Sheikh Shanawaz Mostafa- Doctor of Philosophy
- Posdoctoral Researcher at Instituto Superior Técnico
Sheikh Shanawaz Mostafa
- Doctor of Philosophy
- Posdoctoral Researcher at Instituto Superior Técnico
About
87
Publications
35,838
Reads
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1,549
Citations
Introduction
Experience with working cross disciplinary research team.
Current institution
Additional affiliations
March 2021 - present
ITI - Interactive Technologies Institute
Position
- PostDoc Position
January 2021 - February 2021
Position
- PostDoc Position
Description
- MTL – Marítimo Training Lab • Analyze monitoring signals from football athletes and determine the correlation between the different features and the performance. • Develop models to predict performance and injuries, using Artificial Intelligence tools.
November 2019 - December 2020
Position
- Researcher
Description
- Sleep Analysis MITIExcell – RH62 • Development of sleep analysis techniques using machine learning. • Development of a prototype for sleep analysis. • Part of works published in different journals.
Education
February 2016 - November 2020
July 2010 - September 2012
May 2010
AKIJ Institute of Technology
Field of study
- Networking using Linux
Publications
Publications (87)
This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. By using data from a network of six meteorological stations and deep learning techniques, the produced model is capable of predicting wind speed and direction up to 30-min...
Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking the multifactorial nature of injuries. This study introduces an automated injury identification and p...
This work introduces a deep learning architecture tailored for accurate wind speed and direction forecasting for airports using a grid-based input. Moving beyond the limitations of conventional forecasting methods, which struggle with rapid and localized atmospheric changes and demand substantial computational power, this study positions a machine...
This study examines the application of machine learning to enhance wind nowcasting by using a Kolmogorov-Arnold Network model to improve predictions from the Global Forecast System at Madeira International Airport, a site affected by complex terrain. The research addresses the limitations of traditional numerical weather prediction models, which of...
Wind direction nowcasting is crucial in various sectors, particularly for ensuring aviation operations and safety. In this context, the TELMo (Time-series Embeddings from Language Models) model, a sophisticated deep learning architecture, has been introduced in this work for enhanced wind-direction nowcasting. Developed by using three years of data...
The conventional process of visual detection and manual harvesting of the banana bunch has been a known problem faced by the agricultural industry. It is a laborious activity associated with inconsistency in the inspection and grading process, leading to post-harvest losses. Automated fruit harvesting using computer vision empowered by deep learnin...
In aviation, accurate wind prediction is crucial, especially during takeoff and landing at complex sites like Gran Canaria Airport. This study evaluated five Deep Learning models: Long Short-Term Memory (LSTM), Vanilla Recurrent Neural Network (vRNN), One-Dimensional Convolutional Neural Network (1dCNN), Convolutional Neural Network Long Short-Term...
![Wind speed and direction extraction from METAR [24], showing (A) an...](publication/380478108/figure/fig3/AS:11431281258282238@1720022813557/Wind-speed-and-direction-extraction-from-METAR-24-showing-A-an-overview-of-the_Q320.jpg)
Accurate wind speed and direction nowcasting in regions with complex terrains remains a challenge, and critical for applications like aviation. This study proposes a new methodology by harnessing Convolutional Neural Networks and Long Short-Term Memory models with satellite imagery to address wind predictions in a complex terrain, centered on Madei...
Traditional methods for water-level measurement usually employ permanent structures, such as a scale built into the water system, which is costly and laborious and can wash away with water. This research proposes a low-cost, automatic water-level estimator that can appraise the level without disturbing water flow or affecting the environment. The e...
This study focuses on improving sentiment analysis in restaurant reviews by leveraging transfer learning and transformer-based pre-trained models. This work evaluates the suitability of pre-trained deep learning models for analyzing Natural Language Processing tasks in Portuguese. It also explores the viability of utilizing edge devices for Natural...
