Amjed Al-Fahoum - Academia.edu (original) (raw)
Papers by Amjed Al-Fahoum
Intelligence-Based Medicine
F1000Research
Background: The industrial transformation requires a speedy shift to financial digitization. One ... more Background: The industrial transformation requires a speedy shift to financial digitization. One of the needs for financial digitalization in the study of Islamic contracts and Islamic business law is the use of digital platforms with digital currencies. Regarding the merits and downsides of its Sharia restrictions and its halal certification, which is currently under discussion, digital currencies and perks have generated controversy in Jordan and other Islamic countries.Methods: This study intends to analyze the legal foundations of digital currency from Jordanian and Islamic legal perspectives. The descriptive-qualitative research approach was utilized, and data collection processes included documentation and a literature review. All legal possibilities that may be drawn from Islamic law in order to investigate the legality of digital currencies are explored further and used to obtain the conclusions of this study.Results: A review of Sharia reasons and consideration for the well...
Objectives: Current estimates cite more than 100,000 casualties from war in Syria, with 5,000 dea... more Objectives: Current estimates cite more than 100,000 casualties from war in Syria, with 5,000 deaths reported each month since the violence escalated in the summer of 2012. With up to 3,500 Syrians crossing the borders every day, the rate at which refugees have poured over Syria's southern border has outstripped the ability of the Jordanian government and the international community to ensure adequate access to health services for refugees living inside Zaatari, the main refugee camp, and those dispersed throughout Jordan. Study design: The purpose of our study is to explore refugees' attitudes towards health services (i.e. evaluation of the adequacy of health care services and the degree of their satisfaction by the services provided). Methods: This is a cross-sectional study. Data collection with the use of questionnaires took place from August 1 to October 30, 2013 in Irbid, Jordan. The questionnaires consisted of questions concerning demographic information (e.g. age, ge...
Medical & Biological Engineering & Computing, 1999
Automatic detection and classification of arrhythmias based on ECG signals are important to cardi... more Automatic detection and classification of arrhythmias based on ECG signals are important to cardiac-disease diagnostics. The ability of the ECG classifier to identify arrhythmias accurately is based on the development of robust techniques for both feature extraction and classification. A classifier is developed based on using wavelet transforms for extracting features and then using a radial basis function neural network (RBFNN) to classify the arrhythmia. Six energy descriptors are derived from the wavelet coefficients over a single-beat interval from the ECG signal. Nine different continuous and discrete wavelet transforms are considered for obtaining the feature vector. An RBFNN adapted to detect and classify life-threatening arrhythmias is then used to classify the feature vector. Classification results are based on 159 arrhythmia files obtained from three different sources. Classification results indicate the potential for wavelet based energy descriptors to distinguish the main features of the signal and thereby enhance the classification scheme. The RBFNN classifier appears to be well suited to classifying the arrhythmia, owing to the feature vectors' linear inseparability and tendency to cluster. Utilising the Daubechies wavelet transform, an overall correct classification of 97.5% is obtained, with 100% correct classification for both ventricular fibrillation and ventricular tachycardia.
The Open Medical Imaging Journal, 2013
In this paper, a combined Fractal and Wavelet (CFW) compression algorithm targeting x-ray angiogr... more In this paper, a combined Fractal and Wavelet (CFW) compression algorithm targeting x-ray angiogram images is proposed. Initially, the image is decomposed using wavelet transform. The smoothness of the low frequency part of the image appears as an approximation image with higher self similarities, therefore, it is coded using a fractal coding technique. However, the rest of the image is coded using an adaptive wavelet thresholding technique. This model is implemented and its performance is compared with best performances of the available published algorithms. A data set containing 1000 x-ray angiograms is used to study the performance of the algorithm. A minimum compression ratio of 30 with a peak signal to noise ratio (PSNR) of 36 dB and percent diameter stenosis deviation of (<0.2%) was achieved. Results demonstrate the effectiveness of the proposed technique in obtaining a diagnostic quality of reconstructed images at very low bit rates.
