Robust Detection of Heart Beats in Multimodal Data: The PhysioNet/Computing in Cardiology Challenge 2014

This challenge aims to encourage the exploration of robust methods for locating heart beats in continuous long-term data from bedside monitors and similar devices that record not only ECG but usually other physiologic signals as well, including pulsatile signals that directly reflect cardiac activity, and other signals that may have few or no observable markers of heart beats. Our goal is to accelerate development of open-source research tools that can reliably, efficiently, and automatically analyze data such as that contained in the MIMIC II Waveform Database, making use of all relevant information.

本挑战旨在激励研究者探索在连续长期床旁监护仪及类似设备所记录的数据中定位心跳的稳健方法，这些设备不仅记录心电图（ECG），通常还包括其他生理信号，例如直接反映心脏活动的脉动信号，以及其他可能仅有少量或无可见心跳标记的信号。我们的目标是加速开源研究工具的开发，这些工具能够可靠、高效、自动地分析如MIMIC II波形数据库所包含的数据，并充分利用所有相关信息。