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Wyniki wyszukiwania dla: HEART SOUNDS CLASSIFICATION
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A System for Heart Sounds Classification
PublikacjaThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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Outcome-Driven Thresholds for Ambulatory Blood Pressure Based on the New American College of Cardiology/American Heart Association Classification of Hypertension
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublikacjaWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment
PublikacjaThe main obstacle in development of intelligent autodiagnosis medical systems based on the analysis of phonocardiography (PCG) signals is noise. The noise can be caused by digestive and respiration sounds, movements or even signals from the surrounding environment and it is characterized by wide frequency and intensity spectrum. This spectrum overlaps the heart tones spectrum, which makes the problem of PCG signal filtrating complex....
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Dangerous sound event recognition using Support Vector Machine classifiers
PublikacjaA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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Application of passive acoustic radar to automatic localization, tracking and classification of sound sources
PublikacjaA concept, practical realization and applications of the passive acoustic radar to automatic localization, tracking and classification of sound sources were presented in the paper. The device consists of a new kind of multichannel miniature sound intensity sensors and a group of digital signal processing algorithms. Contrary to active radars, it does not emit the scanning beam but after receiving surrounding sounds it provides...
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The Physiological Effects of ASMR on Anxiety
PublikacjaPurpose: Autonomous Sensory Meridian Response is a novel phenomenon that is very popular these days on Youtube and Reddit to its anti-anxiety effects. As the name suggests, ASMR is a relaxing warm sensation that begins on the scalp and spreads throughout the body. This technique is also known as "brain massage," and it relies on soothing sights and sounds, like whispers and slow movements. Investigating these videos is primarily motivated...
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Processing of acoustical data in a multimodal bank operating room surveillance system
PublikacjaAn automatic surveillance system capable of detecting, classifying and localizing acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of...
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Audio-visual surveillance system for application in bank operating room
PublikacjaAn audio-visual surveillance system able to detect, classify and to localize acoustic events in a bank operating room is presented. Algorithms for detection and classification of abnormal acoustic events, such as screams or gunshots are introduced. Two types of detectors are employed to detect impulsive sounds and vocal activity. A Support Vector Machine (SVM) classifier is used to discern between the different classes of acoustic...
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Automatic localization and continous tracking of mobile sound source using passive acoustic radar
PublikacjaA concept, practical realization and applications of the passive acoustic radar for localization and continuous tracking of fixed and mobile sound sources such as: cars, trucks, aircrafts and sources of shooting, explosions were presented in the paper. The device consists of the new kind of multi-channel miniature three dimensional sound intensity sensors invented by the Microflown company and a group of digital signal processing...
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Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results
PublikacjaThe goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are...
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublikacjaA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
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Further developments of parameterization methods of audio stream analysis for secuirty purposes
PublikacjaThe paper presents an automatic sound recognition algorithm intended for application in an audiovisual security monitoring system. A distributed character of security systems does not allow for simultaneous observation of multiple multimedia streams, thus an automatic recognition algorithm must be introduced. In the paper, a module for the parameterization and automatic detection of audio events is described. The spectral analyses...
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Improving automatic surveillance by sound analysis
PublikacjaAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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Objectivization of phonological evaluation of speech elements by means of audio parametrization
PublikacjaThis study addresses two issues related to both machine- and subjective-based speech evaluation by investigating five phonological phenomena related to allophone production. Its aim is to use objective parametrization and phonological classification of the recorded allophones. These allophones were selected as specifically difficult for Polish speakers of English: aspiration, final obstruent devoicing, dark lateral /l/, velar nasal...
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Improvement of glass break acoustic signal detection via application of wavelet packet decomposition
PublikacjaThe main subject of the authors' research are non-contact methods of glass break detection based on analysis of the acoustic signal generated during the event. This problem has essential meaning for modern cost- effective alarm systems, particularly those installed into big buildings. The main difficulties of the matter are: transient character of the signal, great number of similar sounds (false signals, mainly accidental glass...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Insight into heart regeneration
PublikacjaThe mammalian heart is thought to be incapable of regeneration because of the limited ability of cardiomyocytes. to proliferate. However, it has been recently shown that the neonatal murine heart is able to restore its normal function after coronary artery ligation or even partial resection. Unfortunately, this feature is lost in a few days after birth, although lower vertebrates as zebrafish or newt, retain this ability until adulthood. Therefore,...
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Nordic Sounds
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Paremetrization of sounds for recognizing hazarodus events
PublikacjaNowoczesne systemy monitoringu działają na zasadzie automatycznego wykrywania niebezpiecznych zdarzeń na podstawie analizy obrazu z kamer i dźwięku z mikrofonów. W niniejszej publikacji skupiono się na pierwszym etapie rozpoznawania zdarzeń dźwiękowych, jakim jest parametryzacja dźwięku. Podstawą do skutecznego działania systemu jest znalezienie parametrów, których zmienność najlepiej odzwierciedla cechy charakterystyczne dźwięku...