Computers, Materials & Continua
International journal emerging technology and advanced engineering, Dec 4, 2022
In this research, we developed an Autonomous UVC robot disinfection system suitable for a healthc... more In this research, we developed an Autonomous UVC robot disinfection system suitable for a healthcare setting. The effectiveness of cleaning with UVC light inspired the design of the robot. The experiment was designed to determine how long, how far, and how much energy would be required to prevent the germs from replicating and kill them as rapidly as possible. The UVC robot is lightweight and simple to move about. The ultraviolet-candelabra (UVC) lamp was used in its construction. UVC light kills bacteria and viruses by interfering with the way their DNA bases couple together. Our experiment involved shutting the UVC robot in a room and observing its behavior. The UVC robot is equipped with four 30W lights that can illuminate an entire room. Within 30 seconds after commencement, samples were placed 60 centimeters from the lights and left there for a time from 0 to 6 minutes. Killing 92% of the germs in 6 minutes is a strong indicator that the suggested approach works effectively. The low initial cost and relatively straightforward nature of the design suggest that it might eventually achieve its full potential.
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium... more Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG sign...
International Journal of Innovation and Learning, 2008
Knowledge-technology transfer is the core driver for national prosperity and enhancement of intel... more Knowledge-technology transfer is the core driver for national prosperity and enhancement of intellectual capitals. Jordan has taken major steps towards economic transformation from a traditional rhythm into a knowledge base motivated by the accelerative impact of Information and Communication Technology (ICT). In this context, Yarmouk University has developed dynamic programmes of ICT enrichment and adopted an innovative partnership model. This model represents an in-campus facility that works towards bridging the gap between academia and industry. It provides a rich internal collaborative environment that brings together business and technical faculties in the pursuit of projects with an objective to cultivate collaboration with industrial and business partners; update the knowledge base of the university with the latest industry developments; and align the skills and knowledge of students to real and immediate industry needs. This paper presents an innovative partnership model and...
Thesis (Ph. D. in Engineering)--University of Wisconsin--Milwaukee, 2001. Includes bibliographica... more Thesis (Ph. D. in Engineering)--University of Wisconsin--Milwaukee, 2001. Includes bibliographical references (leaves 220-235). Vita. Microfiche copy: University Microfilms No. 30-08769.
International Journal of Computer and Electrical Engineering, 2018
This paper presents a quaternion-based modified Madgwick filter for real-time estimation of rigid... more This paper presents a quaternion-based modified Madgwick filter for real-time estimation of rigid body orientations using attitude and heading reference system (AHRS). The filter consists of a cluster of a tri-axis accelerometer, a tri-axis magnetometer, and a tri-axis angular rate sensor. The proposed filter implementation incorporates gyroscope bias drift compensation. Additionally, an estimated magnetic reference along with low-pass filter are adopted to compensate for the magnetic perturbations. An optimized Levenberg-Marquardt (LM) algorithm is applied to the Whaba's problem to obtain the body orientations. The hessian matrix of the algorithm was analytically derived to reduce the numerical calculations cost. This algorithm ensures adaptive damped parameter for accurate and fast iterations. The filter performs the calculations of rotations using quaternions rather than Euler angles, which avoids the singularities issue associated with attitude estimation. The accelerometer and magnetometer are calibrated off-line prior to the data fusion process. The magnetometer calibration is made using the ellipsoid fitting technique. Experimental validation of the filter with the actual sensor data proved to be satisfactory. Testing cases included the presence of large dynamics and magnetic perturbation were carried out. In all situations the filter was found to converge and accurately track the rotational motions.
Computers, Materials & Continua
Applied Sciences
The films teenagers watch have a significant influence on their behavior. After witnessing a film... more The films teenagers watch have a significant influence on their behavior. After witnessing a film starring an actor with a particular social habit or personality trait, viewers, particularly youngsters, may attempt to adopt the actor’s behavior. This study proposes an algorithm-based technique for predicting the market potential of upcoming science fiction films. Numerous science fiction films are released annually, and working in the film industry is both profitable and delightful. Before the film’s release, it is necessary to conduct research and make informed predictions about its success. In this investigation, different machine learning methods written in MATLAB are examined to identify and forecast the future performance of movies. Using 14 methods for machine learning, it was feasible to predict how individuals would vote on science fiction films. Due to their superior performance, the fine, medium, and weighted KNN algorithms were given more consideration. In comparison to e...
