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Precise peak width estimation for solving key challenges in biosignal and spectral analysis.

Cristina Rueda1, Itziar Fernández1, Christian Canedo1

  • 1Department of Statistics and Operations Research, University of Valladolid, 47011, Valladolid, Spain.

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|March 15, 2026
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Summary
This summary is machine-generated.

This study introduces a new Frequency Modulated Möbius (FMM) decomposition method for accurately estimating peak width and wave duration (WD). The novel approach enhances signal analysis in fields like electrocardiogram (ECG) and spectroscopy.

Keywords:
ECG segmentsFMM modelFWHMPeak estimationXPS

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Area of Science:

  • Signal Processing
  • Biomedical Engineering
  • Analytical Chemistry

Background:

  • Accurate estimation of peak width and wave duration (WD) is crucial in diverse scientific fields.
  • Traditional methods like Full Width at Half Maximum (FWHM) struggle with complex data, including overlapping peaks, asymmetry, noise, and multi-channel signals.

Purpose of the Study:

  • To introduce a novel method for estimating peak width and WD using Frequency Modulated Möbius (FMM) decomposition.
  • To develop a parametric expression for FWHM and a new WD measure.
  • To demonstrate the method's robustness and flexibility in handling various signal complexities.

Main Methods:

  • Utilized Frequency Modulated Möbius (FMM) decomposition to analyze the oscillatory nature of signals.
  • Derived a parametric expression for Full Width at Half Maximum (FWHM).
  • Proposed a novel Wave Duration (WD) measure.

Main Results:

  • The FMM-based method provides robust and flexible estimation of peak width and WD.
  • Successfully applied the WD measure to electrocardiogram (ECG) signal analysis for critical cardiac activity segments.
  • Evaluated the new FWHM estimator in spectroscopic analysis for spectral resolution and material property determination.
  • Demonstrated superior performance compared to standard techniques in both ECG and spectroscopic applications.

Conclusions:

  • The novel FMM decomposition method offers a mathematically and physiologically sound approach to peak width and WD estimation.
  • The method effectively addresses limitations of traditional techniques, particularly with complex and multi-channel data.
  • The proposed measures show significant promise for advancing signal analysis in electrocardiogram (ECG) and spectroscopic applications.