Oliver Faust

Oliver Faust
Anglia Ruskin University | ARU

DEng, PhD, CEng, Dipl.-Ing (FH), FHEA, MIET

About

151
Publications
71,690
Reads
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5,477
Citations
Citations since 2016
54 Research Items
4321 Citations
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
Additional affiliations
January 2014 - present
Habib University
Position
  • Professor (Associate)
September 2009 - December 2013
Ngee Ann Polytechnic
Position
  • Visiting Lecturer

Publications

Publications (151)
Article
Full-text available
Background: Sleep stage classification is a crucial process for the diagnosis of sleep or sleep-related diseases. Currently, this process is based on manual electroencephalogram (EEG) analysis, which is resource-intensive and error-prone. Various machine learning models have been recommended to standardize and automate the analysis process to addr...
Article
Mental performance classification is a critical issue for brain-computer interfaces. Accurate and reliable classification of good or bad mental performance gives important clues for the preliminary diagnosis of some diseases and mental stress. In this work, we put forward an objective artificial intelligence model to quantify the clarity of thought...
Article
Automated sleep disorder detection is challenging because physiological symptoms can vary widely. These variations make it difficult to create effective sleep disorder detection models which support hu-man experts during diagnosis and treatment monitoring. From 2010 to 2021, authors of 95 scientific papers have taken up the challenge of automating...
Article
Full-text available
Sleep Apnoea (SA) is a common chronic illness that affects nearly 1 billion people around the world, and the number of patients is rising. SA causes a wide range of psychological and physiological ailments that have detrimental effects on a patient’s wellbeing. The high prevalence and negative health effects make SA a public health problem. Whilst...
Article
Full-text available
In this study, we evaluate and compare the diagnostic performance of ultrasound for non‐invasive axillary lymph node (ALN) metastasis detection. The study was based on fusing shear wave elastography (SWE) and B‐mode ultrasonography (USG) images. These images were subjected to pre‐processing and feature extraction, based on bi‐dimensional empirical...
Article
Full-text available
Multiple sclerosis (MS) is a chronic demyelinating condition characterized by plaques in the white matter of the central nervous system that can be detected using magnetic resonance imaging (MRI). Many deep learning models for automated MS detection based on MRI have been presented in the literature. We developed a computationally lightweight machi...
Data
In this study, photographs of mask (name start 1), no mask (name start 2), and improper mask (name start 3) were collected by researchers via internet search. The discovered photos were combined with 4072 photos that were uploaded to the Kaggle website by Larxel (https://www.kaggle.com/andrewmvd/face-mask-detection). A face detection application wa...
Article
Full-text available
Heart Rate Variability (HRV) is a good predictor of human health because the heart rhythm is modulated by a wide range of physiological processes. This statement embodies both challenges to and opportunities for HRV analysis. Opportunities arise from the wide-ranging applicability of HRV analysis for disease detection. The availability of modern hi...
Article
Full-text available
Mask usage is one of the most important precautions to limit the spread of COVID-19. Therefore, hygiene rules enforce the correct use of face coverings. Automated mask usage classification might be used to improve compliance monitoring. This study deals with the problem of inappropriate mask use. To address that problem, 2075 face mask usage images...
Article
Full-text available
Background and objectives : Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, which can, in turn, translate into various measurements such as the variation in blood flow volume, heart rate variability, blood pressure, etc. Hence, PPG signals can produce a wide variety of biolo...
Article
Full-text available
Medical imaging is a useful tool for disease detection and diagnostic imaging technology has enabled early diagnosis of medical conditions. Manual image analysis methods are labor-intense and they are susceptible to intra as well as inter-observer variability. Automated medical image analysis techniques can overcome these limitations. In this revie...
Conference Paper
Full-text available
Over the last decades, sleep apnea has become one of the most prevalent healthcare problems. Diagnosis and treatment monitoring are key elements when it comes to addressing this public health crisis. A problem for diagnosis and treatment monitoring is a chronic lack of specialized lab facilities which results in long waiting times or the absence of...
Article
Full-text available
Abnormal heart rhythms, also known as arrhythmias, can be life-threatening. AFIB and AFL are examples of arrhythmia that affect a growing number of patients. This paper describes a method that can support clinicians during arrhythmia diagnosis. We propose a deep learning algorithm to discriminate AFIB, AFL, and NSR RR interval signals. The algorith...
