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A pulse-foot-seeking algorithm for Doppler ultrasound waveforms.

¹Department of Medical Physics and Clinical Engineering, Leicester Royal Infirmary, England.

Clinical Physics and Physiological Measurement : an Official Journal of the Hospital Physicists' Association, Deutsche Gesellschaft Fur Medizinische Physik and the European Federation of Organisations for Medical Physics

|August 1, 1988

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A new algorithm accurately detects the start of the systolic upstroke in Doppler ultrasound waveforms. This method reliably identifies the

Area of Science:

Cardiovascular Ultrasound
Signal Processing
Medical Imaging

Background:

Accurate detection of the systolic upstroke, or 'pulse foot', in Doppler ultrasound is crucial for hemodynamic assessment.
Existing methods for pulse foot detection can be complex and sensitive to signal noise.
Automated and robust algorithms are needed to improve the efficiency and reliability of Doppler waveform analysis.

Purpose of the Study:

To describe a novel, simple algorithm for detecting and flagging the start of the systolic upstroke in Doppler ultrasound waveforms.
To evaluate the performance of this algorithm in a large dataset of cardiac cycles.

Main Methods:

The algorithm operates in three stages: locating the waveform maximum, identifying the point of maximum gradient on the upslope, and then finding the maximum rate of change of gradient at the waveform foot.

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The algorithm was applied to process Doppler signals from over 150,000 individual cardiac cycles.

Main Results:

The algorithm successfully detected and flagged the systolic upstroke in the vast majority of processed cardiac cycles.
The algorithm was only completely unsuccessful on signals that were deemed too noisy for analysis upon review.

Conclusions:

The described three-stage algorithm provides a simple and effective method for detecting the systolic upstroke in Doppler ultrasound.
This algorithm demonstrates high robustness and accuracy, even with large volumes of cardiac cycle data.
The method shows significant potential for improving automated analysis of Doppler ultrasound signals in clinical practice.