Omar altwijri - Academia.edu (original) (raw)

Papers by Omar altwijri

Scientific Reports

Gait data collection from overweight individuals walking on irregular surfaces is a challenging t... more Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectiv...

Materials Express

Annually, more than two million deaths are caused due to the exposure of air pollution which caus... more Annually, more than two million deaths are caused due to the exposure of air pollution which cause damage to the lungs and the respiratory system. Topography, light-textured topsoil, drought, and desert climate make Saudi Arabia vulnerable to sand storms and dust. The study aims to examine the deposition of dust particles in the human airway and its relationship to asthma and investigate the possibility that the dust deposition would be changed with different particle size diameters. An idealized upper respiratory tract 3D model was constructed with computer-aided design software. Later a computational simulation was performed using computational fluid dynamics with 3 different sizes (0.03, 2, and 9 microns) of the dust particles to find out the change in airflow velocity and pressure. Our findings revealed that small size particles will travel more with less inertia, whereas bigger size particles will travel less but with higher inertia at airflow rates of 30 L/min. It was found th...

Systems

The integration of Student Response Systems (SRSs) into classroom teaching is a pioneering progre... more The integration of Student Response Systems (SRSs) into classroom teaching is a pioneering progression in social sciences research that has shown potential in boosting student engagement and elevating academic success. However, no extensive study has examined the impact of its use on academic achievement within a sizable number of students of diverse cofactors, such as scientific discipline and study levels. The current study aims to conduct a comprehensive score analysis investigating the effect of SRS use on academic performance. It involved a total of 6047 male and female undergraduate students from four scientific disciplines, seven colleges, four campuses, and 13 courses covering all study levels within King Saud University. The student’s scores along with their attributes were anonymously collected from the university system. A voluntary anonymous survey was distributed to collect students’ perceptions of SRS along with their personal attributes, such as learning style, and cl...

Applied Sciences

Artificial intelligence (AI) is one of the most promising approaches to health innovation. The us... more Artificial intelligence (AI) is one of the most promising approaches to health innovation. The use of AI in image recognition considerably extends findings beyond the constraints of human sight. The application of AI in medical imaging, which relies on picture interpretation, is beneficial for automatic diagnosis. Diagnostic radiology is evolving from a subjective perceptual talent to a more objective science thanks to AI. Automatic object detection in medical images is an essential AI technology in medicine. The problem of detecting brain tumors at an early stage is well advanced with convolutional neural network (CNN) and deep learning algorithms (DLA). The problem is that those algorithms require a training phase with a big database of more than 500 images and time-consuming with a complex computational and expensive infrastructure. This study proposes a classical automatic segmentation method for detecting brain tumors in the early stage using MRI images. It is based on a multil...

Bioengineering

Walking speed is considered a reliable assessment tool for any movement-related functional activi... more Walking speed is considered a reliable assessment tool for any movement-related functional activities of an individual (i.e., patients and healthy controls) by caregivers and clinicians. Traditional video surveillance gait monitoring in clinics and aged care homes may employ modern artificial intelligence techniques to utilize walking speed as a screening indicator of various physical outcomes or accidents in individuals. Specifically, ratio-based body measurements of walking individuals are extracted from marker-free and two-dimensional video images to create a walk pattern suitable for walking speed classification using deep learning based artificial intelligence techniques. However, the development of successful and highly predictive deep learning architecture depends on the optimal use of extracted data because redundant data may overburden the deep learning architecture and hinder the classification performance. The aim of this study was to investigate the optimal combination o...

Physical and Engineering Sciences in Medicine

Sustainability

Enhancing faculty performance and student interaction during the lecture is essential to achieve ... more Enhancing faculty performance and student interaction during the lecture is essential to achieve sustainable learning development. The current study aims to evaluate the effect of using “Student response systems (SRS)” on faculty performance and student interaction in the classroom. The faculty members at King Saud University were encouraged to join a university-scale educational project that involve utilizing SRSs within their classes. From Fall 2016 to Fall 2019, a total of 371 faculty members and 19,746 students were enrolled in the current study. By the end of each semester, faculty and student satisfaction surveys were distributed to evaluate their perceptions of using SRS in the class. The faculty members’ and students’ response rates were 75.7% and 38.1%, respectively, and represented 18 different colleges from different disciplines within the university. Furthermore, the study covered a wide range of study levels for bachelor’s degrees ranging from levels 1–10. The study dem...

Synthetic bio-materials are a substitute to diseased tissue. In ideal condition the fabricated ti... more Synthetic bio-materials are a substitute to diseased tissue. In ideal condition the fabricated tissue must mimic native tissue structurally as well as functionally. Millions are spent, however, little or no attention is paid to as how the fabricated material will behave under physiological conditions. We propose that a material must first be designed through software then it must be analysed for its mechanical properties and then it must go through prototyping and biocompatibility tests. Bone is a porous tissue with great variation in pore size and porosities. However, the effect of pore size on how the material will behave under mechanical forces and due to blood flowin vivo is poorly characterised. In this study we report the effect of pore size on the mechanical integrity and impact of blood flow of a synthetic polymer scaffold via computer simulation model. It was observed that increasing the pore size may significantly reduce implant success. It is suggested that anticipated si...

