Mohamed Yacin Sikkandar
University of Majmaah, Medical-Equipment-Technology, Faculty Member
Purpose Insomnia-related affective functional disorder may negatively affect social cognition such as empathy, altruism, and attitude toward providing care. No previous studies have ever investigated the mediating role of attention... more
Purpose Insomnia-related affective functional disorder may negatively affect social cognition such as empathy, altruism, and attitude toward providing care. No previous studies have ever investigated the mediating role of attention deficit in the relationship between insomnia and social cognition. Methods A cross-sectional survey was carried out among 664 nurses (Mage = 33.03 years; SD ± 6.93 years) from December 2020 to September 2021. They completed the Scale of Attitude towards the Patient (SAtP), the Athens Insomnia Scale (AIS), a single-item numeric rating scale assessing the increasing severity of attention complaints, and questions relating to socio-demographic information. The analysis was carried out by examining the mediating role of attention deficit in the relationship between insomnia and social cognition. Results The prevalence of insomnia symptoms was high (52% insomnia using the AIS). Insomnia was significantly correlated with attention problems (b = 0.18, standard e...
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In this paper, the feasibility of automated and accurate in vivo measurements of vascular parameters continuously and non-invasively using ultrasound sensor is presented. Vascular parameters such as pulse wave velocity (PWV), blood... more
In this paper, the feasibility of automated and accurate in vivo measurements of vascular parameters continuously and non-invasively using ultrasound sensor is presented. Vascular parameters such as pulse wave velocity (PWV), blood pressure (BP), arterial compliance (AC) and stiffness index (SI) are affluent indicators of cardiovascular disorders and needs to be monitored non-invasively and continuously during surgeries and follow-up procedures. Cuff based or invasive catheter techniques are considered as gold standard to measure BP and are fed manually to compute AC and SI which employ imaging algorithms. In this context, a Continuous and Non-Invasive Vascular Stiffness and Arterial Compliance Screener (CaNVAS) is developed to measure said parameters continuously and non-invasively using ultrasound sensor. Acoustic waves of 5 MHz (2.2 – 10 MHz) are driven through target arterial walls, reflected echoes captured, pre-processed and frequency shift is used to calculate PWV. It is obse...
Research Interests: Biosensors and BioSensors
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Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orifice area is reduced leading to many complications in heart function. Noninvasive and less expensive procedures for diagnosis are not currently... more
Mitral Stenosis (MS) is an abnormal condition of the heart mitral valve in which the valve orifice area is reduced leading to many complications in heart function. Noninvasive and less expensive procedures for diagnosis are not currently available. The aim of this work was to explore the use of the radial artery pulse (RAP) to diagnose MS. This paper analyzed the effect of the development and growth of MS on possible radial artery noninvasive assessment parameters. For this, MS was introduced to ex vivo by varying the orifice area to either 1, 2, 3, 4 or 5[Formula: see text]cm2 in a hybrid cardiopulmonary electrical analogous model based on clinically obtained healthy controls with an orifice area of 6[Formula: see text]cm2. Results showed that a mitral valve area less than 2[Formula: see text]cm2 significantly influenced the pulse magnitude and time parameters. A strong correlation was observed in pulse height (PH), mean pulse height (MPH), and time occurrence of the dichotic notch...
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Research Interests: Engineering, Mathematics, Biomedical Engineering, Medicine, Cross Correlation, and 15 moreHumans, Fasting, Male, Heart rate, Electromyography, Enteric Nervous System, Adult, Gastrointestinal motility, Discrete wavelet transform, Fingers, Healthy Subjects, Normalized Cross Correlation, Frequency Domain, Electrogastrogram, and Medical and Health Sciences
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Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found... more
Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found useful in several applications of brain and cancer imaging such as prostate cancer, breast cancer, and ovarian cancer. At the same time, the vessel images hold important medical details which offer strategies for a qualified diagnosis. Recently developed image processing techniques can be employed to segment vessels. Since vessel segmentation on PAI is a difficult process, this paper employs metaheuristic optimization-based vascular segmentation techniques for PAI. The proposed model involves two distinct kinds of vessel segmentation approaches such as Shannon’s entropy function (SEF) and multilevel Otsu thresholding (MLOT). Moreover, the threshold value and entropy function in the segmentation process are optimized using three metaheuristics such as ...
