School of Electronics Engineering, Kyungpook National University, Daegu 702-701, South Korea.
Sci Data. 2017 Apr 25;4:170052. doi: 10.1038/sdata.2017.52.
Chest surface motion is of significant importance as it contains information of respiratory and cardiac systems together with the complex coupling between these two systems. Chest surface motion is not only critical in radiotherapy, but also useful in personalized systems for continuous cardiorespiratory monitoring. In this dataset, a multimodal setup is employed to simultaneously acquire cardiorespiratory signals. These signals include high-density trunk surface motion (from 16 distinct locations) with VICON motion capture system, nasal breathing from a thermal sensor, respiratory effort from a strain belt and electrocardiogram in lead-II configuration. This dataset contains 72 trials recorded from 11 participants with a cumulative duration of approximately 215 min under various conditions such as normal breathing, breath-hold, irregular breathing and post-exercise recovery. The presented dataset is not only useful for evaluating prediction algorithms for radiotherapy applications, but can also be employed for the development of techniques to evaluate the cardio-mechanics and hemodynamic parameters of chest surface motion.
胸部表面运动非常重要，因为它包含了呼吸系统和心血管系统的信息，以及这两个系统之间的复杂耦合。胸部表面运动不仅在放射治疗中至关重要，而且在用于连续心肺监测的个性化系统中也很有用。在这个数据集里，采用了多模态设置来同时获取心肺信号。这些信号包括来自 16 个不同位置的高密度胸部表面运动（使用 VICON 运动捕捉系统）、来自热传感器的鼻呼吸、应变带的呼吸努力以及导联 II 配置的心电图。这个数据集包含了 11 名参与者在不同条件下记录的 72 次试验，累计持续时间约为 215 分钟，这些条件包括正常呼吸、屏气、不规则呼吸和运动后恢复。所提供的数据集不仅可用于评估放射治疗应用的预测算法，还可用于开发技术以评估胸部表面运动的心脏力学和血液动力学参数。
