Fetal Heart Rate Baseline Identification via Dynamic Filtering

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Solution Overview

Problem

Current methods for calculating the Fetal Heart Rate (FHR) baseline are inaccurate and unstable due to interference from regular fetal movements and external stimuli, failing to account for changes in fetal states, leading to deviations from actual values and inability to display regular changes in fetal monitoring diagrams.

Innovation Solution

An apparatus and method involving a FHR data collecting module, preprocessing module, primary dominant peak value selecting module, and dynamic baseline identifying module, which collect, preprocess, and filter FHR data to identify a dynamic baseline using lowpass filtering and data recovery, effectively accounting for fetal state changes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If the average method is used to calculate FHR baseline, then the calculation process is simple, but the calculated baseline deviates from actual values due to interference from fetal movements and external stimuli

Engineering Contradiction:
Improvecalculation process simplicityVSAvoidbaseline accuracy
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent extracts and removes interference data (fetal movements and external stimuli) from the FHR signal before baseline calculation. By identifying and eliminating these harmful factors, the remaining data provides an accurate baseline without requiring complex processing of the entire signal.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces an intermediary processing step that identifies and separates interference components from the FHR signal. This intermediary layer allows the simple average method to work effectively on cleaned data, bridging the gap between simplicity and accuracy.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Productivity

If the average method is used to calculate FHR baseline, then only one value is obtained from all data, but this prevents identification of baseline changes with different fetal states

Engineering Contradiction:
Improvedata processing efficiencyVSAvoidresponse to different fetal states
Core Design Contradiction:
ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent implements a dynamic baseline identification approach that adapts to different fetal states. Instead of calculating a single static average, the system continuously processes data in segments and identifies baseline changes according to fetal state variations, making the baseline calculation adaptable and versatile.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent segments the FHR data into different portions corresponding to different fetal states. By dividing the data and calculating baselines for each segment separately, the system maintains processing efficiency while capturing state-specific baseline variations.

Inventive Principle:
Principle #1Segmentation

3Quantity of substance

If regular FHR changes are not filtered out, then all data is used in calculation, but the calculated baseline is unstable and inaccurate

Engineering Contradiction:
Improvedata utilizationVSAvoidbaseline stability
Core Design Contradiction:
Quantity of substanceVSReliability

Solution Approach 1:

The patent converts the harmful effect of regular FHR changes (fetal movements and external stimuli) into a beneficial identification process. By detecting these regular changes, the system can selectively exclude them from baseline calculation, transforming what was previously harmful noise into useful information for improving baseline stability.

Inventive Principle:
Principle #22Blessing in disguise (Convert harm into benefit)

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

The solution accurately reflects baseline levels and changes, filtering out interference and providing a stable and accurate FHR baseline representation across different fetal states, enhancing the accuracy of fetal monitoring.

Implementation Method 1

carries out the lowpass filtering and data recovery for the sequence B(m) to further obtain the dynamic FHR baseline

Methodology Applied
Scientific EffectLowpass filtering: Filter (electronic)

Data Source

PatentEP2676601B1Apparatus and method for automatically identifying fetal heart rate baseline
Publication Date: 2017.04.26 EDAN INSTR
  • EP2676601B1 patent drawingFigure 1
  • EP2676601B1 patent drawingFigure 2
  • EP2676601B1 patent drawingFigure 3~4

AI summary

The present invention relates to the field ofbio-medical signal processing, particularly relates to an apparatus and method for automatically identifying FHR baseline, comprising: collecting FHR data within a preset duration to obtain an FHR data sequence h' (n); preprocessing the collected FHR data sequence h' (n) to obtain a corresponding FHR data sequence during the preprocessing; selecting a primary dominant peak value according to the frequency distribution of the corresponding FHR data sequence during the preprocessing; and identifying a dynamic baseline according to the corresponding FHR data sequence and the primary dominant peak value during the preprocessing to obtain the dynamic baseline, and display and print the dynamic baseline. The technical solution provided in the present invention effectively prevents the impact caused by regular change of the FHR to the baseline solution, and accurately reflects the FHR baseline and changes thereof of a fetus under different conditions.