Photoplethysmography Algorithm for Cardiovascular Monitoring
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Solution Overview
Problem
Current monitoring devices for cardiovascular insufficiency are insensitive, invasive, and require complex setups, making them unsuitable for low-acuity settings and less competent care providers, and they fail to effectively identify preload-responsive patients, leading to delayed treatment and potential organ failure.
Innovation Solution
A non-invasive device comprising a controller, transducer, and processor that uses a novel formula to generate meaningful outputs from non-invasive data, allowing for monitoring in various settings and by less skilled personnel, and includes a method to perturb the cardiovascular system to assess responsiveness to fluid resuscitation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-invasive monitoring is used, then ease of operation and adaptability improve, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent introduces an intermediary algorithm that processes non-invasive photoplethysmographic signals to extract hemodynamic parameters. The algorithm acts as a mediator between the non-invasive measurement and the physiological parameters of interest, enabling precise measurement of preload responsiveness without invasive procedures. The intermediary processing transforms raw optical signals into clinically useful hemodynamic assessments.
Solution Approach 2:
The patent applies parameter changes by analyzing variations in photoplethysmographic signal characteristics (amplitude, area, shape) in response to controlled perturbations. By monitoring how these signal parameters change during fluid challenge or passive leg raising, the system infers preload responsiveness. This approach converts simple optical parameter variations into precise hemodynamic assessments.
2Measurement precision
If current monitoring devices are used, then measurement precision may be maintained, but device complexity and ease of operation worsen
Solution Approach 1:
The patent extracts the essential monitoring function from complex invasive systems and implements it using a simple photoplethysmographic sensor. By taking out only the necessary measurement capability (optical detection of pulse waveform) and processing it through an algorithm, the system achieves precise hemodynamic monitoring without the complexity of invasive catheters, pumps, or sophisticated mechanical ventilation requirements.
Solution Approach 2:
The patent replaces mechanical invasive monitoring systems with an optical-based photoplethysmographic system. Instead of using mechanical catheters, pressure transducers, or physical maneuvers requiring specialized equipment, the system uses light absorption by blood to generate pulse waveform signals that are then processed algorithmically to assess hemodynamic status.
3Loss of information
If current monitoring approaches are used, then some measurement capability is provided, but loss of time and productivity worsen due to delayed treatment identification
Solution Approach 1:
The patent performs preliminary assessment of preload responsiveness using the algorithmic processing of photoplethysmographic signals before initiating fluid resuscitation. By evaluating the change in pulse waveform parameters in response to a small perturbation (fluid challenge or passive leg raising), the system determines in advance whether the patient will respond to fluid therapy. This preliminary action prevents delayed treatment by identifying preload-responsive patients early, allowing immediate appropriate intervention.
Data Source
AI summary
In an embodiment, the present invention provides a device that identifies cardiovascular dysfunction of a subject. The claimed device comprises a controller, a transducer, and a processor. The controller initiates collection of a plurality of data related to a physiological condition. The transducer collects data over a plurality of cycles and transfers the data to the processor, which reduces the received data signal into an output using a novel formula. In an example the data correlate with data that are directly related to cardiovascular dysfunction but that are of limited use.