Sleep is a complex process divided into different stages, and a decrease in sleep quality can lead to adverse health-related effects. Therefore, diagnosing and treating sleep-related conditions is crucial. The Cyclic Alternating Pattern (CAP) is an indicator of sleep instability and can assist in assessing sleep-related disorders such as sleep apne...
The unique geographical and topographical features of Madeira International Airport in Portugal significantly influence flight safety, primarily due to variable wind patterns. In this study, a machine learning approach is developed to predict runway operational statuses at Madeira International Airport, focusing on addressing wind-related challenge...
This study presents a novel approach for kernel selection based on Kullback–Leibler divergence in variational autoencoders using features generated by the convolutional encoder. The proposed methodology focuses on identifying the most relevant subset of latent variables to reduce the model’s parameters. Each latent variable is sampled from the dist...
Wind forecasting, which is essential for numerous services and safety, has significantly improved in accuracy due to machine learning advancements. This study reviews 23 articles from 1983 to 2023 on machine learning for wind speed and direction nowcasting. The wind prediction ranged from 1 min to 1 week, with more articles at lower temporal resolu...
Wind factors significantly influence air travel, and extreme conditions can cause operational disruptions. Machine learning approaches are emerging as a valuable tool for predicting wind patterns. This research, using Madeira International Airport as a case study, delves into the effectiveness of feature creation and selection for wind nowcasting,...
This study conducted a systematic review to determine the feasibility of automatic Cyclic Alternating Pattern (CAP) analysis. Specifically, this review followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to address the formulated research question: is automatic CAP analysis viable for clinical ap...
Cyclic Alternating Pattern (CAP) is a sleep instability marker defined based on the amplitude and frequency of the electroencephalogram signal. Because of the time and intensive process of labeling the data, different machine learning and automatic approaches are proposed. However, due to the low accuracy of the traditional approach and the black b...
Introduction: Evaluating sleep stability can provide valuable insights into understanding sleep disorders and their underlying causes. The present study introduces an approach to assessing sleep stability, by developing Near-Real-Time (NRT) Cyclic Alternating Pattern (CAP) A-phase Index (API). Materials & methods: The study evaluates 15 healthy and...
Chatbots are becoming increasingly popular and require the ability to interpret natural language to provide clear communication with humans. To achieve this, intent detection is crucial. However, current applications typically need a significant amount of annotated data, which is time-consuming and expensive to acquire. This article assesses the ef...
Through the development of artificial intelligence, some capabilities of human beings have been replicated in computers. Among the developed models, convolutional neural networks stand out considerably because they make it possible for systems to have the inherent capabilities of humans, such as pattern recognition in images and signals. However, c...
The number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic continues, with new variants constantly emerging. Therefore, to prevent the virus from spreading, coronavirus cases must be diagnosed as soon as possible. The COVID-19 pandemic has had a devastating impact on people’s health and the economy worldwide. For COVID-...
The ripeness of bananas is the most significant factor affecting nutrient composition and demand. Conventionally, cutting and ripeness analysis requires expert knowledge and substantial human intervention, and different studies have been conducted to automate and substantially reduce human effort. Using the Preferred Reporting Items for the Systema...
The agrotech revolution is emerging and aims to use advanced precision technology, such as real-time analysis of soil nutrients and weather conditions using sensors to meet the future demands for food in a more sustainable, efficient, and eco-friendly way. IoT is remodeling agriculture, enabling farmers with a wide range of techniques, namely preci...
Study Objectives
Sleep stability can be studied by evaluating the Cyclic Alternating Pattern (CAP) in electroencephalogram signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night’s sleep.
Methods
Two ensem...
This work proposed kernel selection approaches for probabilistic classifiers based on features produced by the convolutional encoder of a variational autoencoder. Particularly, the developed methodologies allow the selection of the most relevant subset of latent variables. In the proposed implementation, each latent variable was sampled from the di...
