Department of Communication Systems, Jožef Stefan Institute, 1000 Ljubljana, Slovenia.
Sensors (Basel). 2022 Jul 6;22(14):5070. doi: 10.3390/s22145070.
The paper analyses the autonomy of a wireless body sensor that continuously measures the potential difference between two proximal electrodes on the skin, primarily used for measuring an electrocardiogram (ECG) when worn on the torso. The sensor is powered by a small rechargeable battery and is designed for extremely low power use. However, the autonomy of the sensor, regarding its power consumption, depends significantly on the measurement quality selection, which directly influences the amount of data transferred. Therefore, we perform an in-depth analysis of the power consumption sources, particularly those connected with the Bluetooth Low Energy (BLE) communication protocol, in order to model and then tune the autonomy of the wireless low-power body sensor for long-term ECG monitoring. Based on the findings, we propose two analytical models for power consumption: one for power consumption estimation in idle mode and the other one for power estimation in active mode. The proposed models are validated with the measured power consumption of the ECG sensor at different ECG sensor settings, such as sampling rate and transmit power. The proposed models show a good fit to the measured power consumption at different ECG sensor sampling rates. This allows for power consumption analysis and sensor autonomy predictions for different sensor settings. Moreover, the results show that the transmit power has a negligible effect on the sensor autonomy in the case of streaming data with high sampling rates. The most energy can be saved by lowering the sampling rate with suitable connection interval and by packing as much data as possible in a single BLE packet.
本文分析了一种无线体传感器的自主性，该传感器持续测量皮肤两个近端电极之间的电势差，主要用于在躯干上佩戴时测量心电图（ECG）。该传感器由一个小型可充电电池供电，设计用于极低功耗。然而，传感器的自主性，即其功耗，很大程度上取决于测量质量的选择，这直接影响传输的数据量。因此，我们深入分析了功耗源，特别是与蓝牙低能 (BLE) 通信协议相关的功耗源，以便对无线低功耗体传感器进行建模，并调整其用于长期 ECG 监测的自主性。基于研究结果，我们提出了两种用于功率消耗估计的分析模型：一种用于空闲模式下的功率消耗估计，另一种用于活动模式下的功率估计。所提出的模型通过在不同的 ECG 传感器设置（如采样率和传输功率）下测量 ECG 传感器的实际功率消耗进行验证。所提出的模型与不同 ECG 传感器采样率下的实际功率消耗具有很好的拟合度。这使得可以针对不同的传感器设置进行功耗分析和传感器自主性预测。此外，结果表明，在以高采样率传输数据流的情况下，传输功率对传感器自主性的影响可以忽略不计。通过降低采样率并在单个 BLE 数据包中尽可能多地打包数据，可以最大程度地节省电量。
