Cardiovascular diseases are best diagnosed using multiple modalities that assess both the heart's electrical and mechanical functions. While effective, imaging techniques like echocardiography and nuclear imaging are costly and not widely accessible. More affordable technologies, such as simultaneous electrocardiography (ECG) and phonocardiography (PCG), may provide valuable insights into electromechanical coupling and could be useful for prescreening in low-resource settings. Using physical stress test data from the EPHNOGRAM ECG-PCG dataset, collected from 23 healthy male subjects (age: 25.4+/-1.9 yrs), we investigated electromechanical intervals (RR, QT, systolic, and diastolic) and their interactions during exercise, along with hysteresis between cardiac electrical activity and mechanical responses. Time delay analysis revealed distinct temporal relationships between QT, systolic, and diastolic intervals, with RR as the primary driver. The diastolic interval showed near-synchrony with RR, while QT responded to RR interval changes with an average delay of 10.5s, and the systolic interval responded more slowly, with an average delay of 28.3s. We examined QT-RR, systolic-RR, and diastolic-RR hysteresis, finding narrower loops for diastolic RR and wider loops for systolic RR. Significant correlations (average:0.75) were found between heart rate changes and hysteresis loop areas, suggesting the equivalent circular area diameter as a promising biomarker for cardiac function under exercise stress. Deep learning models, including Long Short-Term Memory and Convolutional Neural Networks, estimated the QT, systolic, and diastolic intervals from RR data, confirming the nonlinear relationship between RR and other intervals. Findings highlight a significant cardiac memory effect, linking ECG and PCG morphology and timing to heart rate history.

翻译：心血管疾病的最佳诊断需采用多种模式评估心脏的电学与机械功能。尽管超声心动图及核医学成像等技术有效，但其成本高昂且普及性有限。同步心电图与心音图等经济型技术可为机电耦合提供重要见解，并适用于资源匮乏场景的预筛查。基于EPHNOGRAM ECG-PCG数据集中23名健康男性受试者（年龄：25.4±1.9岁）的体力应激测试数据，本研究探究了运动过程中机电间期（RR、QT、收缩期与舒张期间期）及其相互作用，以及心脏电活动与机械响应间的迟滞现象。时延分析揭示了QT间期、收缩期间期和舒张期间期之间以RR间期为主导的显著时序关系：舒张期间期与RR间期近乎同步；QT间期对RR间期变化的平均响应延迟为10.5秒；收缩期间期的响应更为迟缓，平均延迟达28.3秒。通过分析QT-RR、收缩期-RR及舒张期-RR迟滞环，发现舒张期-RR迟滞环较窄而收缩期-RR迟滞环较宽。心率变化与迟滞环面积呈现显著相关性（平均0.75），表明等效圆面积直径可作为运动应激下心功能的有潜力的生物标志物。基于长短期记忆网络与卷积神经网络等深度学习模型，通过RR数据对QT、收缩期及舒张期间期进行估计，证实了RR间期与其他间期之间的非线性关系。研究结果揭示了显著的心脏记忆效应，将心电图与心音图的形态特征及时序特性与心率历史相关联。