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The first attempts to modeling relationships between electrocardiographic leads, were based on measuring lead vectors by using models of human torso (deterministic approach), and by estimating liner regression models between leads of interest (statistical models). Among the most recent attempts, one of the most prominent is the state-space models approach, because of better noise immunity compared to mean squared error estimated statistical models. This study uses state-space models to synthesize precordial leads and Frank leads, from leads I, II, and V1. The synthesis was evaluated with the linear correlation coefficient (CC) on 200 measurements from the Physionet's PTB diagnostic ECG database. The results show better performance of regression models (mean CC between 0.88 and 0.96) than the state-space models (mean CC between 0.78-0.86). The leads were not pre-aligned for the R-peaks, which can be the main cause for the lower performances of state-space models, as a previous study has also shown. Residual baseline wander (after filtering) was the dominant reason for not obtaining better synthesis results with both methods.

Dysfunction of cardiac intrinsic autonomic nervous system could be one of possible triggers for atrial fibrillation. Different studies show that it is possible to modulate the cardiac intrinsic autonomic activity with electrical stimulation through the skin in the ear, innervated by auricular branch of the vagus nerve (tVNS). The aim of our study was to determine, weather tVNS reduces the burden of atrial arrhythmias in patients with paroxysmal atrial fibrillation. A randomised double-blind study, with one-hour daily subthreshold tVNS, over three-day blocks of sham or true stimulation, was performed. A continuous single-channel ambulatory ECG was recorded. Significant technical assistance to computer-based ECG interpretation was necessary for highest possible interpretation quality. The obtained results were compared between periods with true and sham stimulation to discover eventual differences. We have successfully validated the designed methodology. The subthreshold tVNS has a detectable impact on heart rate variability. However, there was no significant impact of tVNS on the burden of atrial arrhythmias. A 3-day tVNS is probably too short for such evaluation.

The recent trend in electrocardiogram (ECG) device development is towards wireless body sensors applied for patient monitoring. The ultimate goal is to develop a multi-functional body sensor that will provide synchronized vital bio-signs of the monitored user. In this paper, we present an ECG sensor for long-term monitoring, which measures the surface potential difference between proximal electrodes near the heart, called differential ECG lead or differential lead, in short. The sensor has been certified as a class IIa medical device and is available on the market under the trademark Savvy ECG. An improvement from the user’s perspective—immediate access to the measured data—is also implemented into the design. With appropriate placement of the device on the chest, a very clear distinction of all electrocardiographic waves can be achieved, allowing for ECG recording of high quality, sufficient for medical analysis. Experimental results that elucidate the measurements from a differential lead regarding sensors’ position, the impact of artifacts, and potential diagnostic value, are shown. We demonstrate the sensors’ potential by presenting results from its various areas of application: medicine, sports, veterinary, and some new fields of investigation, like hearth rate variability biofeedback assessment and biometric authentication., Export Date: 2 April 2020; Article; Correspondence Address: Rashkovska, A.; Department of Communication Systems, Jožef Stefan Institute, Jamova cesta 39, Slovenia; email: aleksandra.rashkovska@ijs.si

The atrial irregular rhythm, often reflected in atrial fibrillation, undulation or flutter, is recognized as one of the major causes of brain stroke and entails an increased risk of thromboembolic events because it increases the likelihood of blood clots formation. Its early detection is becoming an increasingly important preventive measure. The paper presents a simple methodology for the detection of atrial irregular rhythm by ECG body gadget that can perform long-term measurements, e.g. several weeks or more. Multichannel ECG, on the body surface, gives a more detailed insight into the atrial activity in comparison to standard 12-lead ECG. The information from MECG is compared with single-channel patch ECG. The obtained results suggest that the proposed methodology could be useful in treatments of atrial irregular rhythm. One can obtain a reliable information about the time and duration of fibrillation events, or determine arrhythmic focuses and conductive pathways in heart atria, or study the effects of antiarrhythmic drugs on existing arrhythmias and on an eventual development of new types of arrhythmias.

Currently we are witnessing fast development of patch ECG devices, some of which have already been extensively evaluated and shown to be useful for detecting arrhythmias. The research about using the patch ECG devices for purposes other than arrhythmia detection has been scarce. The efficiency of patch electrocardiography for a specific purpose can depend on the devices location on the body surface. It is still an open question where to position the ECG patch devices, and should the position depend on the specific purpose and perhaps even be personalized. We present the lead theory of differential leads (ECG leads obtained by patch ECG devices) and discuss its implications on the patch ECG devices positioning on the body surface.

