Computational Electrocardiography: Revisiting Hotter ECG Monitoring
Computational Electrocardiography: Revisiting Hotter ECG Monitoring
复制标题
DOI：
10.3414/me15-05-0009
复制
发表时间：
2016-01-01
影响因子：
1.7
通讯作者：
Marx, Nikolaus
中科院分区：
文献类型：
--
作者：
Deserno, Thomas M.;Marx, Nikolaus
背景资料：自1942年Goldberger引入12导联心电图（ECG）以来，这种诊断方法一直没有改变。目的：经过70年的技术发展，我们重新回顾霍尔特ECG从记录到理解的过程。一个根本性的变化是预见到“计算心电图”（CECG），其中连续监测产生了传统上不可能检查但需要有效计算方法的大数据量。我们绘制CECG和计算生物学之间的相似之处，特别是在计算机断层扫描，计算机放射学和计算机摄影。从这一点上，我们确定所需的技术和方法CECG.Results：实时传输的原始数据到有意义的参数，随着时间的推移进行跟踪将允许严重事件的预测，如心脏性猝死。从霍尔特的技术演变而来，带有蓝牙连接的织物嵌入式传感器的便携式智能手机将捕获嘈杂的原始数据（记录），随着时间的推移处理有意义的参数（分析），并将其传输到云服务以进行共享（处理），预测严重事件和报警（理解）。为了实现这一目标，以下领域需要更多的研究：i）信号处理，ii）周期分解; iii）周期归一化，iv）周期建模，v）临床参数计算，vi）生理建模，以及vii）事件prediction.Conclusions：我们将立即开始开发用于CECG分析和理解的方法。
Background: Since 1942, when Goldberger introduced the 12-lead electrocardiography (ECG), this diagnostic method has not been changed.Objectives: After 70 years of technologic developments, we revisit Holter ECG from recording to understanding.Methods: A fundamental change is foreseen towards "computational ECG" (CECG), where continuous monitoring is producing big data volumes that are impossible to be inspected conventionally but require efficient computational methods. We draw parallels between CECG and computational biology, in particular with respect to computed tomography, computed radiology, and computed photography. From that, we identify technology and methodology needed for CECG.Results: Real-time transfer of raw data into meaningful parameters that are tracked over time will allow prediction of serious events, such as sudden cardiac death. Evolved from Holter's technology, portable smartphones with Bluetooth-connected textile-embedded sensors will capture noisy raw data (recording), process meaningful parameters over time (analysis), and transfer them to cloud services for sharing (handling), predicting serious events, and alarming (understanding). To make this happen, the following fields need more research: i) signal processing, ii) cycle decomposition; Hi) cycle normalization, iv) cycle modeling, v) clinical parameter computation, vi) physiological modeling, and vii) event prediction.Conclusions: We shall start immediately developing methodology for CECG analysis and understanding.