Wang Yishan, Doleschel Sammy, Wunderlich Ralf, Heinen Stefan
Chair of Integrated Analog Circuits and RF Systems, RWTH Aachen University, D-52062, Aachen, Germany.
J Med Syst. 2016 Jul;40(7):170. doi: 10.1007/s10916-016-0526-1. Epub 2016 May 30.
In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.
本文首先设计了一种基于低功耗蓝牙（BLE）的可穿戴无线心电图系统。它能够检测三导联心电图信号，且完全无线化。其次，实现了数字压缩感知（CS）技术以提高无线心电图传感器的能量效率。对不同的稀疏基、各种压缩比（CR）以及几种重构算法进行了仿真和讨论。最后，通过智能手机上的安卓应用程序（App）进行重构，以实时显示信号。测量了功率效率，并与未采用CS的系统进行比较。通过仿真选择了由三级分解的db4小波系数构建的最优满足基、1位伯努利随机矩阵以及最合适的重构算法，并应用于传感器节点和App。信号在智能手机的App上成功重构并显示。传感器节点的电池续航时间从55小时延长至67小时。所提出的带有CS的无线心电图系统可显著延长电池续航时间22%。该系统具有紧凑的特性和较长的工作时间，为长期家庭护理应用提供了一种可行的解决方案。