ProBoost, a new boosting algorithm for probabilistic classifiers, is proposed in this work. This algorithm uses the epistemic uncertainty of each training sample to determine the most challenging/uncertain ones; the relevance of these samples is then increased for the next weak learner, producing a sequence that progressively focuses on the samples...
The Cyclic Alternating Pattern (CAP) is a periodic activity detected in the electroencephalogram (EEG) signals. This pattern was identified as a marker of unstable sleep with several possible clinical applications; however, there is a need to develop automatic methodologies to facilitate real-world applications based on CAP assessment. Therefore, a...
The cyclic alternating pattern is a microstructure phasic event, present in the non-rapid eye movement sleep, which has been associated with multiple pathologies, and is a marker of sleep instability that is detected using the electroencephalogram. However, this technique produces a large quantity of information during a full night test, making the...
Methodologies for automatic non-rapid eye movement and cyclic alternating pattern analysis were proposed to examine the signal from one electroencephalogram monopolar derivation for the A phase, cyclic alternating pattern cycles, and cyclic alternating pattern rate assessments. A population composed of subjects free of neurological disorders and su...
Biomedical decision making involves multiple signal processing, either from different sensors or from different channels. In both cases, information fusion plays a significant role. A deep learning based electroencephalogram channels' feature level fusion is carried out in this work for the electroencephalogram cyclic alternating pattern A phase cl...
Resumo A qualidade do sono pode ser afetada pela ocorrência de um distúrbio relacionado ao sono e, entre esses distúrbios, a apneia obstrutiva do sono é um dos mais prevalentes. Apesar de a polissonografia ser o teste padrão para a análise do sono, é um exame caro e complexo que não está disponível para a maioria da população mundial. Desta forma,...
The electrocardiogram (ECG) has significant clinical importance for analyzing most cardiovascular diseases. ECGs beat morphologies, beat durations, and amplitudes vary from subject to subject and diseases to diseases. Therefore, ECG morphology-based modeling has long-standing research interests. This work aims to develop a simplified ECG model base...
The relevance of sleep quality examination for clinical diagnosis is increasing with the discovery of new relationships with several diseases and the overall wellness. This assessment is commonly performed by conducting interviews with the subjects, evaluating the self-report and psychological variables. However, this approach has a major constrain...
Objective. The cyclic alternating pattern is a marker of sleep instability identified in the electroencephalogram signals whose sequence of transient variations compose the A phases. These phases are divided into three subtypes (A1, A2, and A3) according to the presented patterns. The traditional approach of manually scoring the cyclic alternating...
Obstructive sleep apnea is considered to be one of the most prevalent sleep-related disorders that can affect the general population. However, the gold standard for the diagnosis, polysomnography, is an expensive and complicated process that is commonly unavailable to a large group of the population. Alternatively, automatic approaches have been de...
Obstructive sleep apnea is a disorder characterized by pauses in respiration during sleep. Due to this disturbance in breathing, there is a decrease in the oxygen saturation (SpO2) level. Thus, SpO2 can be used as a source of information for the automatic detection of apnea. Several solutions exist in the literature where different features are use...
![Experimental setup for data acquisition [18]](publication/326088007/figure/fig1/AS:941461616984144@1601473349874/Experimental-setup-for-data-acquisition-18_Q320.jpg)
Hands are the main environmental manipulator for the human being. After losing a hand, the only alternative for the victim is to use a prosthesis. Despite the progress of science, the modern prosthesis has the same age-old problem of accurate force estimation. Among different kinds of force, clench force is the most important one. Because of this i...
A probabilistic model for sleep analysis is proposed in this work, modeling the temporal relation between the sleep structure and the presence of the electroencephalogram (EEG) Cyclic Alternating Pattern (CAP) with a Hidden Markov Model (HMM). Sleep scoring is frequently performed by assigning a state to each thirty second epoch. However, this appr...
