Miao Fen, Cheng Yayu, He Yi, He Qingyun, Li Ye
Key Laboratory for Health Informatics of the Chinese Academy of Sciences (HICAS), Shenzhen Institutes of Advanced Technology, 1068 Xueyuan Boulevard, Shenzhen 518055, China.
Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen 518055, China.
Sensors (Basel). 2015 May 19;15(5):11465-84. doi: 10.3390/s150511465.
Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user's physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.
连续数小时监测心电图信号并结合活动状态对于预防心血管疾病非常重要。传统的心电图动态监测仪通常携带不便，因为它有许多电极附着在胸部且重量较大。这项工作提出了一种可穿戴的、低功耗的情境感知心电图监测系统，该系统将智能手机的内置运动传感器与自行设计的心电图传感器集成在一起。可穿戴心电图传感器由一个完全集成的模拟前端（AFE）、一个商用微控制单元（MCU）、一个安全数字（SD）卡和一个蓝牙模块组成。由于采用了AFE设计，整个传感器体积非常小，尺寸仅为58×50×10毫米，适用于可穿戴监测应用，并且在一轮完整的心电图采集过程中的总功耗仅为12.5毫瓦。借助智能手机的内置运动传感器，所提出的系统可以计算并识别用户的身体活动，从而为连续的心电图监测提供情境感知信息。实验结果证明了所提出系统在提高心律失常诊断准确性以及识别不同活动中最常见的异常心电图模式方面的性能。总之，我们提供了一种可穿戴、准确且节能的系统，用于长期的情境感知心电图监测，无需在运动传感器设计上额外花费成本，而是借助广泛使用的智能手机。