Article
We developed a software tool to validate a deep learning algorithm for an atrial fibrillation detection service with heart rate data from a clinical study. The deep learning algorithm analyses the measurement data and establishes an estimated atrial fibrillation probability for each heartbeat. The software tool displays both data and deep learning...
Article
Full-text available
This paper presents a scientific foundation for automated stroke severity classification. We have constructed and assessed a system which extracts diagnostically relevant information from Magnetic Resonance Imaging (MRI) images. The design was based on 267 images that show the brain from individual subjects after stroke. They were labeled as either...
Article
Acute Lymphoblastic Leukemia (ALL) is a cancer of the blood cells which is characterized by a large number of immature lymphocytes, known as blast cells (myeloblasts). To aid the ALL diagnosis, we propose to automate the blast cell detection using Artificial Intelligence (AI). Our automation system incorporates an object detection method that predi...
Article
Background Autism spectrum disorder is a common group of conditions affecting about one in 54 children. Electroencephalogram (EEG) signals from children with autism have a common morphological pattern which makes them distinguishable from normal EEG. We have used this type of signal to design and implement an automated autism detection model. Mate...
Article
Full-text available
In this paper we review devices that can be used in the home environment for Atrial Fibrillation (AF) detection. Detection and subsequent treatment of this heart rhythm disorder is an important strategy for stroke prevention, because AF increases stroke risk fivefold. The device review was carried out in two steps. In the first step, we have examin...
Article
Full-text available
In 2020 the world is facing unprecedented challenges due to COVID‐19. To address these challenges, many digital tools are being explored and developed to contain the spread of the disease. With the lack of availability of vaccines, there is an urgent need to avert resurgence of infections by putting some measures, such as contact tracing, in place....
Article
Skin melanoma is a potentially life-threatening cancer. Once it has metastasized, it may cause severe disability and death. Therefore, early diagnosis is important to improve the conditions and outcomes for patients. The disease can be diagnosed based on Digital-Dermoscopy (DD) images. In this study, we propose an original and novel Automated Skin-...
Article
Arrhythmias are abnormal heart rhythms that can be life-threatening. Atrial Fibrillation (AFIB), Atrial Flutter (AFL), Supraventricular Tachycardia (SVT), Sinus Tachycardia (ST), and Sinus Bradycardia (SB) are common arrhythmias that affect a growing number of patients. In this paper we describe a method to detect these arrhythmias in RR interval s...
Article
Full-text available
In this paper, we discuss hybrid decision support to monitor atrial fibrillation for stroke prevention. Hybrid decision support takes the form of human experts and machine algorithms working cooperatively on a diagnosis. The link to stroke prevention comes from the fact that patients with Atrial Fibrillation (AF) have a fivefold increased stroke ri...
Chapter
Sleep stage scoring is an important aspect of sleep medicine and research. The literature for automated sleep stage scoring contains a wide range of methods. A major goal of this study is to give an overview on how these methods are combined such that the automated sleep stage scoring functionality emerges. We discuss and advise on signal processin...
Article
Full-text available
Sleep is vital for one’s general well-being, but it is often neglected, which has led to an increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep interruptions, extreme daytime drowsiness, or snoring, can be detected with sleep analysis. However, sleep analysis relies on visuals conducted by experts, and is susceptible...
Article
Sleep apnea is a common condition that is characterized by sleep-disordered breathing. Worldwide the number of apnea cases has increased and there has been a growing number of patients suffering from apnea complications. Unfortunately, many cases remain undetected, because expensive and inconvenient examination methods are formidable barriers with...
Article
Full-text available
Aim: In this study we have investigated the problem of cost effective wireless heart health monitoring from a service design perspective. Subject and methods: There is a great medical and economic need to support the diagnosis of a wide range of debilitating and indeed fatal non-communicable diseases, like Cardiovascular Disease (CVD), Atrial Fi...
Article
Full-text available
Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implem...
Article
Full-text available
Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implem...
Preprint
Full-text available
This paper describes the validation of a deep learning model for Internet of Things (IoT) based health care applications. As such, the deep learning model was created to detect episodes of Atrial Fibrillation (AF) using Heart Rate (HR) signals. The initial Long Short-Term Memory (LSTM) model was developed using 20 data sets, from distinct subjects,...