BioNanoScience, 2019

Abdominal aortic aneurysm (AAA) is a life-threatening disease when the diameter exceeds its safet... more Abdominal aortic aneurysm (AAA) is a life-threatening disease when the diameter exceeds its safety margin or the aortic wall reaches its mechanical strength. Both of these potential problems need to be clinically assessed. The geometrical influence on blood flow behavior and hemodynamic changes of AAA are not fully clinically understood. The study aimed to explore creating comprehensive and detailed models for use in reconstruction, modeling, and simulating three-dimensional (3D) patient-specific geometry based on two-dimensional (2D) computed tomography images. The patient information was extracted from computed tomography images and the AAA patient's database. The 3D geometrical models were created using MIMICS software segmentation tools and exported in STL files to ANSYS Workbench. Computational fluid dynamics (CFD) and finite volume methods were used to solve Navier-Stokes equations for fluid flow in the 3D domain. Blood was treated as incompressible and Newtonian fluid, and a transient flow with a timedependent velocity waveform assigned at the inlet boundary. The computational results were visualized using ANSYS Fluent postprocessing. The CFD transient simulation results are presented using the hemodynamic parameters, including velocity vectors, flow patterns (streamlines), pressure distribution, and wall shear stress. The demonstrated results are part of the study aims and methods in order to provide detailed approaches of computational analysis. The procedures used in this study would be useful for understanding the biomechanical influence on blood flow and hemodynamics.

Journal of Biomedical Engineering and Medical Imaging, 2018

The aim of this study is to analyze the possibilities to measure the wall stress on the thinnest ... more The aim of this study is to analyze the possibilities to measure the wall stress on the thinnest and thickest side of the AAA by using patient's Specific Finite Element (SFE) models, in order for understanding the rupture of AAA in a better approach. Patient specific model with different in position, Finite Element Analysis (FEA) models that were studied earlier by Di Martino et al. (1998) [1], was adopted. The AAA was modelled as a homogenous, isotropic, incompressible, linear elastic material with Young's modulus (E) and Poisson's ratio (µ) having value of 0.11 MPa and µ = 0.45, respectively. The values of E and µ was determined from uniaxial loading tests performed on specimens of AAA. In order to cast peak systolic blood pressure of a healthy patient, pressure of 145 mmHg was directed to the internal surface of the models. FEA models of AAA were analysed using ANSYS Finite Element Package 15.0 version. Values of stress was observed on the scale of von-Mises, this method helps to locate area with highest stress i.e. to calculate failure criteria by combining the stress in threedimensions. In order to determine the collapse of AAA wall von-Mises stress is commonly use for the assessment of the AAA stress. Our findings and results strengthens the earlier studies performed by Polzer et al. (2010) [2] and Altuwaijri (2015) [3], where AAA wall stress was reduced by formation of thrombus. Thus reducing the chance of AAA rupture and supporting the wall strength. Our findings suggest that thrombus clearly works as a shield to guard the AAA wall from rupture. However, more research and further studies are required that corroborate the relation between the biological and mechanical factors to understand the role of the thrombus for AAA rupture.

2018 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges (GMEPE/PAHCE), 2018

Abdominal aortic aneurysm (AAA) is a cardio-vascular disease occurring when the aorta becomes wea... more Abdominal aortic aneurysm (AAA) is a cardio-vascular disease occurring when the aorta becomes weak and develops a balloon expansion in its wall which leads to rupture and cause death. The role of the intraluminal thrombus (ILT) is examined using five finite element models to understand its effect on wall stresses and it was found that ILT volume and thickness decrease the stresses on wall and may lower the risk of rupture.

This paper aimed to classify two forearm muscles known as Flexor Carpi Ulnaris (FCU) and Extensor... more This paper aimed to classify two forearm muscles known as Flexor Carpi Ulnaris (FCU) and Extensor Carpi Radialis Longus (ECRL) using surface Electromyography (sEMG) signal during different hand prehension tasks, such as cylindrical, tip, spherical, palmar, lateral and hook while grasping any object. Thirteen Machine Learning (ML) algorithms were analyzed to compare their performance using a single EMG time domain feature called integrated EMG (IEMG). The tree-based methods have the top performance to classify the forearm muscles than other ML methods among all those 13 ML algorithms. Results showed that 4 out of 5 tree-based classifiers achieved more than 75% accuracies, where the random forest method showed maximum classification accuracy (85.07%). Additionally, these tree-based ML methods computed the variable importance in classification margin. The results showed that the lateral grasping was the most important moving variable for all those algorithms except AdaBoost where tippi...