The quality of sleep can be affected by the occurrence of a sleep related disorder and, among these disorders, obstructive sleep apnea is commonly undiagnosed. Polysomnography is considered to be the gold standard for sleep analysis. However, it is an expensive and labor-intensive exam that is unavailable to a large group of the world population. T...
Obstructive sleep apnea (OSA) is a common sleep disorder characterized by interrupted breathing during sleep. Because of the cost, complexity, and accessibility issue related to polysomnography, the gold standard test for apnea detection, automation of the diagnostic test based on a simpler method is desired. Several signals can be used for apnea d...
Background and Objective
Sleep apnea is a common sleep disorder, usually diagnosed using an expensive, highly specialized, and inconvenient test called polysomnography. A single SpO2 sensor based on an automated classification system can be developed to simplify the apnea detection. The main objective of this work is to develop a classifier based o...
Sleep related disorders can severely disturb the quality of sleep. Among these disorders, obstructive sleep apnea (OSA) is highly prevalent and commonly undiagnosed. Polysomnography is considered to be the gold standard exam for OSA diagnosis. Even though this multi-parametric test provides highly accurate results, it is time consuming, labor-inten...
Background:
Multiple methods have been developed to assess what happens between and within time series. In a particular type of these series, the previous values of the currently observed series are contingent on the lagged values of another series. These cases can commonly be addressed by regression. However, a model selection criteria should be e...
Quality of sleep can be assessed by analyzing the cyclic alternating pattern, a long-lasting periodic activity that is composed of two alternate electroencephalogram patterns, which is considered to be a marker of sleep instability. Experts usually score this pattern through a visual examination of each one-second epoch of an electroencephalogram s...
Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and implemented automatic scoring processes to address these issues, based on fewer sensors and automatic cla...
Objective:
The term sleep quality is widely used by researchers and clinicians despite the lack of a definitional consensus, due to different assumptions on quality quantification. It is usually assessed using subject self-reporting, a method that has a major limitation since the subject is a poor self-observer of their sleep behaviors. A more pre...
The cyclic alternating pattern is a characteristic phasic event present in the electroencephalogram signals and is commonly scored by experts through a visual examination. This pattern is considered to be a marker of sleep instability and can be used for the assessment of sleep quality. However, in manual scoring, each one second epoch of the signa...
Sleep quality is directly related to overall wellness and can reveal symptoms of several diseases. However, the term “sleep quality” still lacks a definitional consensus and is commonly assessed in sleep labs with polysomnography, comprising high costs, or through sleep questionnaires, a highly subjective technique. Multiple methods have been propo...
The gold standard for assessment of sleep quality is the polysomnography where physiological signals are used to generate both quantitative and qualitative measurements. Despite the production of highly accurate results, polysomnography is a complex, uncomfortable and expensive process, inaccessible to a large group of the population. Home monitori...
The cyclic alternating pattern can be seen as an electroencephalogram marker of sleep instability. This pattern consists of alternations between activation and quiescent phases. An automatic cyclic alternating pattern detection method is proposed, having the advantage, over other previously proposed methods, of being featureless. Therefore, there i...
Obstructive sleep apnea is a highly prevalent sleep related breathing disorder and polysomnography is the gold standard exam for diagnosis. Despite providing results with high accuracy this multi-parametric test is expensive, time consuming and does not fit with the new tendency in health care that is changing the focus to prevention and wellness....
Specific information about types of appliances and their use in a specific time window could help determining in details the electrical energy consumption information. However, conventional main power meters fail to provide any specific information. One of the best ways to solve these problems is through non-intrusive load monitoring, which is chea...
Sleep quality is commonly assessed with subject self-reporting, interviews and psychological variables. However, more precise methods comprise estimation of physiological signals where polysomnography is considered to be the gold standard and can be performed to produce qualitative or quantitative measurements regarding the subjects sleep. However,...
The selection of the correct values for passive elements, resistors, and capacitors, is an important task in analog active filter design. The classic method of choosing passive elements is a difficult task and can lead to errors. To reduce the incidence of error and human effort evolutionary optimization techniques are used to select the values of...
