International Journal of Advanced Computer Science and Applications, 2022
The development of big data in the era of data explosion and the growing demand for micro-servers... more The development of big data in the era of data explosion and the growing demand for micro-servers in place of traditional servers to adapt to lightweight tasks in recent years has put into question how to integrate and make use of these two important domains. During the same era, CPU performance growth has reached a certain maturity. In order to surpass these issues and to reach high performances computing, a new trend now is to use multiple processing units or heterogeneous components in micro-servers to reduce computational complexity. The implementation of Big Data processing algorithms using embedded heterogeneous architectures rises a new challenges due to constraints of the used architecture-based system on chip which require a special attention and imposed new demands to our works. In this article, we focus on using embedded FPGA accelerator to give a solution to this problem. Precisely, we will attempt to prototype a micro-server for the processing of big data on FPGA and compare its performances with a high-end GPGPU using existing benchmarks. The implementation on the FPGA is done using a High-Level Synthesis based-OpenCL (HLS) instead of the traditional description language. The obtained results shows that FPGA is an interesting alternative and can be a promising platform to design a micro-server when it comes to process a hug amount of data, in particular with the emerging technologies for FPGA programming using HLS approach and by adopting the OpenCL optimization strategies.
Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applicatio... more Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applications and autonomous navigation systems. The FastSLAM2.0 addresses an issue of the SLAM problem and allows a robot to navigate in an unknown environment. Several works have presented many algorithmic optimizations to reduce the computational complexity of such algorithm. In this paper, a GPGPU (general-purpose computing on graphics processing units) is exploited to achieve a parallel implementation of the FastSLAM2.0. The GPGPU acceleration is done using two different implementations for parallel programming. The first implementation used OpenGL shading language which is based on the characteristics of graphics hardwares. The second implementation used OpenCL which allows hardware acceleration across heterogeneous architectures. We also explored the impact of the two approaches on the the resulting GPGPU implementation. A comparison related to processing-time and localization accuracy is ma...
2020 6th IEEE Congress on Information Science and Technology (CiSt), 2020
The monitoring of vital signs is essential in the clinical setting, including temperature, respir... more The monitoring of vital signs is essential in the clinical setting, including temperature, respiratory, and heart rates. Remote monitoring devices, systems, and services are emerging as vital signs monitoring must be performed daily. Different types of sensors can be used to monitor breathing patterns and frequency. However, the respiratory rate remains the least measured vital sign in many scenarios due to the intrusiveness of most of the sensors adopted. This is not the case with Covid-19, which directly infects the respiratory system. In this paper, we present a state of the art on the different applications that monitor temperature, heart rate, and restorative rate, as well as the evaluation of an algorithm that extracts the heart rate from an RGB camera.
This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid a... more This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.
The integration of low-cost systems in precision agriculture applications has shown great benefit... more The integration of low-cost systems in precision agriculture applications has shown great benefits, both in terms of the variety of applications and the tools used. In this paper, we present a monitoring platform for agricultural applications based on low-cost systems—also, a review on the different applications of precision agriculture. The proposed platform contains a guidance system based on stepper motors, as well as an embedded architecture for processing the various applications. The guidance system helps to drive the system in the vertical axis for multispectral camera processing. The guidance system helps to move the system in the vertical axis for processing multispectral cameras and in the horizontal axis for the movement of the two bars that will support the system. This platform was inspired by the principle of the scanner, which aims to extract all the information by sliding the scan tool. In the same way, in our case, the sliding will allow us to process the whole agri...
Practical Applications of Electrocardiogram [Working Title]
The electrocardiogram (ECG) signal is a fundamental tool for patient treatment, especially in the... more The electrocardiogram (ECG) signal is a fundamental tool for patient treatment, especially in the cardiology domain, due to the high mortality rate of heart diseases. The main objective of this paper is to present the most optimal techniques that can link the processing and analysis of ECG signals. This work is divided into two steps. In the first one, we propose a comparison between some denoising techniques that can reduce noise affecting the ECG signals; these techniques are the empirical mode decomposition (EMD), the ensemble empirical mode decomposition (EEMD), and the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). In the second one, we make a comparison of three time-frequency techniques: the Choi-Williams (CW), the periodogram (PE), and the smoothed pseudo Wigner-Ville (SPWV). Firstly, the obtained results illustrate the effectiveness of the CEEMDAN in reducing noise that interferes with ECG signals compared to other denoising methods. Secondly, they show that the periodogram time-frequency technique gives a good detection and localization of the main components in the time-frequency plan of ECG signals. This work proves the utility of the combination of the periodogram and CEEMDAN techniques in analyzing the ECG signals.
Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitiv... more Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet ...
The storage capacity of the ECG records presents an important issue in the medical practices. The... more The storage capacity of the ECG records presents an important issue in the medical practices. These data could contain hours of recording, which needs a large space for storage to save these records. The compression of the ECG signal is widely used to deal with this issue. The problem with this process is the possibility of losing some important features of the ECG signal. This loss could influence negatively the analyzing of the heart condition. In this paper, we shall propose an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding. This method is based on the decomposition of the ECG signal, the thresholding stage and the encoding of the final data. This method is tested on some of the MIT-BIH arrhythmia signals from the international database Physionet. This method shows high performances comparing to other methods recently published.
International Journal of Computer Applications, Aug 23, 2013
IWBSN (Implantable Wireless Body Sensor Network) becomes nowadays an important area of research i... more IWBSN (Implantable Wireless Body Sensor Network) becomes nowadays an important area of research in computer science and healthcare application industries for improving the quality of life. Communication with implanted medical devices is considered as a key to effective diagnosis and therapy. These biosensors are implanted inside the patient body to measure body temperature and blood pressure, respiration rate, blood pressure and other physiological parameters. The purpose of this paper is to provide an enhanced version of TBCD communication protocol (Time Based Coded Data) for implantable sensor networks in order to guarantee an ultra-low energy consumption in the very tiny battery of the biosensors, and hence increasing the network lifetime for longer periods of time.
Wireless Body Area Networks (WBAN) also referred to as a body sensor network (BSN), is a wireless... more Wireless Body Area Networks (WBAN) also referred to as a body sensor network (BSN), is a wireless network of wearable computing devices. It has emerged as a key technology to provide real-time health monitoring of a patient and diagnose many life threatening diseases. WBAN operates in close vicinity to, on, or inside a human body and supports a variety of medical and non-medical applications. The design of a medium access control is a challenge due to the characteristics of wireless channel and the need to fulfill both requirements of mobility support and energy efficiency. This paper presents a comparative study of IEEE 802.15.6, IEEE 804.15.4 and T-MAC in order to analyze the performance of each standard in terms of delay, throughput and energy consumption.
International Journal of Advanced Computer Science and Applications, 2022
The development of big data in the era of data explosion and the growing demand for micro-servers... more The development of big data in the era of data explosion and the growing demand for micro-servers in place of traditional servers to adapt to lightweight tasks in recent years has put into question how to integrate and make use of these two important domains. During the same era, CPU performance growth has reached a certain maturity. In order to surpass these issues and to reach high performances computing, a new trend now is to use multiple processing units or heterogeneous components in micro-servers to reduce computational complexity. The implementation of Big Data processing algorithms using embedded heterogeneous architectures rises a new challenges due to constraints of the used architecture-based system on chip which require a special attention and imposed new demands to our works. In this article, we focus on using embedded FPGA accelerator to give a solution to this problem. Precisely, we will attempt to prototype a micro-server for the processing of big data on FPGA and compare its performances with a high-end GPGPU using existing benchmarks. The implementation on the FPGA is done using a High-Level Synthesis based-OpenCL (HLS) instead of the traditional description language. The obtained results shows that FPGA is an interesting alternative and can be a promising platform to design a micro-server when it comes to process a hug amount of data, in particular with the emerging technologies for FPGA programming using HLS approach and by adopting the OpenCL optimization strategies.
Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applicatio... more Simultaneous Localization And Mapping (SLAM) algorithms are being used in many robotic applications and autonomous navigation systems. The FastSLAM2.0 addresses an issue of the SLAM problem and allows a robot to navigate in an unknown environment. Several works have presented many algorithmic optimizations to reduce the computational complexity of such algorithm. In this paper, a GPGPU (general-purpose computing on graphics processing units) is exploited to achieve a parallel implementation of the FastSLAM2.0. The GPGPU acceleration is done using two different implementations for parallel programming. The first implementation used OpenGL shading language which is based on the characteristics of graphics hardwares. The second implementation used OpenCL which allows hardware acceleration across heterogeneous architectures. We also explored the impact of the two approaches on the the resulting GPGPU implementation. A comparison related to processing-time and localization accuracy is ma...