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This work presents a portable, affordable and reliable vein locating device to overcome the complications in vein localization irrespective of age and tissue thickness during medical procedures like Phlebotomy and intravenous infusion. A... more
This work presents a portable, affordable and reliable vein locating device to overcome the complications in vein localization irrespective of age and tissue thickness during medical procedures like Phlebotomy and intravenous infusion. A prototype has been developed using infrared (IR) detector and multispectral near infrared (NIR) (740,765,770,780 nm) source. The differential absorption of the NIR by veins due to the presence of deoxyhemoglobin, helps in enhancing the localization of the vein. The detector is integrated with the single board computer (SBC) and connected with LCD through serial programming interface (SPI) for real time display of veins. The initial observations have found to be successful. It is expected that this affordable device will help in reducing time and improving accessibility to locate antecubital and cephalic vein without multiple incision and minimal pain.
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Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are... more
Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are many medical imaging and processing technologies to improve the diagnostic process of DR to overcome the lack of human experts. In the existing image processing methods, there are issues such as lack of noise removal, improper clustering segmentation and less classification accuracy. This can be accomplished by automatic diagnosis of DR using advanced image processing method. The cotton wool spot (CWS), hard exudates (HE) contains a common manifestation of many diseases in retina including DR and acquired immunodeficiency syndrome. In the present work, super iterative clustering algorithm (SICA) is proposed to identify the CWS, HE on retinal image. Feature-based medical image retrieval (FBMIR) datasets are utilized for this purpose. Noises present on t...
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According to consensus, the use of Computerized Tomography (CT) methodology for early finding of several disease, yields both quick and reliable results. Expert radiologists reported that COVID19 has exhibit severalmanners in CT images.... more
According to consensus, the use of Computerized Tomography (CT) methodology for early finding of several disease, yields both quick and reliable results. Expert radiologists reported that COVID19 has exhibit severalmanners in CT images. In this research, a novel technique of fusing and rankingfeatures based Deep Learning Approach was proposed to detect COVID-19 in its early stages. To create sub-datasets, 32x32 as Subset-1 and 64x64 as Subset-2, within the framework of the proposed procedure, 300 patch images as COVID-19 and Non-COVID-19 were used in the training and testing phases. A VB-Net Deep learning-based segmentation system was created to segment the infection regions in CT scans image of COVID-19 patients. To improve the proposed methodperformance, feature fusion and a ranking method were used.The Convolutional Neural Network (CNN) technique is used in transfer learning. The processed data was then categorized into two types as by using a Support Vector Machine (SVM). This s...
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In the quantitative assessment of Diabetic maculopathy from Spectral Domain Optical Coherence Tomography (SDOCT) images, analysis of intraretinal fluid filled regions plays a vital role because of its comparative superiority in providing... more
In the quantitative assessment of Diabetic maculopathy from Spectral Domain Optical Coherence Tomography (SDOCT) images, analysis of intraretinal fluid filled regions plays a vital role because of its comparative superiority in providing tissue-level anatomical information. The detailed study on efficacy and performance of soft computing techniques-based automatic detection and diagnosis for SDOCT retinal images is still in the preliminary stage. Although some automatic algorithms have been proposed to segment retinal layers in recent times, full accuracy in edge detection continues to be a challenging problem. Some researchers have developed different versions of automatic algorithms for segmenting intraretinal fluid based on region-based level-set method and the retinal layers by dual gradient method. This particular level-set implementation is carried out using a fast front propagation algorithm. A valid search region is then defined to identify layer boundaries. The features of ...
