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Introduction: The transtelephonic electrocardiogram has been shown to have a great value in the management of out-of-hospital chest pain emergencies. In our previous study it not only improved the pre-hospital medical therapy and time to intervention, but also the in-hospital mortality in ST-segment elevation myocardial infarction. It was hypothesised that the higher in-hospital survival rate could be due to improved transtelephonic electrocardiogram-based pre-hospital management (electrocardiogram interpretation and teleconsultation) and consequently, better coronary perfusion of patients at the time of hospital admission. To test this hypothesis, our database of ST-segment elevation myocardial infarction patients was evaluated retrospectively for predictors (including transtelephonic electrocardiogram) that may influence in-hospital survival., Methods and Results: The ST-segment elevation myocardial infarction patients were divided into two groups, namely (a) hospital death patients ( n  = 49) and (b) hospital survivors (control, n  = 726). Regarding pre-hospital medical management, the transtelephonic electrocardiogram-based triage (odds ratio 0.48, confidence interval 0.25-0.92, p  = 0.0261) and the administration of optimal pre-hospital medical therapy (acetylsalicylic acid and/or clopidogrel and glycoprotein IIb/IIIa inhibitor) were the most important independent predictors for a decreased risk in our model. At the same time, age, acute heart failure (Killip class >2), successful pre-hospital resuscitation and total occlusion of the infarct-related coronary artery before percutaneous coronary intervention were the most important independent predictors for an increased risk of in-hospital mortality., Discussion: In ST-segment elevation myocardial infarction patients, (a) an early transtelephonic electrocardiogram-based teleconsultation and triage, (b) optimal pre-hospital antithrombotic medical therapy and (c) the patency and better perfusion of the infarct-related coronary artery on hospital admission are important predictors of a lower in-hospital mortality rate.

A non-uniform distribution of diagnostic information in the electrocardiogram (ECG) has been commonly accepted and is the background to several compression, denoising and watermarking methods. Gaze tracking is a widely recognized method for identification of an observer's preferences and interest areas. The statistics of experts' scanpaths were found to be a convenient quantitative estimate of medical information density for each particular component (i.e., wave) of the ECG record. In this paper we propose the application of generalized perceptual features to control the adaptive sampling of a digital ECG. Firstly, based on temporal distribution of the information density, local ECG bandwidth is estimated and projected to the actual positions of components in heartbeat representation. Next, the local sampling frequency is calculated pointwise and the ECG is adaptively low-pass filtered in all simultaneous channels. Finally, sample values are interpolated at new time positions forming a non-uniform time series. In evaluation of perceptual sampling, an inverse transform was used for the reconstruction of regularly sampled ECG with a percent root-mean-square difference (PRD) error of 3-5% (for compression ratios 3.0-4.7, respectively). Nevertheless, tests performed with the use of the CSE Database show good reproducibility of ECG diagnostic features, within the IEC 60601-2-25:2015 requirements, thanks to the occurrence of distortions in less relevant parts of the cardiac cycle.

Background: In 2010, an Italian project was launched aimed at using a telecardiology device in order to perform early diagnosis of young students at risk of sudden cardiac death., Methods: Our retrospective observational study was conducted on a population of 13,016 students, aged between 16 and 19 years, in different Italian regions. It consisted of analysis of data recorded during a telecardiology pilot study. The recorded data were electrocardiograms and data concerning lifestyle habits and family history of cardiovascular diseases. In total, 14 alterations in the electrocardiogram signal have been considered in this study. Some of these alterations are as follows: ventricular ectopic beats, atrioventricular block, Brugada-like electrocardiogram pattern, left anterior/posterior fascicular block, left/right ventricular hypertrophy, long/short QT interval, left atrial enlargement, right atrial enlargement, short PQ interval, and ventricular pre-excitation Wolff-Parkinson-White syndrome. On the basis of the collected data, we implemented this retrospective observational study., Results: The analysed data showed that 13.60% of students had a family history for cardiovascular diseases, 22.43% reported smoking habits, 26.23% reported alcohol consumption, and 7.24% reported abuse of drugs. A total of 24% of students had at least one of the 14 electrocardiogram pathological alterations considered in our study and 32% had electrocardiogram values within the normal range., Conclusions: This retrospective observational study analysed data registered during our telecardiology activity. This activity permitted to maximise data collection and minimise the costs for collecting such data. This activity of screening is being continued and in the next few years it will allow us to have a greater mass of data.

