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BSeg++: a modified blind segmentation method for Ballistocardiogram cycle extraction.

Alireza Akhbardeh1, Bozena Kaminska, Kouhyar Tavakolian

  • 1Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. alireza.akhbardeh@tut.fi

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
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This study introduces BSeg++, an improved algorithm for extracting cardiac cycles and H-I-J components from Ballistocardiogram (BCG) signals without Electrocardiogram (ECG) synchronization. The method accurately segments BCG and ECG signals, even with motion artifacts.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Physiology
  • Signal Processing

Background:

  • Ballistocardiogram (BCG) analysis is crucial for non-invasive cardiac monitoring.
  • Existing methods for BCG cycle extraction often require Electrocardiogram (ECG) synchronization or suffer from inaccuracies due to artifacts.
  • Previous algorithms for blind BCG segmentation produced redundant cycles from motion or signal fluctuations.

Purpose of the Study:

  • To develop an improved algorithm (BSeg++) for accurate BCG signal segmentation and H-I-J complex extraction.
  • To enable BCG analysis without the need for synchronized ECG data.
  • To enhance the robustness of cardiac cycle extraction in the presence of common signal interferences.

Main Methods:

  • Modification of a blind segmentation algorithm to address issues of redundant cycle extraction.

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  • Integration of a new feature for detecting the H-I-J complexes within the BCG signal.
  • Adaptation of the algorithm for simultaneous extraction of cardiac cycles and R-S-T components from ECG signals.

    • Main Results:

    • The BSeg++ algorithm successfully segmented BCG signals and extracted H-I-J components without ECG synchronization.
    • The method demonstrated high accuracy in extracting cardiac cycles and components from both BCG and ECG signals.
    • Negligible errors were observed even in the presence of motion artifacts, BCG fluctuations, latency, and non-linear disturbances in initial tests on twenty subjects.

    Conclusions:

    • BSeg++ offers a robust and accurate solution for non-invasive cardiac cycle and component extraction from BCG signals.
    • The algorithm's ability to function without ECG synchronization simplifies clinical application and data acquisition.
    • The enhanced method holds potential for improved cardiovascular monitoring and diagnostics.