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In this paper, the flow dynamic behavior of the filter press electrochemical reactor (FPECR) has been investigated for the treatment of liquid biomedical wastewater. The residence time distribution is utilized as a tool to investigate the... more
In this paper, the flow dynamic behavior of the filter press electrochemical reactor (FPECR) has been investigated for the treatment of liquid biomedical wastewater. The residence time distribution is utilized as a tool to investigate the flow dynamic behavior of the electrolyte within the reactor. The reactor is operated at different current densities of 2, 4, 6, 8, and 10 A/dm2 with RuO2/ Ti as an electrode by varying flow rates such as 20, 40, 60, 80, and 100 L/h. Impacts of various flow rates on flow dynamics were examined. The outcomes of this study demonstrate the presence of a dead volume and short-circuiting in the reactor were reduced for the lowest flow rate of 20 L/h in the reactor at 10 A/dm2. The potential of the FPECR was experimentally validated by analyzing the chemical oxygen demand (COD) removal efficiency, total dissolved solids, and total suspended solids emanating from the wastewater. Findings of this study reveal that maximum COD reduction of about 94% was achi...
Analysis of Parkinson's disease (PD) patient's gait pattern from foots vertical ground reaction forces' (VGRF) is a thought-provoking research problem with substantial scientific applications. The purpose of the present work... more
Analysis of Parkinson's disease (PD) patient's gait pattern from foots vertical ground reaction forces' (VGRF) is a thought-provoking research problem with substantial scientific applications. The purpose of the present work is to advance this approach further and investigate relationship of VGRF signals obtained from patients with PD foots as a function of time. Gait analysis based on instrumented technique has been extensively used in gait laboratories and there is a lack of understanding gait patterns in different phases of gait cycle. In this study, a modern signal processing method called wavelet-based semblance analysis is performed on time series signals obtained from VGRF sensors placed under the foots of PD patients. Semblance analysis between VGRF signals of PD patients in normal walking and dual tasking shows that it has high cross correlation (P <0.05) than control subjects. Semblance power ration (PRSEM) is always greater than 1 for control subjects and i...
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Thermography is a non-invasive and promising clinical method widely being used in screening of breast cancer. Breast thermal images show the heat distribution, depicting the manifestation of cancerous lesions with hot regions. Accurate... more
Thermography is a non-invasive and promising clinical method widely being used in screening of breast cancer. Breast thermal images show the heat distribution, depicting the manifestation of cancerous lesions with hot regions. Accurate segmentation of these hotspots is very vital in determining the severity of the lesions, localization and treatment regimen. In this work, color segmentation based on superpixel scheme is proposed to extract the hotspots from breast thermal images. Here, we employ the most recently proposed Gaussian mixture model superpixels, featuring semantically defined boundaries to segment the hotspots with ease. The proposed system tested with a standard dataset exhibits best performance, evaluated with various statistical metrics. It demonstrates very high segmentation accuracy around 99.84%. Visual analyses and statistical comparisons with ground truth images establish the superiority of proposed system over existing methods. Proposed method could increase dia...
Tumor interpretation on cancer image can lead to early detection of cancer with the prevalence of breast cancer being the second leading cause for death in women. Segmentation of mammographic images is a challenging space because of the... more
Tumor interpretation on cancer image can lead to early detection of cancer with the prevalence of breast cancer being the second leading cause for death in women. Segmentation of mammographic images is a challenging space because of the complexity in extracting data without causing any source of artefacts on the image. Diagnosis becomes difficult when data extraction is challenging. In order to cater effective diagnosis and effective treatment, segmentation is a vital process. This paper discusses about two segmentation method, Watershed and Local Center of Masses. Comparison between these two algorithms based on the amount of data extraction for six different categories of mammographic images, the apt segmentation method for data extraction is found out. Watershed provides an average dice score of 0.53, and occupies 665 KB memory space and avails 5 seconds running time whereas LCM avails on an average of 0.59 dice score, 250 KB memory space and 1008 seconds computing time. This can...
