ROSC Recognition via Pulse Oximetry Waveform Analysis
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Solution Overview
Problem
Current methods for recognizing restoration of spontaneous circulation (ROSC) during cardio-pulmonary resuscitation (CPR) are inadequate, as they do not accurately differentiate between spontaneous circulation and chest compression, which can interfere with hemodynamics and exacerbate cardiac damage.
Innovation Solution
The use of arterial pulse oximetry technology in combination with clinical physiological characteristics and digital signal processing methods to recognize ROSC in real-time, through the analysis of pulse oximetry waveform signals to distinguish between manual compression and spontaneous circulation signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse oximetry waveform analysis is used to recognize ROSC, then measurement precision is improved, but device complexity increases due to signal processing requirements
Solution Approach 1:
The patent replaces complex mechanical monitoring systems with optical pulse oximetry technology. By using light absorption characteristics of hemoglobin during arterial pulsation, the system achieves accurate ROSC detection through non-invasive optical measurement rather than mechanical or electrical monitoring, thereby improving measurement precision while managing device complexity
Solution Approach 2:
The patent utilizes changes in optical parameters (light absorption at different wavelengths) to detect physiological changes. By monitoring the AC component of pulse oximetry waveforms which reflects arterial blood volume changes, the system transforms unobservable ROSC events into measurable optical parameter variations, enabling accurate detection through parameter transformation
2Loss of time
If real-time ROSC recognition is implemented during CPR, then loss of time is reduced, but device complexity increases due to continuous monitoring requirements
Solution Approach 1:
The patent implements continuous real-time monitoring of pulse oximetry waveforms throughout the CPR process. By continuously analyzing the AC component of the waveform without interruption, the system ensures immediate detection of ROSC events as they occur, eliminating detection delays while the continuous nature of monitoring is managed through efficient signal processing algorithms
Solution Approach 2:
The system provides real-time feedback by continuously analyzing pulse oximetry signal characteristics and immediately identifying ROSC when specific waveform patterns emerge. The feedback mechanism processes incoming signal data continuously and triggers ROSC detection alerts without delay, enabling timely clinical decision-making through immediate information feedback
3Measurement precision
If frequency domain analysis is used to distinguish ROSC from chest compression, then measurement precision is improved, but loss of energy increases due to computational requirements
Solution Approach 1:
The patent replaces computationally intensive time-domain signal processing with frequency domain analysis using Fast Fourier Transform (FFT). By transforming the pulse oximetry waveform from time to frequency domain, the system efficiently distinguishes between chest compression artifacts and genuine ROSC signals through spectral peak identification, achieving high measurement precision with optimized computational energy consumption
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
This approach enables timely and accurate recognition of ROSC, allowing healthcare professionals to make informed decisions about when to stop CPR and improving the effectiveness of the CPR process.
Implementation Method 1
Spontaneous circulation recognition systems can be established based on the theory of pulse oximetry waveform analysis
Implementation Method 2
The processor can receive the pulse oximetry waveform signals including a first waveform signal corresponding to manual compression during the CPR process
Data Source
AI summary
This disclosure relates to methods, 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.