Background: Currently, transmission of electrocardiograms (EKGs) from a small emergency department (ED) to specialists at referral hospitals can be a time-consuming and laborious process. We investigate whether text messaging by use of short message service (SMS) of EKGs from a small hospital to consultants at a large hospital is rapid and accurate., Methods: This study involved a one-month prospective evaluation of consecutive EKGs recorded in a small community ED. Investigators obtained de-identified photographs of each EKG via a mobile phone camera. Each EKG picture, along with a brief patient clinical history, was sent via SMS to on-call emergency physicians located at a large referral care site. All images were evaluated solely on a mobile phone. The primary outcome was the proportion of SMS that were received within two minutes of being sent. As a secondary outcome, the intra-rater evaluation of the initial EKG and the SMS EKG image were compared on 13 standardized features. The tertiary outcome was cost of text messaging., Results: A total of 298 patients (14.6%) had 409 EKGs performed and a total of 926 SMS were sent. 921 SMS (99.5%, 95% confidence interval (CI) 98.7-99.8%) arrived within two minutes with a median transmission time of nine seconds (interquartile range (IQR) 3-32 s). Between the gold standard original EKG, and the interpretation of the texted image, six out of 409 (1.5%, 95% CI 0.6-3.3%) had any differences recorded, across all 13 categories. Overall, the study cost 4.1 cents per texted image., Conclusions: Systematic text messaging of ED EKGs from a small community hospital to a referral center is a rapid, accurate, portable, and inexpensive method of data transfer. This may be a safe and effective strategy to communicate vital patient information., (© The Author(s) 2015.)

Telecardiology is envisaged as a supplement to inadequate local cardiac care, especially, in infrastructure deficient communities. Yet the associated infrastructure constraints are often ignored while designing a traditional telecardiology system that simply records and transmits user electrocardiogram (ECG) signals to a professional diagnostic facility. Against this backdrop, we propose a two-tier telecardiology framework, where constraints on resources, such as power and bandwidth, are met by compressively sampling ECG signals, identifying anomalous signals, and transmitting only the anomalous signals. Specifically, we design practical compressive classifiers based on inherent properties of ECG signals, such as self-similarity and periodicity, and illustrate their efficacy by plotting receiver operating characteristics (ROC). Using such classifiers, we realize a resource-constrained telecardiology system, which, for the PhysioNet databases, allows no more than 0.5% undetected patients even at an average downsampling factor of five, reducing the power requirement by 80% and bandwidth requirement by 83.4% compared to traditional telecardiology., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Acute coronary syndrome (ACS) patients residing in rural areas are predisposed to higher risk of poor outcomes due to substantial delays in disease management, emphasising the importance of emerging telecardiology technologies in delivering emergency services in such settings. This meta-analysis aimed to investigate the impacts of prehospital telecardiology strategies on the clinical outcomes of rural ACS patients.Methods: A literature search was performed of articles published up to April 2020 through six databases. Included studies were assessed for bias risk using the ROBINS-I tool, and a random-effects model was utilised to estimate effect sizes. Certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE).Results: Twelve studies with a total of 3989 patients were included in this review. Prehospital telecardiology in the form of tele-electrocardiography (tele-ECG) enabled prompt diagnosis and triage, resulting in a decreased door-to-balloon (DTB) time (mean difference = -25.53 minutes, 95% confidence interval (CI) -36.08 to -14.97 minutes; I2 = 98%), as well as lower in-hospital mortality (odds ratio (OR) = 0.57, 95% CI 0.36-0.92) and long-term mortality (OR = 0.52, 95% CI 0.39-0.69) rates, both with negligible heterogeneity (I2 = 0%). GRADE assessment yielded very low to moderate certainty of evidence.Conclusion Prehospital tele-ECG appeared to be an effective and worthwhile approach in the management of rural ACS patients, as shown by moderate quality evidence on lower long-term mortality. Given the uncertainties of the evidence quality on DTB time and in-hospital mortality, future studies with a higher quality of evidence are required to confirm our findings. [ABSTRACT FROM AUTHOR]

Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of heart patients arduous. Patients who need regular heart monitoring were affected the most. Telecardiology is used for regular remote heart monitoring of such patients. However, the resultant huge electrocardiogram (ECG) data obtained through regular monitoring affects available storage space and transmission bandwidth. These signals can take less space if stored or sent in a compressed form. To recover them at the receiver end, they are decompressed. We have combined telecardiology with automatic ECG arrhythmia classification using CNN and proposed an algorithm named TELecardiology using a Deep Convolution Neural Network (TELDCNN). Discrete cosine transform (DCT), 16-bit quantization, and run length encoding (RLE) were used for compression, and a convolution neural network (CNN) was applied for classification. The database was formed by combining real-time signals (taken from a designed ECG device) with an online database from Physionet. Four kinds of databases were considered and classified. The attained compression ratio was 2.56, and the classification accuracies for compressed and decompressed databases were 0.966 and 0.990, respectively. Comparing the classification performance of compressed and decompressed databases shows that the decompressed signals can classify the arrhythmias more appropriately than their compressed-only form, although at the cost of increased computational time. [ABSTRACT FROM AUTHOR]

Pre-partecipation ECG screening of large populations has a significant socioeconomic impact. Technological progress now allows for high-tech-low-cost ECG screening using validated smartphone-based devices capable of guiding to the correct performance of a 12‑lead ECG by layman with no medical background. We enrolled 728 (364, 52% males) individuals, aged 12–13 years who underwent ECG screening with a smartphone 12‑lead ECG during school hours by layman volunteers. Correct electrodes placement was provided by a validated image-processing algorithm by the smartphone camera in the App. ECG interpretation was via a telecardiology platform and alterations classified following current standards. A total of 741 ECGs were recorded, of which 13(2%) were technically not interpretable. Mean PR, QRS and QTc were: 145 ± 22, 85 ± 19 and 387 ± 57 msec. No QTc prolongation was observed. Mean QRS axis was 15°; 26 (4%) patients presented an iRBB. T-wave inversion from V1-V3 was present in 145 (21%) subjects. Twenty-one(3%) patients were referred to second level examination: deep Q-waves in inferior leads in 12(1.6%), ventricular ectopics in 5(0.7%), anterior T-waves inversions V1-V4 in 3(0.4%); extreme right axis deviation in 1(0.3%). Second line investigations did not provide any definitive diagnosis. Total project costs (material equipment and human cost) was 14.460€, 19.51€ per individual. The potential net saving with respect to current pre-participation screening cost was 19%. Layman 12‑lead Smartphone-ECG population screening proved feasible and effective, with a rate of non-interpretable ECG of <5%. Potential cost-saving in ECG screening and recording was 19%, providing an appealing opportunity when large campaigns should be addressed also in developing countries. • Pre-partecipation ECG screening of large populations has significant socioeconomic impact. Technological progress allows for high-tech-low-cost ECG screening using smartphone-based devices capable of guiding a user with no medical background to perform a12-lead ECG. • We enrolled 728 (364, 52% males) individuals, aged 12–13 years who underwent ECG screening with a smartphone 12-lead ECG during school hours by layman volunteers. • Twenty-one(3%) patients were referred to second level examination, reasons were: deep Q-waves in inferior leads in 12(1.6%), ventricular ectopics in 5(0.7%), anterior T-waves inversions V1-V4 in 3(0.4%); extreme right axis deviation in 1(0.3%). • Total project costs was 14.460€, 19.51€ per individual. The potential net saving with respect to current pre-participation screening cost in ECG recording and interpretation was 19%. [ABSTRACT FROM AUTHOR]

The monitoring of electrocardiography (ECG) in ambulatory conditions is an important task for achieving success in remote healthcare monitoring. In this paper, Kalman-based adaptive artifact cancellation structures, which are the hybrid versions of least-mean-square (LMS) algorithm variants, are proposed for the high-resolution enhancement of an ECG signal. The main advantage of the Kalman-based adaptive filter structure lies in the extraction of the ECG signal at a low signal-to-noise ratio (SNR). This property helps the Kalman noise canceller (KNC) to achieve greater monitoring accuracy. The hybrid version of this Kalman algorithm makes the noise canceller independent of the step-size parameter, whereas the performance of conventional adaptive filters depends on the step-size parameter. In the proposed KNCs, we use discrete wavelet transform to generate a reference component from the contaminated ECG signal itself. In addition to these constraints, in remote health care monitoring, it is necessary to lower the computational burden and increase the convergence rate of the noise canceller. In a practical remote health care monitoring system if the computational burden of the signal conditioning unit is more, then it takes a much greater amount of time to process samples in the filter. This leads to waiting of incoming samples at the input port of the filter. This causes overlapping of samples at the input port and causes ambiguity in the diagnosis process. To achieve the feature of low computational complexity, we combine Kalman-based LMS (KLMS) with sign algorithms. In addition, data normalization is introduced to improve convergence characteristics. Finally, to test the performance of the proposed implementations, real ECG signals from the MIT-BIH database is used. The measured parameters, namely, SNR, excess mean square error, and mis-adjustment are calculated in the enhancement process to judge the ability of various algorithms. Experimental results confirm that the proposed Kalman-based adaptive algorithms are better than the LMS-based algorithms. Among the implemented techniques sign regressor-based KNC performs better in terms of various considered measures.

