# Design of an Open Remote Electrocardiogram (ECG) Service
## 2 Related Works and Results Summary  
The electrical functionality of the heart is a piece of fundamental diagnostic information for the medical staff. Its recording dates back to the end of the 19 th century. From that time, research addressed first the amplification of the signal, whose amplitude is in the \(\mu V\) range, and next to the design of filters that remove unwanted components (like powerline _hum_, or signals from body activity) [2]. Computers came into play in connection with filters, and today they extract the fundamental features of the ECG signal [3]. [PERSON] et al. evaluate the computing resources needed, with a survey of research results in the field [4]. With the advent of the Web, storage and transport of ECG data emerge as a practical perspective. A study that in origin was aimed at using the ECG for personal identification [5] incidentally created a database of ECGs, which later became a precious resource for many. The availability of historical data is relevant for medical research, daily health-care use, and educational purposes. A primary concern with ECG and other medical data is their confidential nature. Cryptographic systems can be used to secure not only their transport but also their storage when a database aggregates data coming from several distinct sources in a Medical Sensor Network (MSN) [6]. The ubiquitous presence of wireless networks justifies the realization of portable (or even _wearable_[7]) ECG devices that forward the trace to a nearby Personal Computer (PC) or tablet. A Body (or Personal) Data Network (BAN) is a network infrastructure connecting many such devices. The idea dates back to 2001 when [PERSON] et al. [8] introduce the basic principles and concepts. Ten years later, a survey [9] lists nine BAN projects, five of which include ECG devices. Meanwhile, many research studies produce detailed designs of BANs [10; 11; 12] targeting local area networks, and therefore confined in a room or a building. The availability of cloud servers allows overcoming such limits. In 2013, [PERSON] et al. propose a cloud-based infrastructure [13]: the physician and the patient are clients of a Web server that processes the ECG, evaluates its quality, and provides parameter extraction and visualization. The server is in the AmazonWeb Services (AWS) cloud, while the client uses a personal device that interacts with the server using Secure Hypertext Transfer Protocol (HTTPS). The two edge units communicate in real time, so that doctor and patient may interact during the ECG. In this scenario, end-to-end encryption is a challenge since the server cannot analyze encrypted data. To mitigate the problem, [PERSON] et al. [14] propose the use of an encryption algorithm which allows homomorphic operations on encrypted data. The presence of a remote ECG service is fundamental for large scale screenings, like the REHEARSE-AF study referenced in the introduction [1]. The study involved 1001 patients divided into two arms to evaluate the improvement of early diagnosis of AF--which is often asymptomatic and implicated in ischemic strokes--using a remote ECG monitoring service named _iECG_. The trial consisted of taking an ECG two times a week, at home and without assistance, using a commercial ECG device attached to a tablet. Using the home Wireless Fidelity (WiFi) AP, the trace was uploaded to a server for automatic and human analysis targeting AF symptoms. The experiment successfully diagnosed 19 AFs, versus five in the control arm, at the cost of slightly more than 10,000$ for each AF diagnosis, and was supported by public and private funding. These results are encouraging, but the cost of such trials is a reason of concern [15]: to apply them on a large scale, we need to limit their financial impact by design and build an ecosystem of interoperable devices and services produced by competing enterprises which will encourage the diffusion of the service in a virtuous circle.