Papers by Mustafa Alhamdi
ECG based system for arrhythmia detection and patient identification
ABSTRACT
The electrocardiogram (ECG) is the recording of heart activity obtained by measuring the signals ... more The electrocardiogram (ECG) is the recording of heart activity obtained by measuring the signals from electrical contacts placed on the skin of the patient. By analyzing ECG, it is possible to detect the rate and consistency of heartbeats and identify possible irregularities in heart operation. This paper describes a set of techniques employed to pre-process the ECG signals and extract a set of features – autoregressive (AR) signal parameters used to characterise ECG signal. Extracted parameters are in this work used to accomplish two tasks. Firstly, AR features belonging to each ECG signal are classified in groups corresponding to three different heart conditions – normal, arrhythmia and ventricular arrhythmia. Obtained classification results indicate accurate, zero-error classification of patients according to their heart condition using the proposed method. Sets of extracted AR coefficients are then extended by adding an additional parameter – power of AR modelling error and a su...
2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
We are developing a thin neutron detector for applications including decommissioning at Fukushima... more We are developing a thin neutron detector for applications including decommissioning at Fukushima Daiichi. We are developing a system based to detect fast and thermal neutrons using a SiC detector and SiC front-end amplifier. Here we evaluate candidate converter layers for thermal neutron detection by means of Monte Carlo simulation using MCNP 6.2. We also make preliminary investigation of gamma rejection as well as comparison with simulations using Geant4 10.05.01. We require neutron sensitivity and gamma rejection in a very small device.
Signal Discrimination in Thinned Silicon Neutron Detectors using Machine learning
High gamma backgrounds can pose a significant source of interference in solid-state neutron detec... more High gamma backgrounds can pose a significant source of interference in solid-state neutron detectors making the neutron flux approximation inaccurate. This work focuses on optimizing a thin sensor thickness to enhance the neutron capture rate and reject gammas, and analysis of multiple input source through the differentiation of signals using pattern recognition. Gamma isotopes and neutron spectrums have been simulated using GEANT4 + Electronic noise estimation. Different machine learning tools have been considered to discriminate different gamma and neutron sources, including PCA, RNN, SVM, KNN, ResNet and others.
The electrocardiogram is a skin surface measurement of the electrical activity of the heart over ... more The electrocardiogram is a skin surface measurement of the electrical activity of the heart over time. This activity is detected by electrodes attached to the surface of the skin and recorded or displayed by an external medical device. Doctors use electrocardiograms to detect and diagnose conditions such as arrhythmias (abnormal heart rhythms) and myocardial infarctions (heartattacks). The work described in this thesis investigates the system designed for two primary applications, electrocardiogram classification system based on autoregressive models which identifies normal (healthy) from abnormal (unhealthy) electrocardiogram signals and the electrocardiogram biometric system based on analytic and modeling features which identifies each person individually from his or her electrocardiogram. In recent years, a number of signal processing techniques have been used to design electrocardiogram signal auto-classification and biometric identification systems. electrocardiogram classifica...
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Papers by Mustafa Alhamdi