International Journal of Modelling and Simulation, 2016
Abstract Radial gas turbine of 50-kW power output coupled directly to a high-speed permanent magn... more Abstract Radial gas turbine of 50-kW power output coupled directly to a high-speed permanent magnet alternator could be a favourable option as an emergency power plant at areas suffering from severe disasters, such as earthquakes, floods and volcanoes. This study aims to use the results of the subtractive clustering algorithm and the least square estimation method to generate a fuzzy model of the pre-designed radial gas turbine system whereby the fuzzy model takes the fuel mass flow rate as an input, and gives the value of the gas turbine net work Wnet as an output. In addition, a suitable controller of the fuel mass flow rate is designed and analysed so that the speed of the gas turbine and the alternator is maintained at 42,000 rpm. A proportional derivative fuzzy controller was built and tested. Results illustrate that the proposed controller achieves the desired performance and stability, and showed the effectiveness of the approach. Conclusions of this study will constitute a base for further studies that could be made to enhance the performance of the proposed emergency power plant system.
Engineering Science and Technology, an International Journal, 2019
Lumbar spine's lordosis is a very important parameter functionally and clinically; it is a key fe... more Lumbar spine's lordosis is a very important parameter functionally and clinically; it is a key feature in maintaining the sagittal balance, in addition to its crucial role in evaluating the spinal deformities. The main objective of the current study is to present a fully-automated measurement of the lumbar spine's lordotic curve angle in T2-MR images. This goal has been achieved by the automatic measurement of lordosis radius at the lumbar spine level by computer-aided methods utilizing data mining classification and image segmentation followed by morphological image processing. The spine has been segmented from the entire image using a machine-learning technique that is based on texture features for recognizing the lumbar-spine pattern. The extracted features were fed to C4.5 decision tree classifier for designing the lumbar-spine recognition system. The resultant classifier's ''if-then" rules have been employed for segmenting the spine region from the entire image. Multiple morphological image processes have been applied to the raw segmentation result to enhance the true positive rate and suppressing the false positive rate. The mean radius of lumbar spine's curvature has been evaluated by fitting the contours average to the closest circle using least-square fitting algorithm which was followed by calculating the lumbar lordosis curvature angle. The proposed approach has been tested and validated on normal and pathological T2-MR spine images and found to perform effectively. The calculation of lumbar lordosis angles showed a strong correlation with the Cobb angle measurements (R = 93.2%).
Reverse Data Hiding is a technique used to hide the object's data details. This technique is ... more Reverse Data Hiding is a technique used to hide the object's data details. This technique is used to ensure the security and to protect the integrity of the object from any modification by preventing intended and unintended changes. Digital watermarking is a key ingredient to multimedia protection. However, most existing techniques distort the original content as a side effect of image protection. As a way to overcome such distortion, reversible data embedding has recently been introduced and is growing rapidly. In reversible data embedding, the original content can be completely restored after the removal of the watermark. Therefore, it is very practical to protect legal, medical, or other important imagery. In this paper a novel removable (lossless) data hiding technique is proposed. This technique is based on the histogram modification to produce extra space for embedding, and the redundancy in digital images is exploited to achieve a very high embedding capacity. This method...
International Journal of Biomedical Engineering and Technology, 2015
In this paper, various spectral analysis methods are applied to investigate the spectral behaviou... more In this paper, various spectral analysis methods are applied to investigate the spectral behaviour of Photoplethysmography (PPG) signals for both healthy normal athletic and non–athletic subjects. The paper investigates the contribution of the PPG spectral components in revealing time trends and how they minimise artefacts that conceal these spectral contents. Both parametric and non–parametric spectral methods are utilised to study the PPG signal. However, eigenstructure methods such as multiple signal classification are found to be more suitable to localise spectral contents of the signal and robustly estimate the heart rate. The heart rate detection correlation is found to be 99.62% and the PPG detection accuracy is 99.61%. These findings show that PPG can be used as an effective tool in investigating cardiovascular disorders as well rather than in investigating only blood oxygenation and heart rate measurements. Furthermore, it can advance the research for existing heart rate variability methods.