The motivation and goals for the development of mobile health solutions are presented. Short history and background of the electrocardiography provide basic principles and facts related to the heart activity and elucidate the path from the measurement of conventional electrocardiogram to the monitoring of the heart by wireless body sensors. A bipolar differential lead is introduced, which has enabled the implementation of a small body sensor for capturing electric potential differences on the skin. The chapter concludes with guidelines on how to read this book and with a short overview of all book chapters.

The content of our book, devoted to body sensors and their implications to electrocardiography, is recapitulated with this chapter. The identified challenges in long-term ECG data analytics are discussed. Based on the presented material, the near future of mHealth perspectives is foreseen regarding the technology, the usability, and the potential of increased users’ awareness for their own health.

A more detailed description of multichannel electrocardiography and the differential lead aims to clarify why the multichannel ECG opens a path towards implementation of wireless wearable sensors. Several ways of how the differential lead could be used for heart rhythm monitoring are shown with options for analysis and interpretation of sensor ECG measurements. Finally, the most important vital signs that could be provided by a multifunctional body sensor are presented.

A description of software requirements for an mHealth system is provided. Several layers of software are required for proper system functioning: ECG body sensor firmware, applications on smartphones, Cloud applications, and stand-alone applications for personal computers. The main functionality requirements of the mHealth software are described. Additionally, approaches for fulfilling those requirements are proposed.

Besides the standard 12-lead ECG and the Holter monitor, today the market offers a wide range of modern ECG devices and services supported by the latest developments in ICT. This chapter is devoted to the current state-of-the-art from the area of ECG with a reduced number of leads. We focus on ECG wireless body sensors, differentiating between those that measure only heart rate and are used just for entertainment or during sport activities, and those that actually measure and analyze the ECG signal, with all its waveforms. The latter are elaborated in more detail, particularly our differential ECG sensor and its commercial version Savvy, for which we provide also a comprehensive comparison to other state-of-the-art sensors in that field. It is, however, inevitable that the state-of-the art will change in the future. The constant progress in ICT will always drive the development of new and improved ECG devices.

The use of wireless ECG body sensors in two pilot studies is presented. The first study, running at the Department of Cardiovascular Surgery of the University Medical Centre Ljubljana, is focused on the investigation of postoperative atrial fibrillation. The patients are monitored with wireless ECG body sensors one day before and five days after the surgery. The second study has been established at the primary care level in the Community Health Centre Ljubljana, with the intention to establish heart rhythm screening. As both studies are still in progress, we present just their setup and some interesting findings that emerged in their starting phase. Based on evidences from long-term ECG measurements, we identify several still open ECG research questions that could utilize the vast amount of long ECG recordings obtained from the pilot studies.

In this chapter, the lead theory of differential leads is presented. A differential lead is an ECG lead obtained from two closely positioned electrodes on the body surface. It can be measured with an ECG body sensor. The theoretical background is needed to gain a formal and intuitive understanding of what is measured with differential leads, as well as to elaborate how the standard 12-lead ECG can be synthesized from three differential leads. The 12-lead ECG synthesis is based on the dipole volume source model. After introducing the dipole model, the Burger’s equation is derived and the concept of lead vector defined. We describe how to derive lead vectors from known heart vector and, vice versa, how to obtain the heart vector from known lead vectors. Then, the concepts of image surface and lead field are introduced, followed with a description of the lead field of a differential lead. Next, the theory and methods for ECG leads synthesis from differential leads is presented. The chapter concludes with a discussion on the evaluation and personalization of the synthesis.

Presented is a preliminary study that investigates regression trees application for the purpose of mapping relationship between three differential ECG leads and leads of the 12-lead ECG. The approach was evaluated on a single ECG measurement on which it was superior to two syntheses performed by universal and personalized linear transformations, in terms of correlation coefficients between the synthesized and measured leads. A prominent imperfection however is that the regression trees can output only a limited number of values equal to the number of leaf nodes. The paper indicates some ideas on how to overcome this deficiency.

Presented is a wireless body sensor capable of measuring local potential differences on a body surface. By using on-sensor signal processing capabilities, and developed algorithms for off-line signal processing on a personal computing device, it is possible to record single channel ECG, heart rate, breathing rate, EMG, and when three sensors are applied, even the 12-lead ECG. The sensor is portable, unobtrusive, and suitable for both inpatient and outpatient monitoring. The paper presents the sensor's hardware and results of power consumption analysis. The sensor's capabilities of recording various physiological parameters are also presented and illustrated. The paper concludes with envisioned sensor's future developments and prospects.