42 research outputs found

    Assessment of the Performance of the Adaptive Thresholding Algorithm for QRS Detection with the Use of AHA Database

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    Two modifications of an adaptive thresholding algorithm for heart beat detection have already been developed. The threshold combines three parameters: an adaptive slewrate value, a second value which rises when high-frequency noise occurs, and a third one intended to avoid missing of low amplitude beats. The current study assesses the performance of a new modification of the combined adaptive thresholding method for heart beat detection with the use of AHA database. The results are: Mod. 1 Se=99.58%, Sp=99.83 %; Mod. 2 Se=99.73%, Sp=99.83%; Mod. 3 Se=99.78%, Sp=99.85%. The statistical indices are higher than, or comparable to those, cited in the scientific literature

    Real time electrocardiogram QRS detection using combined adaptive threshold

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    BACKGROUND: QRS and ventricular beat detection is a basic procedure for electrocardiogram (ECG) processing and analysis. Large variety of methods have been proposed and used, featuring high percentages of correct detection. Nevertheless, the problem remains open especially with respect to higher detection accuracy in noisy ECGs METHODS: A real-time detection method is proposed, based on comparison between absolute values of summed differentiated electrocardiograms of one of more ECG leads and adaptive threshold. The threshold combines three parameters: an adaptive slew-rate value, a second value which rises when high-frequency noise occurs, and a third one intended to avoid missing of low amplitude beats. Two algorithms were developed: Algorithm 1 detects at the current beat and Algorithm 2 has an RR interval analysis component in addition. The algorithms are self-adjusting to the thresholds and weighting constants, regardless of resolution and sampling frequency used. They operate with any number L of ECG leads, self-synchronize to QRS or beat slopes and adapt to beat-to-beat intervals. RESULTS: The algorithms were tested by an independent expert, thus excluding possible author's influence, using all 48 full-length ECG records of the MIT-BIH arrhythmia database. The results were: sensitivity Se = 99.69 % and specificity Sp = 99.65 % for Algorithm 1 and Se = 99.74 % and Sp = 99.65 % for Algorithm 2. CONCLUSION: The statistical indices are higher than, or comparable to those, cited in the scientific literature

    Public access defibrillation: Suppression of 16.7 Hz interference generated by the power supply of the railway systems

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    BACKGROUND: A specific problem using the public access defibrillators (PADs) arises at the railway stations. Some countries as Germany, Austria, Switzerland, Norway and Sweden are using AC railroad net power-supply system with rated 16.7 Hz frequency modulated from 15.69 Hz to 17.36 Hz. The power supply frequency contaminates the electrocardiogram (ECG). It is difficult to be suppressed or eliminated due to the fact that it considerably overlaps the frequency spectra of the ECG. The interference impedes the automated decision of the PADs whether a patient should be (or should not be) shocked. The aim of this study is the suppression of the 16.7 Hz interference generated by the power supply of the railway systems. METHODS: Software solution using adaptive filtering method was proposed for 16.7 Hz interference suppression. The optimal performance of the filter is achieved, embedding a reference channel in the PADs to record the interference. The method was tested with ECGs from AHA database. RESULTS: The method was tested with patients of normal sinus rhythms, symptoms of tachycardia and ventricular fibrillation. Simulated interference with frequency modulation from 15.69 Hz to 17.36 Hz changing at a rate of 2% per second was added to the ECGs, and then processed by the suggested adaptive filtering. The method totally suppresses the noise with no visible distortions of the original signals. CONCLUSION: The proposed adaptive filter for noise suppression generated by the power supply of the railway systems has a simple structure requiring a low level of computational resources, but a good reference signal as well

    Removal of power-line interference from the ECG: a review of the subtraction procedure

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    BACKGROUND: Modern biomedical amplifiers have a very high common mode rejection ratio. Nevertheless, recordings are often contaminated by residual power-line interference. Traditional analogue and digital filters are known to suppress ECG components near to the power-line frequency. Different types of digital notch filters are widely used despite their inherent contradiction: tolerable signal distortion needs a narrow frequency band, which leads to ineffective filtering in cases of larger frequency deviation of the interference. Adaptive filtering introduces unacceptable transient response time, especially after steep and large QRS complexes. Other available techniques such as Fourier transform do not work in real time. The subtraction procedure is found to cope better with this problem. METHOD: The subtraction procedure was developed some two decades ago, and almost totally eliminates power-line interference from the ECG signal. This procedure does not affect the signal frequency components around the interfering frequency. Digital filtering is applied on linear segments of the signal to remove the interference components. These interference components are stored and further subtracted from the signal wherever non-linear segments are encountered. RESULTS: Modifications of the subtraction procedure have been used in thousands of ECG instruments and computer-aided systems. Other work has extended this procedure to almost all possible cases of sampling rate and interference frequency variation. Improved structure of the on-line procedure has worked successfully regardless of the multiplicity between the sampling rate and the interference frequency. Such flexibility is due to the use of specific filter modules. CONCLUSION: The subtraction procedure has largely proved advantageous over other methods for power-line interference cancellation in ECG signals