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
ABSTRACT Ventricular tachyarrhythmias, in particular ventricular fibrillation (VF), are the prima... more ABSTRACT Ventricular tachyarrhythmias, in particular ventricular fibrillation (VF), are the primary arrhythmic events in the majority of patients suffering from sudden cardiac death. Attention has focused upon these articular rhythms as it is recognized that prompt therapy can lead to a successful outcome. There has been considerable interest in analysis of the surface electrocardiogram (ECG) in VF centred on attempts to understand the pathophysiological processes occurring in sudden cardiac death, predicting the efficacy of therapy, and guiding the use of alternative or adjunct therapies to improve resuscitation success rates. Atrial fibrillation (AF) and ventricular tachycardia (VT) are other types of tachyarrhythmias that constitute a medical challenge. In this paper, a high order spectral analysis technique is suggested for quantitative analysis and classification of cardiac arrhythmias. The algorithm is based upon bispectral analysis techniques. The bispectrum is estimated using an AR model, and the frequency support of the bispectrum is extracted as a quantitative measure to classify atrial and ventricular tachyarrhythmias. Results show a significant difference in the parameter values for different arrhythmias. Moreover, the bicoherency spectrum shows different bicoherency values for normal and tachycardia patients. In particular, the bicoherency indicates that phase coupling decreases as arrhythmia kicks in.
ISRN Neuroscience, 2014
Technically, a feature represents a distinguishing property, a recognizable measurement, and a fu... more Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG signal has been the subject of several studies, because of its ability to yield an objective mode of recording brain stimulation which is widely used...
Intelligence-Based Medicine
F1000Research
Background: The industrial transformation requires a speedy shift to financial digitization. One ... more Background: The industrial transformation requires a speedy shift to financial digitization. One of the needs for financial digitalization in the study of Islamic contracts and Islamic business law is the use of digital platforms with digital currencies. Regarding the merits and downsides of its Sharia restrictions and its halal certification, which is currently under discussion, digital currencies and perks have generated controversy in Jordan and other Islamic countries.Methods: This study intends to analyze the legal foundations of digital currency from Jordanian and Islamic legal perspectives. The descriptive-qualitative research approach was utilized, and data collection processes included documentation and a literature review. All legal possibilities that may be drawn from Islamic law in order to investigate the legality of digital currencies are explored further and used to obtain the conclusions of this study.Results: A review of Sharia reasons and consideration for the well...
Objectives: Current estimates cite more than 100,000 casualties from war in Syria, with 5,000 dea... more Objectives: Current estimates cite more than 100,000 casualties from war in Syria, with 5,000 deaths reported each month since the violence escalated in the summer of 2012. With up to 3,500 Syrians crossing the borders every day, the rate at which refugees have poured over Syria's southern border has outstripped the ability of the Jordanian government and the international community to ensure adequate access to health services for refugees living inside Zaatari, the main refugee camp, and those dispersed throughout Jordan. Study design: The purpose of our study is to explore refugees' attitudes towards health services (i.e. evaluation of the adequacy of health care services and the degree of their satisfaction by the services provided). Methods: This is a cross-sectional study. Data collection with the use of questionnaires took place from August 1 to October 30, 2013 in Irbid, Jordan. The questionnaires consisted of questions concerning demographic information (e.g. age, ge...
