ROSC Detection via Pulse Oximetry Waveform Analysis
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Solution Overview
Problem
Current CPR methods lack effective real-time recognition of restoration of spontaneous circulation (ROSC), leading to potential interference between spontaneous circulation and chest compression, which can exacerbate heart damage and arrest.
Innovation Solution
A ROSC recognition system utilizing arterial pulse oximetry technology combined with digital signal processing, including time-domain and frequency-domain analysis, to detect continuous and regular envelope features or spectral peaks, allowing for real-time identification of ROSC during CPR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CPR is continuously performed without ROSC recognition, then CPR effectiveness is maintained, but heart damage is exacerbated due to interference between spontaneous circulation and chest compression
Solution Approach 1:
The patent implements preliminary ROSC detection through pulse oximetry waveform analysis before making the decision to stop CPR. The system continuously monitors arterial blood oxygen saturation and waveform characteristics, enabling early identification of spontaneous circulation restoration. This preliminary detection mechanism allows healthcare providers to stop CPR at the optimal moment, preventing heart damage while maintaining CPR effectiveness throughout the resuscitation process.
2Object-affected harmful factors
If ROSC recognition system is implemented, then heart damage is prevented, but device complexity increases
Solution Approach 1:
The patent leverages the multi-functionality of pulse oximetry technology, which is already a standard component in CPR monitoring systems. The existing pulse oximeter is extended to perform both its traditional blood oxygen saturation monitoring function and the additional ROSC detection function by analyzing waveform characteristics. This approach integrates ROSC recognition into the existing monitoring framework without requiring entirely new specialized equipment, thereby limiting the increase in device complexity while still preventing heart damage through timely ROSC identification.
3Measurement precision
If pulse oximetry waveform analysis is used for ROSC detection, then measurement precision is improved, but ease of operation decreases
Solution Approach 1:
The patent implements automated feedback mechanisms where the pulse oximetry system continuously analyzes waveform characteristics and provides real-time ROSC status information to the user interface. The system automatically processes complex waveform parameters such as amplitude, frequency, and morphology changes, translating them into clear ROSC detection results. This automated feedback loop maintains high measurement precision through sophisticated waveform analysis while preserving ease of operation by eliminating the need for manual interpretation of complex waveforms by healthcare providers.
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 timely determination of ROSC, reducing potential cardiac damage by informing healthcare professionals when to stop CPR and improving CPR effectiveness.
Implementation Method 1
ROSC in CPR process can be recognized based on arterial pulse oximetry technology
Implementation Method 2
Detection of a spontaneous pulse in photoplethysmograms during automated cardiopulmonary resuscitation in a porcine model
Data Source
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AI summary
This disclosure relates to devices and systems for real-time recognition of restoration of spontaneous circulation (ROSC) in cardio-pulmonary resuscitation (CPR) process. Recognition mechanisms in both time domain and frequency domain are provided for the ROSC recognition, where the time-domain recognition logic may detect the ROSC by recognizing envelope features of sampled signals in the time domain, and the frequency-domain recognition logic may detect the ROSC by recognizing spectral peaks at different frequency points continuously or significant variations of amplitude of spectral peaks in the frequency spectrum. Acquiring pulse oximetry waveform signals of a patient.