Article
Full-text available
This paper describes the validation of a deep learning model for Internet of Things (IoT) based health care applications. As such, the deep learning model was created to detect episodes of Atrial Fibrillation (AF) using Heart Rate (HR) signals. The initial Long Short-Term Memory (LSTM) model was developed using 20 data sets, from distinct subjects,...
Article
Full-text available
Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left untreated, leading to myocardial infarction (MI) that may induce irreversible heart muscle damage, resulting in heart chamber remodeling and eventual congestive heart fa...
Article
In this paper we propose a hybrid decision-making process for medical diagnosis. The hypothesis tested is that a deep learning system can provide real-time monitoring of Atrial Fibrillation (AF), a prevalent heart arrhythmia, and a human cardiologist will then verify the results and reach a diagnosis. The verification step adds the necessary checks...
Article
Full-text available
The gravity of ischemic stroke is the key factor in deciding upon the optimum therapeutic intervention. Ischemic stroke can be divided into three main groups: lacunar syndrome (LACS), partial anterior circulation syndrome (PACS), and total anterior circulation stroke (TACS), where the corresponding severity is mild, medium, and high, respectively....
Article
Full-text available
Background and objective: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stag...
Article
Full-text available
Background and objective: Complex fractionated atrial electrograms (CFAE) may contain information concerning the electrophysiological substrate of atrial fibrillation (AF); therefore they are of interest to guide catheter ablation treatment of AF. Electrogram signals are shaped by activation events, which are dynamical in nature. This makes it dif...
Article
Cardiovascular disease has been the leading cause of death worldwide. Electrocardiogram (ECG)-based heart disease diagnosis is simple, fast, cost effective and non-invasive. However, interpreting ECG waveforms can be taxing for a clinician who has to deal with hundreds of patients during a day. We propose computing machinery to reduce the workload...
Article
The purpose of this study was to investigate the use of a cost-effective heart rate monitor sensor and Arduino Uno configuration to accurately detect simulated sleep apnea, through the use of the inter-beat interval (R-R interval). Three separate 30min heart rate recordings were taken, each with six simulated sleep apnea events ranging from 20 to 4...
Article
Full-text available
Atrial Fibrillation (AF), either permanent or intermittent (paroxysnal AF), increases the risk of cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective treatment to prevent stroke. Long term cardiac monitoring improves the likelihood of diagnosing paroxysmal AF. We used a deep learning system to detect AF beats in...
Article
Full-text available
Background and objective: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.2017. Methods: An initial bibliometric analysis shows that the reviewed papers focused on Electromy...
Article
Full-text available
The Computers in Biology and Medicine (CBM) journal promotes the use of computing machinery in the fields of bioscience and medicine. Since the first volume in 1970, the importance of computers in these fields has grown dramatically, this is evident in the diversification of topics and an increase in the publication rate. In this study, we quantify...
Article
Full-text available
Microstrip patch directional antennas are an attractive solution for modern wireless systems due to their high gain and directivity. Being an attractive solution creates the need to design such devices for various application scenarios. We have addressed that need by designing, simulating, and testing a rectangular microstrip patch directional ante...
Article
Full-text available
In this paper, we review the use of texture features for cancer detection in Ultrasound (US) images of breast, prostate, thyroid, ovaries and liver for Computer Aided Diagnosis (CAD) systems. This paper shows that texture features are a valuable tool to extract diagnostically relevant information from US images. This information helps practitioners...
Article
Depression is a mental disorder that negatively affects the day to day activities of a patient. Diagnosing depression is of paramount importance to reduce suffering for the patient and support network. Electroencephalograph (EEG) signal variations can indicate neurological diseases associated with mental trauma. EEG being a non-invasive technique,...
Article
In this study, we analyze nonlinear feature extraction methods in terms of their ability to support the diagnosis of coronary artery disease (CAD) and myocardial infarction (MI). The nonlinear features were extracted from electrocardiogram (ECG) signals that were measured from CAD patients, MI patients as well as normal controls. We tested 34 recur...
Article
This study documents our efforts to provide computer support for the diagnosis of congestive heart failure (CHF). That computer support takes the form of an index value. A high index value indicates a low probability of CHF, and an index value below a threshold of 25.6 suggests a high probability of CHF. To create that index, we have designed a sop...
