Lazović Aleksandar, Atanasoski Vladimir, Tadić Predrag, Djordjević Natalija, Tiosavljević Maša, Ivanović Marija D, Hadžievski Ljupčo, Ristić Arsen, Vukčević Vladan, Petrović Jovana
Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Mike Petrovića Alasa 12-14, Belgrade, 11000, Serbia.
School of Electronic Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, Belgrade, 11000, Serbia.
Sci Data. 2025 Aug 20;12(1):1452. doi: 10.1038/s41597-025-05781-4.
Noninvasive electromechanical assessment of cardiovascular function is emerging as a cost-effective method for diagnosis of heart failure and arterial diseases, and for telemedical monitoring of blood pressure and neural disorders. It encompasses simultaneous acquisition of electrocardiographic, phonocardiographic, arterial-pulse, chest-vibration, bioimpedance and other waveforms. The phases and amplitudes of these waveforms are used for construction of disease biomarkers. The procedure includes corrections of biomarker values to daily variation and excursions of heart rate. However, datasets that enable a systematic study of the effects of heart rate on mechanical waveforms are currently not available. Here, we describe SensSmartTech - the first dataset of multiparametric cardiovascular signals systematically measured in a large span of heart rates from 52 to 182 beats per minute, achieved by running on a treadmill. Besides providing the data for biomarker correction, the dataset enables new insights into the cardio-respiratory and electro-mechanical couplings in the cardiovascular system.
心血管功能的无创机电评估正在成为一种经济高效的方法,用于心力衰竭和动脉疾病的诊断,以及血压和神经疾病的远程医疗监测。它包括同时采集心电图、心音图、动脉脉搏、胸部振动、生物阻抗和其他波形。这些波形的相位和幅度用于构建疾病生物标志物。该过程包括将生物标志物值校正为每日变化和心率波动。然而,目前尚无能够系统研究心率对机械波形影响的数据集。在此,我们描述了SensSmartTech——第一个多参数心血管信号数据集,该数据集通过在跑步机上跑步,在每分钟52至182次心跳的大心率范围内进行了系统测量。除了为生物标志物校正提供数据外,该数据集还能让人对心血管系统中的心肺和机电耦合有新的认识。