Among the wide range of medical specialties in which telemedicine has been successfully applied, cardiology can be considered as one of the most important fields of application. Through the transmission of clinical data and the electrocardiogram, telecardiology allows access to a real-time assessment (teleconsultation) without any need to travel for both patient and cardiologist. This review discusses the impact of telecardiology in different clinical settings of application. Pre-hospital telecardiology has proved to be useful either in the clinical management of remote patients with acute coronary syndrome or in supporting the decision-making process of general practitioners. In the setting of in-hospital telecardiology, most of the applications refer to real-time echocardiography transmissions between rural small hospitals and tertiary care centres, particularly for the diagnosis or exclusion of congenital heart disease in newborns. Finally, many trials show that post-hospital telecardiology improves outcomes and reduces re-admissions or outpatient contacts in patients with heart failure, arrhythmias or implantable devices. [ABSTRACT FROM AUTHOR]

Telemedicine uses telecommunication and information technologies and provides clinical health care for people who are at a distance. Telecardiology is a type of telemedicine that can send electrocardiogram (ECG) signals over a wireless network to remote healthcare professionals. The aim of this paper is to simulate the transmission of ECG signals over a communication system that uses digital video broadcasting –terrestrial (DVB-T) or digital video broadcasting –satellite version 2 (DVB-S2) technologies. Bit error rate (BER) performance of this system is analyzed over an additive Gaussian white noise (AWGN) channel and compared to theoretical results. Keeping in mind that wireless channel suffers from multipath propagation, multiple-input multiple-output (MIMO) antenna technology is additionally used along with DVB-T in a fading environment. It is shown that DVB-S2 technology offers performance improvements of up to 18 dB over DVB-T in an AWGN channel. It is also shown that using MIMO along with DVB-T mitigates the effects of multipath and improves the performance. This improvement is around 5 dB. Being a superior technology, however, does not necessarily mean DVB-S2 should be chosen over DVB-T in every circumstance. For example, in the case where less delay is important (i.e. in real-time transmission) DVB-T might still be the choice of transmission of ECG signals if performance degradation can be tolerated. [ABSTRACT FROM AUTHOR]

This study presents an improved technique for compression of electrocardiogram (ECG) signals, based on beat correlation of signal and principle component (PC) analysis, for ECG signal. For this purpose, two‐dimensional matrix of ECG signal based on temporal inter‐and intra‐beat correlation is constructed, and further compression is achieved using PC extraction. Beat correlation helps to generate very few PCs that increase the compression efficiency. A detailed analysis has been presented for ten signals having different rhythms, wave morphologies and abnormalities of Massachusetts Institute of Technology ‐ Beth Israel Hospital (MIT‐BIH) arrhythmia database. The effectiveness of the proposed method is examined with several attributes such as percentage root‐mean‐square difference, compression ratio, signal‐to‐noise ratio and correlation. Experimental results have shown that this method is very efficient for compression and suitable for different applications of telecardiology. [ABSTRACT FROM AUTHOR]

Nowadays telecardiology is widely popular due to the fact that an increasing number of people are suffering from cardiac disease in the world. Therefore huge amount of ECG signal as well as patient confidential information will be transmitted via the Internet. Ibaida's wavelet-based data hiding technique aims to protect patient confidential data utilizing ECG signal as a host media. But it cannot completely reconstruct the original ECG signal. Any alteration of the ECG may lead to an inaccurate diagnosis conclusion drawn by the doctor, which cannot be accepted by patients. In this paper, our elemental standpoint requires that both patient information and ECG signal must be perfectly restored at the extraction side. Firstly a method is proposed to embed patient confidential data into ECG signal, while keeping its high visual quality. Then we use a unified embedding-scrambling method to guarantee the security of patient privacy as well as the ECG signal itself. The structure of watermarked ECG signal is severely deconstructed. Both of the experimental results demonstrate that our proposed methods are reversible. Moreover the latter scheme can achieve high information payload. [ABSTRACT FROM AUTHOR]