Article
The diagnosis of Coronary Artery Disease (CAD), Myocardial Infarction (MI) and carotid atherosclerosis is of paramount importance, as these cardiovascular diseases may cause medical complications and large number of death. Ultrasound (US) is a widely used imaging modality, as it captures moving images and image features correlate well with results...
Article
Full-text available
Seasonal depression seriously diminishes the quality of life for many patients. To improve their condition, we propose LUXAMET, a bright light therapy system. This system has the potential to relieve patients from some of the symptoms caused by seasonal depression. The system was designed with a formal and model driven design methodology. This meth...
Article
Full-text available
Humans need sleep. It is important for physical and psychological recreation. During sleep our consciousness is suspended or least altered. Hence, our ability to avoid or react to disturbances is reduced. These disturbances can come from external sources or from disorders within the body. Obstructive Sleep Apnea (OSA) is such a disorder. It is caus...
Article
Full-text available
The interpretation of Electroencephalography (ECG) signals is difficult, because even subtle changes in the waveform can indicate a serious heart disease. Furthermore, these waveform changes might not be present all the time. As a consequence, it takes years of training for a medical practitioner to become an expert in ECG-based cardiovascular dise...
Article
Full-text available
Background: The brain's continuous neural activity during sleep can be monitored by electroencephalogram (EEG) signals. The EEG wave pattern and frequency vary during five stages of sleep. These subtle variations in sleep EEG signals cannot be easily detected through visual inspection. Summary: A range of time, frequency, time-frequency and nonl...
Article
Full-text available
Imaging techniques have gained tremendous popularity and pace in current trend of medical diagnostics. The key reason lies in the fact that such techniques extract clinical information with higher speed and accuracy compared to manual diagnosis by doctors. Moreover, the images serve as important records/evidences of diseases, hence the images are s...
Thesis
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This thesis documents DEng research work at Chiba University which leads towards the formalization of biomedical algorithms for health care systems. The thesis title “formal and model driven design for biomedical engineering” reflects the structure of the research work. The research work was centered on two main areas (a) formal modeling and (b) fu...
Article
Fatty Liver Disease (FLD) is a progressively prevalent disease that is present in about 15% of the world population. Normally benign and reversible if detected at an early stage, FLD, if left undetected and untreated, can progress to an irreversible advanced liver disease, such as fibrosis, cirrhosis, liver cancer and liver failure, which can cause...
Article
Full-text available
Electroencephalography (EEG) is an important tool for studying the human brain activity and epileptic processes in particular. EEG signals provide important information about epileptogenic networks that must be analyzed and understood before the initiation of therapeutic procedures. Very small variations in EEG signals depict a definite type of bra...
Article
Purpose:The concept of real-time is very important, as it deals with the realizability of computer based health care systems. Method:In this paper we review biomedical real-time systems with a meta-analysis on Computational Complexity (CC), Delay (Δ) and Speedup (Sp). Results:During the review we found that, in the majority of papers, the term re...
Article
Full-text available
The objective of this project was to improve the accuracy of cardiac arrhythmia detection by using advanced signal processing and machine learning methods. The proposed Computer-Aided Diagnosis (CAD) system classified Premature Ventricular Contraction (PVC) and normal Electrocardiogram (ECG) signals using unsupervised machine learning algorithms. T...
Article
Fatty Liver Disease (FLD) is a progressively prevalent disease that is present in about 15% of the world population. Normally benign and reversible if detected at an early stage, FLD, if left undetected and untreated, can progress to an irreversible advanced liver disease, such as fibrosis, cirrhosis, liver cancer and liver failure, which can cause...
Article
Heart signals, taken from an Electrocardiogram (ECG) machine, consist of P wave, QRS complex and T wave. These signals contain hidden, but vital information, which enable clinicians to pre-diagnose a disease before any symptoms can be observed. This hidden information is better recognized in the Discrete Wavelet Transform (DWT) domain than in time...
Article
Introduction: Breast cancer is a type of cancer originating from breast tissue, it occurs in both women and men. Normally, it will start when a breast cell becomes abnormal and this abnormality can either be benign or malignant. In Singapore, an average of 1490 woman (29%) were diagnosed with breast cancer and the number of cases has been steadily...
Article
Full-text available
The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, i...