    Dataset of manually measured QT intervals in the electrocardiogram

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    BACKGROUND: The QT interval and the QT dispersion are currently a subject of considerable interest. Cardiac repolarization delay is known to favor the development of arrhythmias. The QT dispersion, defined as the difference between the longest and the shortest QT intervals or as the standard deviation of the QT duration in the 12-lead ECG is assumed to be reliable predictor of cardiovascular mortality. The seventh annual PhysioNet/Computers in Cardiology Challenge, 2006 addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations? METHOD: The PTB Diagnostic ECG Database was given to 4 cardiologists and 1 biomedical engineer for manual marking of QRS onsets and T-wave ends in 458 recordings. Each recording consisted of one selected beat in lead II, chosen visually to have minimum baseline shift, noise, and artifact. In cases where no T wave could be observed or its amplitude was very small, the referees were instructed to mark a 'group-T-wave end' taking into consideration leads with better manifested T wave. A modified Delphi approach was used, which included up to three rounds of measurements to obtain results closer to the median. RESULTS: A total amount of 2*5*548 Q-onsets and T-wave ends were manually marked during round 1. To obtain closer to the median results, 8.58 % of Q-onsets and 3.21 % of the T-wave ends had to be reviewed during round 2, and 1.50 % Q-onsets and 1.17 % T-wave ends in round 3. The mean and standard deviation of the differences between the values of the referees and the median after round 3 were 2.43 ± 0.96 ms for the Q-onset, and 7.43 ± 3.44 ms for the T-wave end. CONCLUSION: A fully accessible, on the Internet, dataset of manually measured Q-onsets and T-wave ends was created and presented in additional file: 1 (Table 4) with this article. Thus, an available standard can be used for the development of automated methods for the detection of Q-onsets, T-wave ends and for QT interval measurements

    Sources of Variation in the QT Readings: What should you be Aware of?

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    The QT interval is measured manually or automatically. In comparison with manual methods, the automated ones offer advantages in terms of absolute repeatability of measurements, immunity from errors related to observer fatigue, lack of attention, as well as efficiency and cost effectiveness that permits either more extensive and rigorous testing for the same cost as manual methods, or more rapid testing at lower cost. But a question arises: 'Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations?' We created a dataset of manually measured Q-onsets and T-ends for the PTB Diagnostic ECG Database. Further on we developed a fully automated method for QT measurements and forwarded it to PhysioNet/Computers in Cardiology Challenge, 2006. The manually measured dataset was then used as a 'gold standard' for assessment of the accuracy of the automated method. The current lecture notes summarize all our up to date publications on the QT measurements topic. Sources of variation in the QT readings are for the first time discussed by the authors

    Potential of Rule-Based Methods and Deep Learning Architectures for ECG Diagnostics

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    The main objective of this study is to propose relatively simple techniques for the automatic diagnosis of electrocardiogram (ECG) signals based on a classical rule-based method and a convolutional deep learning architecture. The validation task was performed in the framework of the PhysioNet/Computing in Cardiology Challenge 2020, where seven databases consisting of 66,361 recordings with 12-lead ECGs were considered for training, validation and test sets. A total of 24 different diagnostic classes are considered in the entire training set. The rule-based method uses morphological and time-frequency ECG descriptors that are defined for each diagnostic label. These rules are extracted from the knowledge base of a cardiologist or from a textbook, with no direct learning procedure in the first phase, whereas a refinement was tested in the second phase. The deep learning method considers both raw ECG and median beat signals. These data are processed via continuous wavelet transform analysis, obtaining a time-frequency domain representation, with the generation of specific images (ECG scalograms). These images are then used for the training of a convolutional neural network based on GoogLeNet topology for ECG diagnostic classification. Cross-validation evaluation was performed for testing purposes. A total of 217 teams submitted 1395 algorithms during the Challenge. The diagnostic accuracy of our algorithm produced a challenge validation score of 0.325 (CPU time = 35 min) for the rule-based method, and a 0.426 (CPU time = 1664 min) for the deep learning method, which resulted in our team attaining 12th place in the competition

    Bifunctionalized Allenes. Part XV. Synthesis of 2,5-dihydro-1,2-oxaphospholes by Electrophilic Cyclization Reaction of Phosphorylated α-Hydroxyallenes

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    This paper discusses a reaction of phosphorylated α-hydroxyallenes with protected or unprotected hydroxy groups involving 5-endo-trig cyclizations. Various electrophilic reagents such as sulfuryl chloride, bromine, benzenesulfenyl and benzeneselenenyl chlorides have been applied. The paper describes the reaction of 1-hydroxyalkyl-1,2-dienephosphonates with electrophiles that produces 2-methoxy-2-oxo-2,5-dihydro-1,2-oxaphospholes due to the participation of the phosphonate neighbouring group in the cyclization. On the other hand, (1E)-alk-1-en-1-yl phosphine oxides were prepared as mixtures with 2,5-dihydro-1,2-oxaphosphol-2-ium halides in a ratio of about 1:2 by chemo-, regio, and stereoselective electrophilic addition to the C2-C3-double bond in the allene moiety and subsequent concurrent attack of the external (halide anion) and internal (phosphine oxide group) nucleophiles. The paper proposes a possible mechanism that involves cyclization and additional reactions of the phosphorylated α-hydroxyallenes
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