Aims: Although an increasing prevalence of atrial fibrillation (AF) has been reported worldwide, there are few studies from low- and middle-income countries. Our objective is to assess the prevalence of AF and the associated medical conditions in Brazilian primary care patients.Methods and Results: This is an observational retrospective study. Patients ≥5 years of age from primary care centres of 658 municipalities in Minas Gerais, Brazil, who performed digital electrocardiograms (ECGs) by a public telehealth service in 2011 were assessed. Clinical data were self-reported, and ECGs were interpreted by a team of trained cardiologists using standardized criteria. To assess the relation between clinical characteristics and AF, odds ratios were estimated by logistic regression. A total of 262 685 primary care patients were included, mean (SD) age of 50.3 (19.3) years, 59.6% female. Hypertension was reported in 32.0%, family history of coronary heart disease in 15.0%, diabetes in 5.4%, hyperlipidaemia in 2.8%, Chagas disease in 2.9%, and 7.1% reported current smoking. The prevalence of AF was 1.8% overall: 2.4% in men (ranging from 0.001% from 5-19 years old to 14.6% in nonagenarians) and 1.3% in women (ranging from 0.001% from 5-19 years old to 8.7% in nonagenarians) (P < 0.001). The prevalence of AF increased with advancing age. The comorbidities associated with AF were Chagas disease, previous myocardial infarction, hypertension, and chronic obstructive pulmonary disease. Vitamin K antagonist use was reported by 1.5% of patients.Conclusion: The prevalence and age distribution of AF were similar to studies in high-income countries. The proportion of patients who reported the use of anticoagulants was alarmingly low. Our findings point out the necessity to formulate effective treatment strategies for AF in Brazilian primary care settings. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of a system for digital telecardiology on mobile devices called Remote Cardio Consultation (RCC). Using RCC may improve first intervention procedures in case of heart attack. In fact, it allows physicians to remotely consult ECG signals from a mobile device or smartphone by using a so-called app. The remote consultation is implemented by a server application collecting physician availability to answer upon client support requests. The app can be used by first intervention clinicians and allows reducing delays and decision errors in emergency interventions. Thus, best decision, certified and supported by cardiologists, can be obtained in case of heart attacks and first interventions even by base medical doctors able to produce and send an ECG. RCC tests have been performed, and the prototype is freely available as a service for testing. [ABSTRACT FROM AUTHOR]

Remote cardiovascular disease (CVD) diagnosis from ECG plays an important role in health care domain. Data mining, the major step in the process of the extraction of knowledge using descriptive and predictive algorithms that aid in making proactive decisions, has also been used for CVD diagnosis. Recently, diverse techniques have been developed for analyzing the ECG signals. However, due to the diversity of techniques used, terminologies, performance measures used in different techniques makes analysis and comparing of results thwarting. The aim of this work is to essentially explore and present the analysis of different data mining algorithms proposed earlier in literature for CVD diagnosis, their advantages and limitations. This paper presents various techniques for CVD diagnosis using data mining from an ECG signal under four major phases - ECG Acquisition, ECG Compression, ECG Feature Extraction and ECG diagnosis. The primary aim of this paper is to categorize the various researches done in this regard to provide a glossary for interested researchers and to aid in identifying their potential research direction. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is one of the most widespread health problems with unpredictable and life-threatening consequences. The electrocardiogram (ECG) is commonly recorded for computer-aided CVD diagnosis, human emotion recognition and person authentication systems. For effective detection and diagnosis of cardiac diseases, the ECG signals are continuously recorded, processed, stored, and transmitted via wire/wireless communication networks. But long-term continuous cardiac monitoring system generates huge volume of ECG data daily. Therefore, a reliable and efficient ECG signal compression method is highly demanded to meet the real-time constraints including limited channel capacity, memory and battery-power of remote cardiac monitoring, ECG record management and telecardiology systems. In such scenarios, the main objective of the ECG signal compression is to reduce the data rate for effective transmission and/or storage purposes without significantly distorting the clinical features of different kinds of PQRST morphologies contained in the recorded ECG signal. Numerous ECG compression methods have been proposed by exploiting the intra-beat correlation, inter-beat correlation and intra-channel correlation of the ECG signals. This paper presents a prospective review of wavelet-based ECG compression methods and their performances based upon findings obtained from various experiments conducted using both clean and noisy ECG signals. This paper briefly describes different kinds of compression techniques used in the one-dimensional wavelet-based ECG compression methods. Then, the performance of each of the wavelet-based compression methods is tested and validated using the standard MIT-BIH arrhythmia databases and performance metrics. The pros and cons of different wavelet-based compression methods are demonstrated based upon the experimental results. Finally, various practical issues involved in the validation procedures, reconstructed signal quality assessment, and performance comparisons are highlighted by considering the future research studies based on the recent powerful digital signal processing techniques and computing platform. [ABSTRACT FROM AUTHOR]