Sleep disorders are a common health condition that can affect numerous aspects of life. Obstructive sleep apnea is one of the most common disorders and is characterized by a reduction or cessation of airflow during sleep. In many countries this disorder is usually diagnosed in sleep laboratories, by a polysomnography, which is an expensive procedur...
One of the most common sleep-related disorders is obstructive sleep apnea, characterized by a reduction of airflow while breathing during sleep and cause significant health problems. This disorder is mainly diagnosed in sleep labs with polysomnography, involving high costs and stress for the patient. To address this situation multiple systems have...
The aim of this study is to develop an automatic detector of the cyclic alternating pattern by first detecting the activation phases (A phases) of this pattern, analysing the electroencephalogram during sleep, and then applying a finite state machine to implement the final classification. A public database was used to test the algorithms and a tota...
In a classical classification process, automatic sleep apnea detection involves creating and selecting the features, using prior knowledge, and apply them to a classifier. A different approach is applied in this paper, where a Deep Belief Network is used for feature extraction, without using domain-specific knowledge, and then the same network is u...
Health care is changing the focus from primary and specialty care to prevention and wellness. Therefore, home health care is seen as one of the most relevant wellness services due to high accessibility and low cost of diagnosis. The growth relevance given to the sleep related disorders, due to the high importance of sleep in our lives, is specifica...
Endoscopy is an imaging procedure used for diagnosis as well as for some surgical purposes. The
camera used for the endoscopy should be small and able to produce a good quality image or video, to reduce
discomfort of the patients, and to increase the efficiency of the medical team. To achieve these fundamental
goals, a small endoscopy camera with a...
Some people cannot produce sound although their facial muscles work properly due to having problem in their vocal cords. Therefore, recognition of alphabets as well as sentences uttered by these voiceless people is a complex task. This paper proposes a novel method to solve this problem using non-invasive surface Electromyogram (sEMG). Firstly, ele...
A gamma function is essential for adjusting the response of any display device. In the case of endoscopy, it is even more important because for endoscopy it is not only the satisfaction of the user but the diagnosis of patient’s problems that could lead to life and death decision sometimes. In this paper, a technique of approximating the gamma func...
This paper describes the research carried out to eliminate the noise found in ECG signal and cardiac rhythm. For this, ECG signals were collected carefully from BIOPAC data acquisition system and MIT-BIH database. MIT-BIH noise stress test database was used for generating realistic noises. In addition, to get a better denoised ECG, Symlet wavelet w...
Ultra wide-band (UWB) microwave technology is a promising candidate to detect the early breast cancer. This paper aims to depict pattern recognition performance of support vector machine (SVM) for confocal UWB breast tumor imaging dataset. A novel feature extraction technique is also introduced in this paper for the signal classification perfectly...
The purpose of the research is to evaluate the different human emotions through Electroencephalogram (EEG) signal and to receive information about the internal changes of brain state. The paper presents the detection of human emotion based on some salient features of EEG signal. For this purpose, seven emotional states have been specified such as r...
An electrocardiogram (ECG) detects cardiac abnormalities by measuring the electrical activity generated by the heart. In order to truthful diagnosis, a good quality ECG signal is very essential. ECG signal has to be processed in the existence of unwanted noise. Noise corrupts the ECG signal amplitude and duration and lead to misdiagnosis. Wavelet-b...
In this paper, we describe the consequences of mental conditions due to the variation of electrocardiogram, electroencephalogram and blood pressure using BIOPAC system. The different data sets are collected using BIOPAC system in which subjects were induced to undergo the specific sequence of mental condition or cognitive state. For getting physiol...
Clench force estimator is highly desirable in the field of prosthesis hand. It is one of the most used postures among five types of postures. In this paper, we propose to estimate the clench force using two types of Surface Electromyography (SEMG). The SMEG consists of rectified SEMG and integrated SEMG. A two layered artificial neural network (ANN...
