captures physiological responses across multiple exercise intensities and durations, providing comprehensive assessment without requiring the patient to dedicate specific time for testing.
3Measurement precision
If traditional measurements are used, then measurement precision is improved, but object-generated harmful factors worsen due to patient discomfort, reluctance to perform effort challenges, and potential harm from invasive procedures
Solution Approach 1:
The patent replaces invasive mechanical measurement methods (blood sampling, breathing masks, forced exercise equipment) with non-invasive wearable sensors that monitor physiological parameters during natural activities. This substitution eliminates the discomfort and potential harm associated with invasive procedures while maintaining measurement precision through continuous monitoring of heart rate, oxygen saturation, and other vital signs.
Solution Approach 2:
The patent enables patients to perform their own monitoring without requiring assistance from trained technicians or specialized equipment. The wearable device automatically collects and processes physiological data during the patient's normal daily activities, eliminating the need for supervised laboratory testing and reducing the psychological burden of performing challenging exercise tests under observation.
Data Source
AI summary
An estimate of a functional capacity such as VO2Max is made by applying the vital signs of a monitored human to a trained encoding neural network producing a cardio profile vector. The vector is applied to a trained functional capacity (VO2Max) neural network to estimate the functional capacity. Once estimated, an action is taken.