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Heart disease diagnosis is a very hard task in the medical field, so the mortality rate is increased every day. Also, the diagnosing process is implemented in recent times to predict heart disease. The method of diagnosing a disease in... more
Heart disease diagnosis is a very hard task in the medical field, so the mortality rate is increased every day. Also, the diagnosing process is implemented in recent times to predict heart disease. The method of diagnosing a disease in the medical field can be regarded not only as a new unknown situation to obtain clinical data and data collected from clinical experience, but also as a decision-making process as well as a doctor's diagnosis. The detection of heart abnormalities mainly depends on the examination of the ECG signal at the appropriate sampling period. The data is trained and tested must include more data to get the data as features. These properties are an accurate measure of the diagnosis of heart disease. The conventional system is having some problems like processing time is high, and it gives low accuracy, so the proposed Regressive Learning-Based Neural Network Classifier (RLNNC) system is implemented. The proposed system RLNNC presents a fully automated algorithm for the classification of heart disease, based on the Regressive Learning-Based Neural Network Classifier (RLNNC) and automated initial seed detection. With the advancement of machine learning and information technology, the development of an automated system. This can be predicted the same on this basis for patients with heart disease, and the drug occurs for the benefit of detecting and analyzing the heart disease. Analysis has shown that the proposed Regressive Learning-Based Neural Network Classifier (RLNNC) based techniques promote greater efficiency and higher accuracy than traditional methods.
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Fluid flows play a major role in everyday life, such as thunderstorms, environmental disasters, in engineering fields, applied biosciences to understand complex processes such as blood flow, breathing and renal flow in living systems.... more
Fluid flows play a major role in everyday life, such as thunderstorms, environmental disasters, in engineering fields, applied biosciences to understand complex processes such as blood flow, breathing and renal flow in living systems. Understanding of flow physics is important to execute detailed engineering and healthcare product development. Mathematical modelling can solve the physics of fluid dynamics using partial differential equations (PDE) built on conservation laws. This model can be solved numerically by Computational Fluid Dynamics (CFD) to yield quantitative results. CFD has attracted significant interest in the biomedical engineering area, from researchers to study the complex human anatomical and physiological processes, response to diseases and its effectiveness to develop prosthetics. The introductory sections of the review explain the basics of CFD and its use in biomedical engineering research. The review then focuses on the applications of CFD in biomedical proble...
Computational Fluid Dynamics (CFD) based model is proposed in this work to evaluate the effects of wall shear stress (WSS) on Carotid artery bifurcation (CAB) region. This study involves the flow inside a carotid artery with an aneurysm... more
Computational Fluid Dynamics (CFD) based model is proposed in this work to evaluate the effects of wall shear stress (WSS) on Carotid artery bifurcation (CAB) region. This study involves the flow inside a carotid artery with an aneurysm that dynamically grows from 10mm to 15mm. The wall shear stress (WSS) and the flow effects during this dynamic process is captured and studied. The studies were conducted assuming the artery to be a rigid wall and WSS estimated at various regions of interest. A normal carotid artery was modelled in a computer aided design software through extraction of CT image. An aneurysm of 10mm was incorporated and a user defined function coded to dynamically increase the size of the aneurysm from 10 to 15 mm during several pulse of the flow. The flow simulation was performed using a finite volume numerical technique by solving a set of fluid flow equations. The blood was considered as Non-Newtonian fluid and flow is laminar. The velocity pulse over time was given as input for both rest and exercise conditions. The results were processed to extract the WSS as well as the flow pattern across three cross-sections. A strong vortex with reduction in WSS with increase in aneurysm was noted. The strong vortex could possibly cause damage to inner walls, thinning it, and thus causing an increase in aneurysm size. A high gradient at the bifurcation region is also seen. This shear may cause cell damage and a reason for arteriosclerosis.
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Vertical Ground Reaction Force (VGRF) is a force obtained during gait cycle beneath the feet and is used to screen the severity of Parkinson’s disease (PD) patient’s in clinical environment. This article investigates the VGRF signals... more
Vertical Ground Reaction Force (VGRF) is a force obtained during gait cycle beneath the feet and is used to screen the severity of Parkinson’s disease (PD) patient’s in clinical environment. This article investigates the VGRF signals (left and right) semblance nature among PD patients and control subjects as a function of time and possibility of reconstructing dual tasking VGRF signal from normal walking VGRF signals using radial basis function (RBF) based artificial intelligence (AI). There are many traditional methods for gait analysis and these methods are purely subjective and none made semblance analysis of same subjects gait pattern in different tasking. In order to overcome the difficulties faced by PD patients, RBF based AI is proposed in this research to reconstruct the dual tasking VGRF signal from normal walking VGRF signal. 93 PD patients with mean age: 66.3 years (63% men), and 73 healthy controls with mean age: 66.3 years (55% men) datasets are used in this work. Propo...