2020 6th IEEE Congress on Information Science and Technology (CiSt), 2020
The monitoring of vital signs is essential in the clinical setting, including temperature, respir... more The monitoring of vital signs is essential in the clinical setting, including temperature, respiratory, and heart rates. Remote monitoring devices, systems, and services are emerging as vital signs monitoring must be performed daily. Different types of sensors can be used to monitor breathing patterns and frequency. However, the respiratory rate remains the least measured vital sign in many scenarios due to the intrusiveness of most of the sensors adopted. This is not the case with Covid-19, which directly infects the respiratory system. In this paper, we present a state of the art on the different applications that monitor temperature, heart rate, and restorative rate, as well as the evaluation of an algorithm that extracts the heart rate from an RGB camera.
This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid a... more This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.
The integration of low-cost systems in precision agriculture applications has shown great benefit... more The integration of low-cost systems in precision agriculture applications has shown great benefits, both in terms of the variety of applications and the tools used. In this paper, we present a monitoring platform for agricultural applications based on low-cost systems—also, a review on the different applications of precision agriculture. The proposed platform contains a guidance system based on stepper motors, as well as an embedded architecture for processing the various applications. The guidance system helps to drive the system in the vertical axis for multispectral camera processing. The guidance system helps to move the system in the vertical axis for processing multispectral cameras and in the horizontal axis for the movement of the two bars that will support the system. This platform was inspired by the principle of the scanner, which aims to extract all the information by sliding the scan tool. In the same way, in our case, the sliding will allow us to process the whole agri...
Practical Applications of Electrocardiogram [Working Title]
The electrocardiogram (ECG) signal is a fundamental tool for patient treatment, especially in the... more The electrocardiogram (ECG) signal is a fundamental tool for patient treatment, especially in the cardiology domain, due to the high mortality rate of heart diseases. The main objective of this paper is to present the most optimal techniques that can link the processing and analysis of ECG signals. This work is divided into two steps. In the first one, we propose a comparison between some denoising techniques that can reduce noise affecting the ECG signals; these techniques are the empirical mode decomposition (EMD), the ensemble empirical mode decomposition (EEMD), and the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). In the second one, we make a comparison of three time-frequency techniques: the Choi-Williams (CW), the periodogram (PE), and the smoothed pseudo Wigner-Ville (SPWV). Firstly, the obtained results illustrate the effectiveness of the CEEMDAN in reducing noise that interferes with ECG signals compared to other denoising methods. Secondly, they show that the periodogram time-frequency technique gives a good detection and localization of the main components in the time-frequency plan of ECG signals. This work proves the utility of the combination of the periodogram and CEEMDAN techniques in analyzing the ECG signals.
Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitiv... more Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician's correct decision on patients. The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet ...
The storage capacity of the ECG records presents an important issue in the medical practices. The... more The storage capacity of the ECG records presents an important issue in the medical practices. These data could contain hours of recording, which needs a large space for storage to save these records. The compression of the ECG signal is widely used to deal with this issue. The problem with this process is the possibility of losing some important features of the ECG signal. This loss could influence negatively the analyzing of the heart condition. In this paper, we shall propose an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding. This method is based on the decomposition of the ECG signal, the thresholding stage and the encoding of the final data. This method is tested on some of the MIT-BIH arrhythmia signals from the international database Physionet. This method shows high performances comparing to other methods recently published.
International Journal of Computer Applications, Aug 23, 2013
IWBSN (Implantable Wireless Body Sensor Network) becomes nowadays an important area of research i... more IWBSN (Implantable Wireless Body Sensor Network) becomes nowadays an important area of research in computer science and healthcare application industries for improving the quality of life. Communication with implanted medical devices is considered as a key to effective diagnosis and therapy. These biosensors are implanted inside the patient body to measure body temperature and blood pressure, respiration rate, blood pressure and other physiological parameters. The purpose of this paper is to provide an enhanced version of TBCD communication protocol (Time Based Coded Data) for implantable sensor networks in order to guarantee an ultra-low energy consumption in the very tiny battery of the biosensors, and hence increasing the network lifetime for longer periods of time.
Wireless Body Area Networks (WBAN) also referred to as a body sensor network (BSN), is a wireless... more Wireless Body Area Networks (WBAN) also referred to as a body sensor network (BSN), is a wireless network of wearable computing devices. It has emerged as a key technology to provide real-time health monitoring of a patient and diagnose many life threatening diseases. WBAN operates in close vicinity to, on, or inside a human body and supports a variety of medical and non-medical applications. The design of a medium access control is a challenge due to the characteristics of wireless channel and the need to fulfill both requirements of mobility support and energy efficiency. This paper presents a comparative study of IEEE 802.15.6, IEEE 804.15.4 and T-MAC in order to analyze the performance of each standard in terms of delay, throughput and energy consumption.
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