Medical & Biological Engineering & Computing, 1999
Automatic detection and classification of arrhythmias based on ECG signals are important to cardi... more Automatic detection and classification of arrhythmias based on ECG signals are important to cardiac-disease diagnostics. The ability of the ECG classifier to identify arrhythmias accurately is based on the development of robust techniques for both feature extraction and classification. A classifier is developed based on using wavelet transforms for extracting features and then using a radial basis function neural network (RBFNN) to classify the arrhythmia. Six energy descriptors are derived from the wavelet coefficients over a single-beat interval from the ECG signal. Nine different continuous and discrete wavelet transforms are considered for obtaining the feature vector. An RBFNN adapted to detect and classify life-threatening arrhythmias is then used to classify the feature vector. Classification results are based on 159 arrhythmia files obtained from three different sources. Classification results indicate the potential for wavelet based energy descriptors to distinguish the main features of the signal and thereby enhance the classification scheme. The RBFNN classifier appears to be well suited to classifying the arrhythmia, owing to the feature vectors' linear inseparability and tendency to cluster. Utilising the Daubechies wavelet transform, an overall correct classification of 97.5% is obtained, with 100% correct classification for both ventricular fibrillation and ventricular tachycardia.
The Open Medical Imaging Journal, 2013
In this paper, a combined Fractal and Wavelet (CFW) compression algorithm targeting x-ray angiogr... more In this paper, a combined Fractal and Wavelet (CFW) compression algorithm targeting x-ray angiogram images is proposed. Initially, the image is decomposed using wavelet transform. The smoothness of the low frequency part of the image appears as an approximation image with higher self similarities, therefore, it is coded using a fractal coding technique. However, the rest of the image is coded using an adaptive wavelet thresholding technique. This model is implemented and its performance is compared with best performances of the available published algorithms. A data set containing 1000 x-ray angiograms is used to study the performance of the algorithm. A minimum compression ratio of 30 with a peak signal to noise ratio (PSNR) of 36 dB and percent diameter stenosis deviation of (<0.2%) was achieved. Results demonstrate the effectiveness of the proposed technique in obtaining a diagnostic quality of reconstructed images at very low bit rates.
Computers, Materials & Continua
International journal emerging technology and advanced engineering, Dec 4, 2022
In this research, we developed an Autonomous UVC robot disinfection system suitable for a healthc... more In this research, we developed an Autonomous UVC robot disinfection system suitable for a healthcare setting. The effectiveness of cleaning with UVC light inspired the design of the robot. The experiment was designed to determine how long, how far, and how much energy would be required to prevent the germs from replicating and kill them as rapidly as possible. The UVC robot is lightweight and simple to move about. The ultraviolet-candelabra (UVC) lamp was used in its construction. UVC light kills bacteria and viruses by interfering with the way their DNA bases couple together. Our experiment involved shutting the UVC robot in a room and observing its behavior. The UVC robot is equipped with four 30W lights that can illuminate an entire room. Within 30 seconds after commencement, samples were placed 60 centimeters from the lights and left there for a time from 0 to 6 minutes. Killing 92% of the germs in 6 minutes is a strong indicator that the suggested approach works effectively. The low initial cost and relatively straightforward nature of the design suggest that it might eventually achieve its full potential.
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium... more Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG sign...
International Journal of Innovation and Learning, 2008
Knowledge-technology transfer is the core driver for national prosperity and enhancement of intel... more Knowledge-technology transfer is the core driver for national prosperity and enhancement of intellectual capitals. Jordan has taken major steps towards economic transformation from a traditional rhythm into a knowledge base motivated by the accelerative impact of Information and Communication Technology (ICT). In this context, Yarmouk University has developed dynamic programmes of ICT enrichment and adopted an innovative partnership model. This model represents an in-campus facility that works towards bridging the gap between academia and industry. It provides a rich internal collaborative environment that brings together business and technical faculties in the pursuit of projects with an objective to cultivate collaboration with industrial and business partners; update the knowledge base of the university with the latest industry developments; and align the skills and knowledge of students to real and immediate industry needs. This paper presents an innovative partnership model and...
Thesis (Ph. D. in Engineering)--University of Wisconsin--Milwaukee, 2001. Includes bibliographica... more Thesis (Ph. D. in Engineering)--University of Wisconsin--Milwaukee, 2001. Includes bibliographical references (leaves 220-235). Vita. Microfiche copy: University Microfilms No. 30-08769.
