Singstad Bjorn-Jostein
Department of Computational PhysiologySimula Research Laboratory Kristian Augusts Gate 23,0164OsloNorway.
IEEE Open J Eng Med Biol. 2022 Oct 21;3:162-166. doi: 10.1109/OJEMB.2022.3214719. eCollection 2022.
Athletes often have training-induced remodeling of the heart, and this can sometimes be seen as abnormal but non-pathological changes in the electrocardiogram. However, these changes can be confused with severe cardiovascular diseases that, in some cases, can cause cardiovascular death. Electrocardiogram data from athletes is therefore important to learn more about the difference between normal athletic remodeling and pathological remodeling of the heart. This work provides a dataset of electrocardiograms from 28 Norwegian elite endurance athletes. The electrocardiograms are standard 12-lead resting ECGs, recorded for 10 seconds while the athlete's lay supine on a bench. The electrocardiograms were then interpreted by an interpretation algorithm and by a trained cardiologist. The electrocardiogram waveform data and the interpretations were stored in Python Waveform Database format and made publicly available through PhysioNet.
运动员经常会因训练导致心脏重塑，有时这在心电图中可表现为异常但非病理性的变化。然而，这些变化可能会与严重的心血管疾病相混淆，在某些情况下，严重的心血管疾病可能会导致心血管死亡。因此，运动员的心电图数据对于深入了解正常运动性心脏重塑与病理性心脏重塑之间的差异非常重要。这项工作提供了28名挪威精英耐力运动员的心电图数据集。这些心电图是标准的12导联静息心电图，在运动员仰卧于长椅上时记录10秒。然后通过解读算法和训练有素的心脏病专家对心电图进行解读。心电图波形数据和解读结果以Python波形数据库格式存储，并通过PhysioNet公开提供。
