Synchronous post-exercise electrocardiogram, phonocardiogram, photoplethysmograms and seismocardiogram.
Aleksandar Lazović1, Vladimir Atanasoski1, Predrag Tadić2
1Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovića Alasa 12-14, Belgrade, 11000, Serbia.
Scientific Data
|August 20, 2025
Summary
This study introduces SensSmartTech, the first dataset of cardiovascular signals across a wide heart rate range. This resource aids in correcting disease biomarkers and understanding cardio-respiratory and electro-mechanical couplings.
Area of Science:
- Biomedical Engineering
- Cardiovascular Physiology
- Medical Data Science
Background:
- Noninvasive electromechanical assessment is crucial for diagnosing heart failure and arterial diseases.
- Existing methods lack datasets to systematically study heart rate's effect on mechanical waveforms.
Purpose of the Study:
- To introduce SensSmartTech, the first dataset of multiparametric cardiovascular signals across a wide heart rate range.
- To enable systematic study of heart rate effects on cardiovascular waveforms for biomarker correction and physiological insights.
Main Methods:
- Acquired simultaneous electrocardiographic, phonocardiographic, arterial-pulse, chest-vibration, and bioimpedance waveforms.
- Systematically measured signals in 52-182 beats per minute heart rate range using a treadmill protocol.
Main Results:
- The SensSmartTech dataset provides comprehensive multiparametric cardiovascular signals.
- Data spans a wide heart rate variability, from 52 to 182 bpm, achieved via controlled exercise.
Conclusions:
- SensSmartTech is a valuable resource for refining cardiovascular disease biomarkers.
- The dataset facilitates novel research into cardio-respiratory and electro-mechanical couplings.
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