International Journal of Computer and Electrical Engineering, 2018
This paper presents a quaternion-based modified Madgwick filter for real-time estimation of rigid... more This paper presents a quaternion-based modified Madgwick filter for real-time estimation of rigid body orientations using attitude and heading reference system (AHRS). The filter consists of a cluster of a tri-axis accelerometer, a tri-axis magnetometer, and a tri-axis angular rate sensor. The proposed filter implementation incorporates gyroscope bias drift compensation. Additionally, an estimated magnetic reference along with low-pass filter are adopted to compensate for the magnetic perturbations. An optimized Levenberg-Marquardt (LM) algorithm is applied to the Whaba's problem to obtain the body orientations. The hessian matrix of the algorithm was analytically derived to reduce the numerical calculations cost. This algorithm ensures adaptive damped parameter for accurate and fast iterations. The filter performs the calculations of rotations using quaternions rather than Euler angles, which avoids the singularities issue associated with attitude estimation. The accelerometer and magnetometer are calibrated off-line prior to the data fusion process. The magnetometer calibration is made using the ellipsoid fitting technique. Experimental validation of the filter with the actual sensor data proved to be satisfactory. Testing cases included the presence of large dynamics and magnetic perturbation were carried out. In all situations the filter was found to converge and accurately track the rotational motions.
Computers, Materials & Continua
Applied Sciences
The films teenagers watch have a significant influence on their behavior. After witnessing a film... more The films teenagers watch have a significant influence on their behavior. After witnessing a film starring an actor with a particular social habit or personality trait, viewers, particularly youngsters, may attempt to adopt the actor’s behavior. This study proposes an algorithm-based technique for predicting the market potential of upcoming science fiction films. Numerous science fiction films are released annually, and working in the film industry is both profitable and delightful. Before the film’s release, it is necessary to conduct research and make informed predictions about its success. In this investigation, different machine learning methods written in MATLAB are examined to identify and forecast the future performance of movies. Using 14 methods for machine learning, it was feasible to predict how individuals would vote on science fiction films. Due to their superior performance, the fine, medium, and weighted KNN algorithms were given more consideration. In comparison to e...
International Journal of Modelling and Simulation, 2016
Abstract Radial gas turbine of 50-kW power output coupled directly to a high-speed permanent magn... more Abstract Radial gas turbine of 50-kW power output coupled directly to a high-speed permanent magnet alternator could be a favourable option as an emergency power plant at areas suffering from severe disasters, such as earthquakes, floods and volcanoes. This study aims to use the results of the subtractive clustering algorithm and the least square estimation method to generate a fuzzy model of the pre-designed radial gas turbine system whereby the fuzzy model takes the fuel mass flow rate as an input, and gives the value of the gas turbine net work Wnet as an output. In addition, a suitable controller of the fuel mass flow rate is designed and analysed so that the speed of the gas turbine and the alternator is maintained at 42,000 rpm. A proportional derivative fuzzy controller was built and tested. Results illustrate that the proposed controller achieves the desired performance and stability, and showed the effectiveness of the approach. Conclusions of this study will constitute a base for further studies that could be made to enhance the performance of the proposed emergency power plant system.
Engineering Science and Technology, an International Journal, 2019
Lumbar spine's lordosis is a very important parameter functionally and clinically; it is a key fe... more Lumbar spine's lordosis is a very important parameter functionally and clinically; it is a key feature in maintaining the sagittal balance, in addition to its crucial role in evaluating the spinal deformities. The main objective of the current study is to present a fully-automated measurement of the lumbar spine's lordotic curve angle in T2-MR images. This goal has been achieved by the automatic measurement of lordosis radius at the lumbar spine level by computer-aided methods utilizing data mining classification and image segmentation followed by morphological image processing. The spine has been segmented from the entire image using a machine-learning technique that is based on texture features for recognizing the lumbar-spine pattern. The extracted features were fed to C4.5 decision tree classifier for designing the lumbar-spine recognition system. The resultant classifier's ''if-then" rules have been employed for segmenting the spine region from the entire image. Multiple morphological image processes have been applied to the raw segmentation result to enhance the true positive rate and suppressing the false positive rate. The mean radius of lumbar spine's curvature has been evaluated by fitting the contours average to the closest circle using least-square fitting algorithm which was followed by calculating the lumbar lordosis curvature angle. The proposed approach has been tested and validated on normal and pathological T2-MR spine images and found to perform effectively. The calculation of lumbar lordosis angles showed a strong correlation with the Cobb angle measurements (R = 93.2%).
