Physiological Signal Qualification for Pulse Rate Accuracy

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Solution Overview

Problem

Existing physiological monitoring systems face challenges in accurately determining pulse rate from photoplethysmographic signals due to noise components, subject movement, and variations in pulse shape, especially in subjects with low perfusion or dicrotic notches, which can lead to incorrect rate determination.

Innovation Solution

The system employs a processing module with adjustable band-pass filtering and qualification techniques to reject noise, determine algorithm settings based on signal analysis, and manage status flags to ensure accurate pulse rate calculation, including correlation calculations and signal conditioning to mitigate noise and variations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If band-pass filtering is applied to reject noise, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvepulse rate determination accuracyVSAvoidprocessing module complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The processing module is divided into multiple independent operating modes (first mode with strict criteria, second mode with band-pass filtering). Each mode handles specific signal conditions independently, allowing complex processing to be broken down into manageable segments that can be selected based on signal quality

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically switches between different operating modes based on signal characteristics and qualification results. The band-pass filter parameters are adjustable and adapt to different physiological conditions, making the complexity dynamic rather than static

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If strict criteria are used to qualify calculated values, then measurement precision is improved, but productivity decreases

Engineering Contradiction:

Improvepulse rate accuracyVSAvoidrate calculation speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system performs preliminary qualification assessments using strict criteria before final rate determination. By pre-evaluating signal quality and applying qualification techniques early in the processing chain, the system prevents incorrect rates from being generated in the first place, rather than having to reject and reprocess them later

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The qualification techniques provide feedback on whether calculated parameters are indicative of true physiological parameters. This feedback loop allows the system to adjust processing intensity dynamically - applying strict qualification only when needed and allowing faster processing when signals are clearly valid

Inventive Principle:

Principle #23Feedback

3Measurement precision

If band-pass filter is tuned to reject noise, then measurement precision is improved, but reliability decreases

Engineering Contradiction:

Improvenoise rejection capabilityVSAvoidcorrect rate determination consistency

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

Qualification techniques monitor whether the band-pass filter is correctly tuned to the physiological rate. If the filter becomes tuned to noise or deviates from the correct rate, the qualification fails and triggers a mode switch or re-initialization, providing continuous feedback to maintain reliable operation

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system prepares multiple operating modes in advance with different filtering and qualification strategies. If the current mode fails to produce reliable results, the system has pre-configured alternative modes ready to switch to, cushioning against the risk of incorrect rate determination

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

4Adaptability or versatility

If multiple operating modes are implemented with different criteria, then adaptability is improved, but device complexity increases

Engineering Contradiction:

Improvehandling of varying physiological conditionsVSAvoidmode management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The processing module is designed as a universal system that can handle multiple physiological conditions and signal quality levels through its multiple operating modes. Rather than requiring separate dedicated systems for different conditions, one multi-functional module handles all scenarios by switching between modes based on signal characteristics

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS9192310B2Methods and systems for qualifying a calculated value based on baseline and deviation information

Publication Date: 2015.11.24 COVIDIEN LP

AI summary

A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a period associated with a physiological rate. The system may determine a first value indicative of a baseline of the physiological signal and a second value indicative of a deviation of the physiological signal from the baseline. The first value may, for example, be a median value, an average, or a coefficient corresponding to a best fit curve of the physiological signal. The second value may be a standard deviation value, a standard error, or a root mean square value based on the physiological signal. The system may qualify or disqualify the calculated value based on the first and second values.