# Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring
## 2 Background and Related Work
### Wireless ECG Sensor  
The wireless ECG sensor investigated in this paper is certified as a Class IIa medical device and is intended for long-term continuous personal cardiac monitoring [4]. It has been available on the market since 2016 under the trademark Savvy ECG ([[http://savvy.si/](http://savvy.si/)]([http://savvy.si/](http://savvy.si/)), accessed on 29 April 2022). Physically, the sensor is small (dimensions: 130 \(\times\) 35 \(\times\) 14 mm) and light (weight: 21 g). It acts as a body gadget that can be worn on the skin by attaching it with two standard self-adhesive electrodes (Figure 1). Its outer shell is made of a waterproof and biocompatible plastic material. The device primarily measures differential surface electrical potential (ECG) between the proximal electrodes--a signal denoted as differential lead or differential ECG [22]. Experiments have shown that the optimal distance between the electrodes, which ensures satisfactory signal-to-noise ratio as well as minimal discomfort for the user, is around 8 cm [22] of flexible connection between the electrodes. This flexible part in combination with the snap fasteners that attach to the electrodes make the sensor adjustable for positioning and resilient to the movements of the user. The hardware of the sensor implements the measurement functionality as follows: The first conversion of the measured quantity is made with an analog circuitry, including preamplifier and analog filters, that takes the input signal and converts it to appropriate voltage levels. Afterwards, the signal is passed to the MCU that converts the analog input signal into digital by sampling it with a predefined frequency and stores the samples into a memory buffer for further transfer. The samples are next transmitted in bulk by the MCU over a standard SPI (Serial Peripheral Interface) to the chip with a radio transceiver. The signal is then wirelessly transferred to a personal digital assistant (PDA), such as a smartphone or a tablet, by using a custom wireless protocol built on top of the BLE. The selected BLE radio for the sensor is the nRF8001 module by Nordic semiconductor, which supports Bluetooth 4.0 low-energy specifications. On the PDA, the data is stored and visualized in real time [23]. The ECG sensor represents a peripheral device in terms of BLE device classification, whereas the main device for ECG sample collection, i.e., the PDA, is called a central device. The two electrical connectors of the sensor, additionally to connecting the electrodes to perform measurements, are also used to plug the sensor on a battery charger. A charger circuitry in the sensor detects when the battery charger is connected to the input snap terminals and puts the sensor in charging mode. Moreover, the battery charger is implemented as a charging dock designed to prevent reverse connection of the sensor on the charger. Additional components of the sensor, contributing to preserving sensor's energy, are: the circuit breaker that isolates all the other circuits from the battery in order to minimize power consumption when the sensor is stored for a longer period of time and the power delivery circuitry used to lower the power usage while the sensor is not active by enabling the MCU to selectively deliver power to other building blocks. As a compromise among sustainable power consumption, acceptable measurement quality, and acceptable bandwidth for most smartphones to handle, a moderate resolution of 128 samples/s is used and enforced by the software, but the hardware allows for it to be increased up to 1024 samples/s. The sensor has found its application in several areas in medicine and in every-day life [4]. It has been demonstrated that the moderate-resolution ECG is suitable for long-term personal cardiac activity monitoring, as well as for clinical use, such as screening patients with a suspicion of irregular heartbeat [13], prospective study of atrial fibrillation [24], and continuous remote monitoring of chronic obstructive pulmonary disease (COPD) patients [25].