Reverse Data Hiding is a technique used to hide the object's data details. This technique is ... more Reverse Data Hiding is a technique used to hide the object's data details. This technique is used to ensure the security and to protect the integrity of the object from any modification by preventing intended and unintended changes. Digital watermarking is a key ingredient to multimedia protection. However, most existing techniques distort the original content as a side effect of image protection. As a way to overcome such distortion, reversible data embedding has recently been introduced and is growing rapidly. In reversible data embedding, the original content can be completely restored after the removal of the watermark. Therefore, it is very practical to protect legal, medical, or other important imagery. In this paper a novel removable (lossless) data hiding technique is proposed. This technique is based on the histogram modification to produce extra space for embedding, and the redundancy in digital images is exploited to achieve a very high embedding capacity. This method...
International Journal of Biomedical Engineering and Technology, 2015
In this paper, various spectral analysis methods are applied to investigate the spectral behaviou... more In this paper, various spectral analysis methods are applied to investigate the spectral behaviour of Photoplethysmography (PPG) signals for both healthy normal athletic and non–athletic subjects. The paper investigates the contribution of the PPG spectral components in revealing time trends and how they minimise artefacts that conceal these spectral contents. Both parametric and non–parametric spectral methods are utilised to study the PPG signal. However, eigenstructure methods such as multiple signal classification are found to be more suitable to localise spectral contents of the signal and robustly estimate the heart rate. The heart rate detection correlation is found to be 99.62% and the PPG detection accuracy is 99.61%. These findings show that PPG can be used as an effective tool in investigating cardiovascular disorders as well rather than in investigating only blood oxygenation and heart rate measurements. Furthermore, it can advance the research for existing heart rate variability methods.
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
ABSTRACT Ventricular tachyarrhythmias, in particular ventricular fibrillation (VF), are the prima... more ABSTRACT Ventricular tachyarrhythmias, in particular ventricular fibrillation (VF), are the primary arrhythmic events in the majority of patients suffering from sudden cardiac death. Attention has focused upon these articular rhythms as it is recognized that prompt therapy can lead to a successful outcome. There has been considerable interest in analysis of the surface electrocardiogram (ECG) in VF centred on attempts to understand the pathophysiological processes occurring in sudden cardiac death, predicting the efficacy of therapy, and guiding the use of alternative or adjunct therapies to improve resuscitation success rates. Atrial fibrillation (AF) and ventricular tachycardia (VT) are other types of tachyarrhythmias that constitute a medical challenge. In this paper, a high order spectral analysis technique is suggested for quantitative analysis and classification of cardiac arrhythmias. The algorithm is based upon bispectral analysis techniques. The bispectrum is estimated using an AR model, and the frequency support of the bispectrum is extracted as a quantitative measure to classify atrial and ventricular tachyarrhythmias. Results show a significant difference in the parameter values for different arrhythmias. Moreover, the bicoherency spectrum shows different bicoherency values for normal and tachycardia patients. In particular, the bicoherency indicates that phase coupling decreases as arrhythmia kicks in.
ISRN Neuroscience, 2014
Technically, a feature represents a distinguishing property, a recognizable measurement, and a fu... more Technically, a feature represents a distinguishing property, a recognizable measurement, and a functional component obtained from a section of a pattern. Extracted features are meant to minimize the loss of important information embedded in the signal. In addition, they also simplify the amount of resources needed to describe a huge set of data accurately. This is necessary to minimize the complexity of implementation, to reduce the cost of information processing, and to cancel the potential need to compress the information. More recently, a variety of methods have been widely used to extract the features from EEG signals, among these methods are time frequency distributions (TFD), fast fourier transform (FFT), eigenvector methods (EM), wavelet transform (WT), and auto regressive method (ARM), and so on. In general, the analysis of EEG signal has been the subject of several studies, because of its ability to yield an objective mode of recording brain stimulation which is widely used...