Search results for "ECG"
showing 10 items of 102 documents
Analysis and recognition of vibratory signals : contribution to the treatment and analysis of cardiac signals for telemedecine
2014
The heart is a muscle. Its mechanical operation is like a pump charged for distributing and retrieving the blood in the lungs and cardiovascular system. Its electrical operation is regulated by the sinus node, a pacemaker or electric regulator responsible for triggering the natural heart beats that punctuate the functioning of the body.Doctors monitor the electromechanical functioning of the heart by recording an electrical signal called an electrocardiogram (ECG) or an audible signal : the phonocardiogram (PCG). The analysis and processing of these two signals are essential for diagnosis, to help detect anomalies and cardiac pathologies.The objective of this thesis is to develop signal pro…
Electrocardiogram Signal Analysing - Delineation and Localization of ECG Component
2016
In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends from noise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (…
Electrocardiogram Signal Analysing
2016
In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends fromnoise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (S…
An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals
2022
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for psychiatrists while examining patients, and for neuromarketing applications. Multimodal signals for emotion charting include electrocardiogram (ECG) signals, electroencephalogram (EEG) signals, and galvanic skin response (GSR) signals. EEG, ECG, and GSR are also known as physiological signals, which can be used for identification of human emotions. Due to the unbiased nature of physiological signals, this field has become a great motivation in recent research as physiological signals are generated autonomously from human central nervous system. Researchers have developed multiple methods for …
A microcontroller-based portable electrocardiograph system
2004
The ambulatory acquisition and monitorization of electrocardiograms (ECG) under not controlled conditions, is a practice of paramount importance in cardiology diagnosis nowadays. The ECGs are acquired while patients develop their normal life, using a portable device. The storage capacity of such devices usually ranges from 24 to 48 hours. ne systems used to perform this task are the so-called Holter systems. In this paper we describe a low cost single channel Holter system, based on a microcontroller, to register the ECG signal continuously during up to 48 hours. This microcontroller system runs off batteries, and includes many peripherals such as a display, keyboard, serial interface, soli…
An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks
2020
Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a…
Visual data mining with self-organising maps for ventricular fibrillation analysis
2012
Detection of ventricular fibrillation (VF) at an early stage is being deeply studied in order to lower the risk of sudden death and allows the specialist to have greater reaction time to give the patient a good recovering therapy. Some works are focusing on detecting VF based on numerical analysis of time-frequency distributions, but in general the methods used do not provide insight into the problem. However, this study proposes a new methodology in order to obtain information about this problem. This work uses a supervised self-organising map (SOM) to obtain visually information among four important groups of patients: VF (ventricular fibrillation), VT (ventricular tachycardia), HP (healt…
Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT
2016
International audience; In this paper, a new method based on the continuous wavelet transform is described in order to detect the QRS, P and T waves. QRS, P and T waves may be distinguished from noise, baseline drift or irregular heartbeats. The algorithm, described in this paper, has been evaluated using the Computers in Cardiology (CinC) Challenge 2011 database and also applied on the MIT-BIH Arrhythmia database (MITDB). The data from the CinC Challenge 2011 are standard 12 ECG leads recordings with full diagnostic bandwidth compared to the MITDB which only includes two leads for each ECG signal. Firstly, our algorithm is validated using fifty 12 leads ECG samples from the CinC collection…
Piecgadīgu bērnu savstarpējās saskarsmes prasmju pilnveide lomu rotaļās
2017
Studiju darba autors: Anfisa Atiķe. Studiju darba nosaukums: Piecgadīgu bērnu savstarpējās saskarsmes prasmju pilnveide lomu rotaļās. Studiju darba mērķis: izpētīt piecgadīgu bērnu savstarpējās saskarsmes prasmju pilnveides iespējas lomu rotaļās. Studiju darba ietvaros tiek izanalizēti zinātnieku atziņas par saskarsmes jēdzienu, veidošanos un izpausmēm. Tajā ir iekļauts saskarsmes termina skaidrojums zinātnieku atziņās, kā arī saskarsmes raksturojums piecgadīgiem bērniem.Vēl, studiju darbā tiek konstatēts skolotāju un bērnu sadarbības situāciju PII X, kur ir apskatīta pētījuma metodoloģija un norise, anketēšanas rezultātu analīze, novērojuma un saskarsmes novērtējuma rezultāti un to ietekme…
A portable system for multiple parameters monitoring: towards assessment of health conditions and stress level in the automotive field
2019
In this work, an electronic portable combo system able to synchronously acquire multiple signals, e.g. electrocardiographic (ECG), photoplethysmographic (PPG) and breathing waveforms, is presented. The realized system is also capable of showing in real time some physiological parameters which can be used for assessing health/stress status of the volunteer, such as heart rate and breathing frequency and their trends over time. Thanks to the use of non-invasive PPG probes, of batteries as power supply, and to the possibility to add in the future additional sensors to acquire other signals, the system could also be employed inside vehicles for assessing the status of the driver. Finally, the r…