# Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring
###### Abstract  
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. Bluetooth Low Energy; ECG; wireless sensor; power consumption; autonomy estimation 202  
Bluetooth technology with Bluetooth Low Energy (BLE), enabling novel applications in health care, fitness, and home entertainment industries. BLE, a proprietary wireless interface, is often selected mainly due to its general ubiquity in modern personal mobile devices. Unlike all the other previously mentioned communication technologies, BLE is the only one readily available in nearly every new smartphone, tablet or smart watch. The main advantages of using standardized and widely spread technology are great availability, standardized communication interfaces, great amount of support available in the community, etc. Despite the ever-present possibility of creating slightly better wireless communication technology regarding the power efficiency per transferred information, the greater availability in consumer devices, and consequently lower price, outweigh small differences in performance. One particular example that we focus on in this paper is the energy consumption of a miniature smart wireless ECG sensor, which is an important topic when providing long power autonomy in the scope of a framework for long-term ECG monitoring [4], e.g., to discover rarely occurring anomalies in ECG, which often do not occur within 30- or less-second ECG measurements routinely performed within primary health care. In combination with a ubiquitous smartphone with BLE connectivity and a large storage capacity, the hardware requirements for ECG sensors are minimal, making the device viable for mass production with a relatively low price. We were able to analyze such a device, which was recently introduced into the local health-care system. Energy consumption in battery-powered wireless sensors is important because of its impact on the sensor's operating time. Having a model to estimate the energy consumption based on the sensor's activity patterns and workload can help engineers to develop energy-efficient applications and obtain quick estimations without thorough testing with actual devices. It can also help the end user or technician to obtain a good estimate of the expected device operating time according to the device settings. These are the reasons for energy consumption modeling in wireless sensor networks (WSNs) being an active research topic.