The article describes a short range wireless telecardiology system with the objective of transmitting electrocardiogram (ECG) signal for remote end acquisition. Topics discussed include the acquired signal being compressed using a combination of modified delta encoding and run length encoding technique using a wireless transceiver operating in 2.4 GigaHertz (GHz) industrial, scientific and medical (ISM) band. Also mentioned is computational simplicity allowing the use of low-end microprocessor.

Abstract: Purpose: Implementation of telemedicine in many clinical scenarios improves the quality of care and patient safety. However, its use is hindered by operational, infrastructural and financial limitations. This paper describes the design and deployment of a plug-and-play telemedicine platform for cardiologic applications. Methods: The novelty of this work is that, instead of complex middleware, it uses a common electronic mailbox and its protocols to support the core of the telemedicine information system and associated data (ECG and medical images). A security model was also developed to ensure data privacy and confidentiality. Results: The solution was validated in several real environments, in terms of performance, robustness, scalability and work efficiency. During the past three years it has been used on a daily basis by several small and medium-sized laboratories. Conclusions: The advantage of using an Internet service in opposition to a server-based infrastructure is that it does not require IT resources to set up the telemedicine centre. A doctor can configure and operate the centre with the same simplicity as any other Internet browser application. The solution is currently in use to support remote diagnosis and reports of ECG and Echocardiography in Portugal and Angola. [Copyright &y& Elsevier]

Objective: In this study, the diagnostic accuracy of interpretations of electrocardiogram (ECG) images taken by a mobile phone and sent as multimedia message was investigated. Materials and Methods: The ECGs of 305 patients who were admitted to the emergency department with cardiac complaints were photographed with the camera of a Nokia (Espoo, Finland) N93 mobile phone. The images were sent via a multimedia messaging system to an identical mobile phone carried by a cardiologist and were interpreted on the screen of that mobile phone. Another cardiologist and an emergency physician interpreted ECG paper printouts separately. The findings of the core laboratory were used as the gold standard. The interpretation errors were scaled from 1 to 4 with respect to the significance of findings. Results: The total ratio of Grade 4 errors, which consisted of significant errors, did not show any significant difference (p =0.76) between the interpretations by the emergency medicine specialist and the cardiologist who interpreted the ECGs on the mobile phone; the cardiologist who interpreted the ECG paper printouts made significantly fewer mistakes than the other two specialists (p =0.025 and p =0.023, respectively). The separate assessment of the findings showed that in the diagnostic process of ST-segment elevation, depression, and supraventricular tachycardia, the consistency of the interpretations (κ=0.81, κ=0.81, and κ=1.0, respectively) made on the mobile phone screen was slightly better than that of the emergency medicine specialist (κ=0.73, κ=0.77, and κ=0.80, respectively) and was similar to that of the cardiologist (κ=0.91, κ=0.91, and κ=1.0, respectively) who interpreted ECG paper printouts. Conclusions: Our findings suggest that sending the ECG images via a multimedia message service may be a practical and inexpensive telecardiology procedure. [ABSTRACT FROM AUTHOR]

In this paper, several simple and efficient sign and error nonlinearity-based adaptive filters, which are computationally superior having multiplier free weight update loops are used for cancellation of noise in electrocardiographic (ECG) signals. The proposed implementation is suitable for applications such as biotelemetry, where large signal to noise ratios with less computational complexity are required. These schemes mostly employ simple addition, shift operations and achieve considerable speed up over the other least mean square (LMS)-based realizations. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal-to-noise ratio and computational complexity. [ABSTRACT FROM PUBLISHER]

