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Practical usage of IJS VisEcg framework for processing ECG data
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The precise heart rate variability is extracted from an ECG signal measured by a wearable sensor that constantly records the heart activity of an active subject for several days. Due to the limited resources of the wear-able ECG device the signal can only be sampled at relatively low, approximately 120 Hz, frequency. Besides low sampling rate the signal from a wearable sensor is also burdened with much more noise than the standard 12-channel ambulatory ECG, mostly due to the design of the device, i.e. the electrodes are positioned relatively close to each other, and the fact that the subject is active during the measurements. To extract heart rate variability with 1 ms precision, i.e. 10 times more accurate than the sample rate of the measured signal, a two-step algorithm is proposed. In first step an approximate global search is performed, roughly determining the point of interest, followed by a local search based on the Moving Least Squares approximation to refine the result. The methodology is evaluated in terms of accuracy, noise sensitivity , and computational complexity. All tests are performed on simulated as well as measured data. It is demonstrated that the proposed algorithm provides accurate results at a low computational cost and it is robust enough for practical application.
Integrating the numerous available ECG devices to the citizen's electronic health record is a major challenge for the users of ECG interoperability standards, since most ECG devices implement protocols and file formats in ways that hinder the open interchange of ECGs and hamper ECG analysis, processing, and serial comparison. The mission of the OpenECG portal is to foster the consistent implementation of interoperability standards in computerized electrocardiography. A help desk and a planned on-line validation and conformance testing service for the SCP-ECG standard assist manufacturers requesting feedback on their implementations. Additionally, tutorials, visualization tools, converters, and annotated ECG samples are expected to provide the framework for the systematic diffusion of standards in the everyday practice and pave the way towards interoperability in all ECG examinations.
This monograph presents a comprehensive overview of the electrocardiography from the aspect of wireless and mobile monitoring and its potential for personalized health management. The topical focus is on the implementation and efficient application of user friendly m-Health systems. The target audience comprises biomedical engineers, medical doctors, students, industrial experts and health managers developing m-Health solutions.
This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques.
Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.
The interoperability of the Electrocardiogram (ECG) between heterogeneous systems has been facilitated by not one, but a number of predefined open storage formats. To improve the techniques currently used, it is important to define the similarities and the differences between these ECG storage formats.
This paper presents a review of 9 formats used to store the ECG. Three of the predominant formats, namely, SCP-ECG, DICOM-ECG, and HL7 aECG are reviewed in detail along with the undertaking of a SWOT analysis. The remaining formats have been examined to a lesser extent as they are not as predominant in the literature.
This study suggests that a plethora of open ECG formats, all aiming to promote interoperability has the opposite effect of adding more complexity. This paper discusses whether a format supporting a variety of diagnostic modalities is more advantageous than a format that only supports the ECG. It is conclusive that a general purpose format such as DICOM solves more interoperability issues, however, no general purpose format currently exists that fulfils the requirements of all users. As a result, the healthcare industry has been bombarded with custom storage formats, i.e., a format for storing the resting ECG, a format for storing the ambulatory ECG, a format for storing the ECG in clinical trials, a format for storing ECG data on mobile devices etc. This study then examines which implementation method is more suited to encode ECG data, i.e. binary or XML. Binary encoding has been used in the past to store the ECG, however, unlike binary, XML files are human readable, searchable and provide a better form of semantics. Based on analysis within this work it is speculated that XML may overtake binary as the preferred implementation method for encoding ECG data since it has already made a huge impact in the healthcare industry.
It can be concluded that there is a wide range of vastly different techniques used to store the ECG. Although the specifications of these formats are openly available, neither has been internationally adopted to be used with all ECG machines. Therefore, there remains a lack of global interoperability of ECG information.
Neurological data measuring and analysis software based on object oriented design
- Roman Trobec
- Viktor Avbelj
- Marjan Šterk
- Bernard Meglič
- Viktor Švigelj