In this paper, we describe the consequences of mental conditions due to the variation of electrocardiogram, electroencephalogram and blood pressure using BIOPAC system. The different data sets are collected using BIOPAC system in which subjects were induced to undergo the specific sequence of mental condition or cognitive state. For getting physiol...
Subscriber satisfaction and maximum radio resource utilization are the
pivotal criteria in communication system design. In multi-Carrier CDMA system,
different paging algorithms are used for locating user within the shortest
possible time and best possible utilization of radio resources. Different
paging algorithms underscored different techniques...
To cope with the increasing demand of wireless communication services
multi-carrier systems are being used. Radio resources are very limited and
efficient usages of these resources are inevitable to get optimum performance
of the system. Paging channel is a low-bandwidth channel and one of the most
important channels on which system performance dep...
Railway grade crossing is become the major headache for the transportation
system. This paper describes an intelligent railway crossing control system for
multiple tracks that features a controller which receives messages from
incoming and outgoing trains by sensors. These messages contain detail
information including the direction and identity of...
Cardiovascular diseases (CVDs) are the most widespread cause of death in many countries all over the world.
Electrocardiogram (ECG) is one of the most basic useful, easily available and low cost tools for the early diagnosis and evolution of
many cardiac problems. ECG signal can potentially corrupted by various types of noises which lead to incor...
Robotics has a momentous feature and future in our daily life. It can make our life fast and easier. But for real life man and
robot interaction like household or workplace creates a new question about the controlling the robot. It is quite impossible to command
a robot through a keyboard or interfaces like this. The problem can be solved by the...
ECG models are complex and their computational time is high. In this paper, we propose a Gaussian wave-based model which can simulate ECG wave as well as P, Q, R, S and T waves individually. In addition, this model is capable of simulating various kinds of practical phenomena. The coefficient of the model was calculated by nonlinear least square te...
Noise reduction is important for getting useful bio-medical signal such as, ECG signals. Because ECG signal can be corrupted by various types of noise which leads to incorrect diagnosis. However, details features of the signal must be conserved very well after the de-noising for proper diagnosis. In this paper, Symlet wavelet filter as well as diff...
Electrocardiogram (ECG) is one of the inexpensive, simple to perform, risk-free tools for the early analysis of many cardiac abnormalities. The relation between mechanical event and electrical event is important because they are used to determine idiosyncrasy of heart. This paper describes the ECG as a primary tool for evaluating electrical events...
The use of information and communication technology has been playing a vital role in the 21st century due to
globalization. The democratic government of Bangladesh has declared the “Vision 2021” which targets establishment of a
resourceful and modern country by 2021 through effective use of information and communication technology-a "Digital
Ban...
Railway crossing are become a major problem for both railway and general people in Bangladesh. Now days the rail way can’t meet the demand of crossing gate because more & more path become cross point. And building & maintaining cost of conventional crossing gate is huge. Out of the cost problem manual gate has many problems the man on gate can slee...
Human civilization has entered in the new and ultramodern age. But the “Middle age complex” does not eliminated from the society. Still we live in a world of discrimination and diversity. This miscellany phenomenon is common in every corner of Bangladesh. Health care is dominating among them. Healthcare center is not available in the remote and rur...
The use of information and communication technology has been playing a vital role in the 21st century due to globalization. The democratic government of Bangladesh has declared the “Vision 2021” which targets establishment of a resourceful and modern country by 2021 through effective use of information and communication technology-a "Digital Bangla...
Questions
Question (1)
I am working in biomedical signal processing. When I am doing classification sensitivity is low. I understand that my data is unbalanced. However It is visible that changing parameter changes the results. So my idea is to choose the best layers and parameters possible. However, my problem lies there I do not know a method which can optimized the Deep ANN. Normally I use matlab. Is there any tool or method to do this?