Background: Due to the great variability of 12-lead ECG instruments and medical specialists' interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists' decision making support in emergency telecardiology. Methods: We create a new cloud and pervasive computing based 12-lead Electrocardiography (ECG) service to realize ubiquitous 12-lead ECG tele-diagnosis. Results: This developed service enables ECG to be transmitted and interpreted via mobile phones. That is, tele-consultation can take place while the patient is on the ambulance, between the onsite clinicians and the off-site senior cardiologists, or among hospitals. Most importantly, this developed service is convenient, efficient, and inexpensive. Conclusions: This cloud computing based ECG tele-consultation service expands the traditional 12-lead ECG applications onto the collaboration of clinicians at different locations or among hospitals. In short, this service can greatly improve medical service quality and efficiency, especially for patients in rural areas. This service has been evaluated and proved to be useful by cardiologists in Taiwan. [ABSTRACT FROM AUTHOR]

In telecardiology, electrocardiogram (ECG) signals from a patient are acquired by sensors and transmitted in real time to medical personnel across a wireless network. The use of IEEE 802.11 wireless LANs (WLANs), which are already deployed in many hospitals, can provide ubiquitous connectivity and thus allow cardiology patients greater mobility. However, engineering issues, including the error-prone nature of wireless channels and the unpredictable delay and jitter due to the nondeterministic nature of access to the wireless medium, need to be addressed before telecardiology can be safely realized. We propose a medical-grade WLAN architecture for remote ECG monitoring, which employs the point-coordination function (PCF) for medium access control and Reed–Solomon coding for error control. Realistic simulations with uncompressed two-lead ECG data from the MIT–BIH arrhythmia database demonstrate reliable wireless ECG monitoring; the reliability of ECG transmission exceeds 99.99% with the initial buffering delay of only 2.4 s. [ABSTRACT FROM AUTHOR]

This paper presents a complete study of wide-area wireless ECG transmission for real-time cardiac tele-monitoring taking into account both technical and clinical aspects, in order to provide recommendations for real-time monitoring considering both channel parameters and the tolerance of cardiologists to the effects of interruptions introduced during transmission. By using extensive wireless simulated scenarios, the compressed ECG signal is monitored on reception. A new protocol [real-time ECG transmission protocol, reliable ECG transmission protocol (RETP)] is used to perform the retransmissions of erroneous packets, introducing a monitoring buffer that mitigates possible negative effects. Assessments by cardiologists have shown that the maximum percentage of time for which the monitoring process could be stopped without their feeling uncomfortable is around 15% with a maximum monitoring delay of 3 or 4 s, depending on the scenario in question. Taking into account these values and the results obtained in the simulations, it is a straightforward step to obtain working areas for the wireless channel parameters where transmission is not recommended from a clinical point of view. [ABSTRACT FROM PUBLISHER]

A new real-time compression method for electrocardiogram (ECG) signals has been developed based on the wavelet transform approach. The method is specifically adaptable for packetized telecardiology applications. The signal is segmented into beats and a beat template is subtracted from them, producing a residual signal. Beat templates and residual signals are coded with a wavelet expansion. Compression is achieved by selecting a subset of wavelet coefficients. The number of selected coefficients depends on a threshold which has different definitions depending on the operational mode of the coder. Compression performance has been tested using a subset of ECG records from MIT-BIH Arrhythmia database. This method has been designed for real-time packetized telecardiology scenarios both in wired and wireless environments. [ABSTRACT FROM AUTHOR]

Background: General practitioners working in remote and rural areas sometimes need consultation with cardiologists. One practical and cost-effective way is transmission of patients' electrocardiographic images via ordinary fax machine to the cardiologists, but there is an important question that how much agreement exists between the diagnoses made by reading an original electrocardiogram and its copy transmitted via fax. Materials and Methods: In this cross-sectional study, 60 original electrocardiographic images were given to cardiologists for diagnosis. In the next step those electrocardiographic images were faxed to the hospital through a simple cheap fax machine, one month later the same cardiologist was asked to put his diagnosis on the copied versions of electrocardiographs, and the results were compared. Results: In 59 studied cases, the two method of diagnoses were exactly the same and only in one case the diagnoses were different. Therefore, Kappa agreement coefficient was calculated as 96%. Conclusion: According to the results of this study, general practitioners working in deprived areas can be certainly recommended to send patients' electrocardiographic images to the cardiologists via fax in the case of needing consultation [ABSTRACT FROM AUTHOR]