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EUROPEAN HEART JOURNAL
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Ordinal pattern statistics for the assessment of heart rate variability
PublikacjaThe recognition of all main features of a healthy heart rhythm (the so-called sinus rhythm) is still one of the biggest challenges in contemporary cardiology. Recently the interesting physiological phenomenon of heart rate asymmetry has been observed. This phenomenon is related to unbalanced contributions of heart rate decelerations and accelerations to heart rate variability. In this paper we apply methods based on the concept...
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Journal of Classification
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Entropy Measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublikacjaWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (Fuzzy En) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Entropy measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublikacjaWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (FuzzyEn) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Machine learning system for estimating the rhythmic salience of sounds.
PublikacjaW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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Cross-talk Between the Heart and Arteries in Older 65+ Adults
PublikacjaRegulatory synchronization between the heart and the arterial walls is essential for optimal blood delivery to tissues. We investigated functional coherence between heart rhythm and aortic wall compliance in 30 volunteers aged 65 – 74. ECG and carotid and iliac pulse-wave were recorded and digitized at 2 kHz. Carotid-femoral pulse-wave transit time (cfTT) which reflex aortic compliance was assessed using the intersecting tangent...
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On the use of instantaneous complex frequency for analysis and modification of simple sounds
PublikacjaW pracy przedstawiono możliwości wykorzystania zespolonej pulsacji chwilowej do analizy i modyfikacji prostych dźwięków. Opisywany algorytm składa się z dwóch kroków: bifaktoryzacji sygnału na obwiednię minimalnofazową i fazor dodatnipskrętny, a następnie estymacja i modyfikacja zespolonej pulsacji chwilowej obu czynników faktoryzacji.
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Physics augmented classification of fNIRS signals
PublikacjaBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Cataloging & Classification Quarterly
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Vegetation Classification and Survey
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Generalised heart rate statistics reveal neurally mediated homeostasis transients
PublikacjaDistributions of accelerations and decelerations, obtained from increments of heart rate recorded during a head-up tilt table (HUTT) test provide short-term characterization of the complex cardiovascular response to a rapid controlled dysregulation of homeostasis. A generalised statistic is proposed for evaluating the neural reflexes responsible for restoring the homeostatic dynamics. An evaluation of the effects on heart rate...
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Kardiologia Polska
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Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublikacjaW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
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Szkolenie CNE: English sounds in technology
Wydarzenia„Dydaktyczne Piątki” w CNE: „English sounds in technology – pronunciation workshop”
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Seabed classification using multibeam echosounder
PublikacjaThe method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...
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Chronographic Imprint of Age-Induced Alterations in Heart Rate Dynamical Organization
PublikacjaBeat-to-beat changes in the heart period are transformed into a network of increments between subsequent RR-intervals, which enables graphical descriptions of short-term heart period variability. Three types of such descriptions are considered: (1) network graphs arising from a set of vertices and directed edges, (2) contour plots of adjacency matrices A, representing the networks and transition matrices T, resulting from A, and (3)...
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Comparison of selected electroencephalographic signal classification methods
PublikacjaA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive
PublikacjaWe argue that network methods are successful in detecting nonlinear properties in the dynamics of autonomic nocturnal regulation in short-term variability. Two modes of visualization of networks constructed from RR-increments are proposed. The first is based on the handling of a state space. The state space of RR-increments can be modified by a bin size used to code a signal and by the role of a given vertex as the representation...
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LEGO bricks for training classification network
Dane BadawczeThe data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...
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The Hough transform in the classification process of inland ships
PublikacjaThis article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...
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Using similar classification tasks in feature extractor learning
PublikacjaThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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Selection of Relevant Features for Text Classification with K-NN
PublikacjaIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Using multibeam echoes in seafloor characterisation and classification
PublikacjaThe method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...
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Entropy Measures in the Assessment of Heart Rate Variability in Patients with Cardiodepressive Vasovagal Syncope
PublikacjaSample entropy (SampEn) was reported to be useful in the assessment of the complexity of heart rate dynamics. Permutation entropy (PermEn) is a new measure based on the concept of order and was previously shown to be accurate for short, non-stationary datasets. The aim of the present study is to assess if SampEn and PermEn obtained from baseline recordings might differentiate patients with various outcomes of the head-up tilt test...
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Invasive Assessment of the Myocardial Microcirculation during Beating Heart Coronary Artery Bypass Grafting
PublikacjaCoronary artery bypass grafting may be associated with several cardiac complications, including ischemia, acute myocardial infarction, arrhythmias, or hemodynamic instability. Accumulating evidence suggests that well-developed coronary collateral circulation may protect against adverse effects, including myocardial ischemia. Assessment of myocardial microvascular perfusion is, therefore, of great clinical interest in beating heart...
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Image Classification Based on Video Segments
PublikacjaIn the dissertation a new method for improving the quality of classifications of images in video streams has been proposed and analyzed. In multiple fields concerning such a classification, the proposed algorithms focus on the analysis of single frames. This class of algorithms has been named OFA (One Frame Analyzed).In the dissertation, small segments of the video are considered and each image is analyzed in the context of its...