Children have special requirements in pulmonary drug delivery, as their lungs evolve continuously... more Children have special requirements in pulmonary drug delivery, as their lungs evolve continuously until they become adult. To deliver the drug to a specific area in the appropriate quantity, we need to study the deposition of particles. In our study we modelled and simulated airflow on a 5-year-old child using a CAD software to understand aerosol deposition. To design and simply the model of a child URT (Upper Respiratory Tract) on a CAD (Computer Aided Design) Software. Child specific model consist of mouth, trachea, and bronchi (left & right) with 11, 9, and 6.2 years old, respectively, was adopted. Using SolidWorks the URT model was sketched and extruded. All the simulation works were performed using software ANSYS CFX. An aerosol deposition converges at a steady-state condition for 500 iterations. A decrease in discharge was recorded as deposition transits from contraction prior to trachea at a velocity of 15 mm/s and a count of approximation of 28,000 with a time-lapse of 5 sec...

Biomedical Research-tokyo, 2016

Although the effect of an Electromyographic (EMG) signal on the Biceps Brachii (BB) muscle is at ... more Although the effect of an Electromyographic (EMG) signal on the Biceps Brachii (BB) muscle is at the forefront of human movement analysis, there is limited information regarding the importance of the differences in the age-related EMG responses during contraction. The present study aimed to compare the BB muscle activity of three different groups of young adults divided based on age and to find a relationship between surface EMG and endurance time during isometric contraction. The EMG signal was recorded in 30 healthy right-arm-dominant young male subjects during a handgrip force task. The subjects were rationally divided into one of the three age groups (ten in each group): adolescents (‘A’; aged 17.3 ± 1.4 years), vicenarians (‘V’; 24.6 ± 2.1 years), and tricenarians (‘T’; 33.2 ± 1.1 years). The muscle activation during contraction was determined as the root mean square (RMS) EMG signal normalised to the peak RMS EMG signal during a 10-s isometric contraction. The statistical anal...

Aim: Diabetes mellitus (DM) is a common chronic disease which require frequent monitoring of bloo... more Aim: Diabetes mellitus (DM) is a common chronic disease which require frequent monitoring of blood sugar levels. The purpose of this study was to assess the handling and effectiveness of self-monitoring of blood glucose (SMBG) among the diabetic patients of Saudi Arabia. Methods: A questionnaire was designed and electronic survey was conducted through Google forms, a web-based application among adult male and female diabetes patients. A comprehensive information was collected regarding the utilization and effectiveness of the glucometer and its impact on health and life. A questionnaire divided into four sections containing questions related to personal information, SBGM device, measurement process and measurement outcomes was employed. Diabetologists were consulted to evaluate the responses of the participants. Results were evaluated using descriptive statistics on Microsoft Excel. Results: A total of 56 respondents (30 males and 26 females) participated in this survey study. The r...

Purpose: The relationship between EMG and elbow angle was investigated to identify the signal cha... more Purpose: The relationship between EMG and elbow angle was investigated to identify the signal characteristics of upper-limb muscles during isometric contraction. The study would improve the current understanding of electrophysiological activities of the human upper limbs, which would aid the development of prosthetic arms for rehabilitation research. Subjects and Methods: Ten subjects aged 22.4(±1.5) years participated in this study. The electromyography signals from the biceps brachii muscle were recorded during isometric contraction. The root mean square and mean absolute value of the EMG signals were calculated and evaluated to assess the relationship between the signals and elbow angles. In addition, the force exerted by the upper limb was recorded using a dynamometer to identify more features of the relationship. Results: The results revealed that both the RMS and MAV of the EMG signals are not significantly related with the elbow angle (r2=0.70 and 0.21; p=0.075 and 0.43, resp...

Advances in Intelligent Systems and Computing, 2019

The initial identification of breast cancer and the prediction of its category have become a requ... more The initial identification of breast cancer and the prediction of its category have become a requirement in cancer research because they can simplify the subsequent clinical management of patients. The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. In addition, the ranked order of the variables based on their importance differed across the ML algorithms. The results demonstrated that the three bagging ensemble ML algorithms, namely, RF ERT and DT, yielded better classification accuracies (78-86%) compared with the two boosting algorithms, GBT and ADB (60-75%). We hope that these our results would help improve the classification of breast tissue to allow the early prediction of cancer susceptibility.

Sensors, 2021

Human body measurement data related to walking can characterize functional movement and thereby b... more Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environmen...

International Journal of Engineering & Technology, 2018

Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of... more Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of medicine. Stable indoor environment including favorable temperature, humidity, air flow and number of microorganisms requires consistent monitoring. This paper aimed to develop a fuzzy logic-based intelligent ventilation system to control the indoor air quality in pharmaceutical sites. Specifically, in the proposed fuzzy inference system, the ventilation system can control the air flow and quality in accordance with the indoor temperature, humidity, air flow and microorganisms in the air. The MATLAB® fuzzy logic toolbox was used to simulate the performance of the fuzzy inference system. The results show that the efficiency of the system can be improved by manipulating the input-output parameters according to the user’s demands. Compared with conventional heating, ventilation and air-conditioning (HVAC) systems, the proposed ventilation system has the additional feature of the existence ...