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A left ventricular assist device (LVAD) is a surgically implanted mechanical pump being used for patients with end-stage heart failure (HF). One of the significant clinical challenges in using LVADs is its remarkable changes in... more
A left ventricular assist device (LVAD) is a surgically implanted mechanical pump being used for patients with end-stage heart failure (HF). One of the significant clinical challenges in using LVADs is its remarkable changes in hemodynamic parameters during a change in body position from supine to standing. In standing position, vasodilatation of veins occurs in the legs, which decreases left ventricular end-diastolic pressure, and, in turn, the preload to the LVAD. In this research, a numerical investigation is carried out to evaluate the effect of LVAD in cardiac hemodynamic parameters such as cardiac output (CO) and stroke work (SW) under preload, normal, and afterload conditions. A Proportional–integral–derivative (PID) controller associated with an LVAD pump model and cardiovascular system (CVS) model is developed to study the cardiac hemodynamic and its performance during HF condition by changing system parameters in one cardiac cycle. The performance of the proposed model is ...
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In this paper, a numerical estimation of wall shear stress (WSS) in a compliant Thoracic Aorta (TA) with aneurysm is modeled and the hemodynamic pattern is studied using Computational Fluid Dynamics (CFD). Thoracic Aortic Aneurysm (TAA)... more
In this paper, a numerical estimation of wall shear stress (WSS) in a compliant Thoracic Aorta (TA) with aneurysm is modeled and the hemodynamic pattern is studied using Computational Fluid Dynamics (CFD). Thoracic Aortic Aneurysm (TAA) is an excessively localized enlargement of TA caused by weakness in the arterial wall and it can rupture the inner wall intima and continue on to the outer wall adventitia. WSS is a tangential force exerted by blood flow on the vessel wall, and its estimation is clinically very important because any change in WSS is considered as a vital cue in the onset of aneurysm. In this work, a three-dimensional (3D) model of a TAA reconstructed from computed tomography (CT) images comprising of 600 slices with 1-mm resolution from neck to hip is considered and patient-specific simulations have been carried out in compliant TA under rest and exercise conditions. The findings show that the change in wall geometry was marginal due to variation in pressure forces i...
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A Vision Based Patient Monitoring system focuses on detecting abnormal activities of a patient. In real-world, factors like occlusion and view point variations make the activity recognition task challenging. This work proposes a... more
A Vision Based Patient Monitoring system focuses on detecting abnormal activities of a patient. In real-world, factors like occlusion and view point variations make the activity recognition task challenging. This work proposes a similarity-based representation for healthcare activities including abnormal patient activities such as coughing, sneezing, vomiting, falling, etc. Global and depth-based representations such as histogram of optical flow, displacement between skeletal sequences and relative position of skeletal joints are used to represent the spatio-temporal dynamics of activities. A benchmark data namely "NTU RGB + D Action Recognition dataset" is used for testing the performance of the proposed approach. A comparison of the proposed methodology against other state-of-the-art approaches has proved the discrimination of the proposed approach.
The recent increase in the number of diabetic cases due to genetic reasons or sedentary lifestyle, necessitates urgent need for an effective glucose monitoring system. Certainly, periodic glucose level monitoring in the blood will prevent... more
The recent increase in the number of diabetic cases due to genetic reasons or sedentary lifestyle, necessitates urgent need for an effective glucose monitoring system. Certainly, periodic glucose level monitoring in the blood will prevent from entering chronic diabetic condition and a noninvasive monitoring tool leads to a simple and automated diagnosis procedure. In this present work, an iridology-based diagnosis of diabetes has been discussed and is compared with a standard retinal imaging modality. Two subject groups, one group of 30 subjects without diabetes, the other group with 20 subjects of controlled diabetes with less than two years duration and 25 subjects with more than two years of uncontrolled diabetes were evaluated. Iris images are acquired using an iriscope and subsequently compared it with that of retinal spectral domain optical coherence tomography (SDOCT) images of the same subjects. The segmentation of the pancreas region in the iris images and the retinal layer...