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Novel Approach of a Smart Medical Mirror system for Medical Applications 5

Novel Approach of a Smart Medical Mirror System for Medical ...

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5th IEEE Middle East and Africa Conference on Biomedical Engineering, MECBME 2020

作者： Halaby, Shady Khoury, George Zeid Daou, Roy Abi Hayek, Ali Boercsoek, Josef Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon Lebanese German University Biomedical Technologies Department Jounieh Lebanon University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany University of Kassel Faculty of Electrical Engineering/Computer Science Department of Computer Architecture and System Programming Germany

ISBN: (纸本)9781728123585

Humans always face problems when it comes to medical check-up due to lack of time or laziness. However, lots of medical problems and fatal illnesses can be detected at earlier stages if the person is subject to continuous check-up. Hence, the idea of the proposed system is to design a tool enabling the measurement of the basic vital signs with the smallest effort possible from the person's side. Thus, this paper proposes a smart medical mirror system that acts as a normal mirror and also delivers the basic vital signs of the user such as the heart rate, SPO2, body temperature, and Body Mass Index (BMI). The system takes five seconds for initialization and starts the measurements and displays the results. The user will not lose time as this check-up can be performed every morning while the person is wearing his clothes and getting ready to start his daily activities. The system was tested by multiple users having different body statuses. The recorded values showed very small differences with the exact ones. At the end, the system was able to meet the user specifications concerning its portability, sensitivity, accuracy and, most importantly, its low cost. © 2020 IEEE.

关键词： Mirrors

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Comparative Study for Classification Methods to Predict and Detect Epilepsy Seizure 5

Comparative Study for Classification Methods to Predict and ...

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5th IEEE Middle East and Africa Conference on Biomedical Engineering, MECBME 2020

作者： El Halabi, Nashaat Abi Zeid Daou, Roy Achkar, Roger Hayek, Ali Boercsoek, Josef American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon American University of Science and Technology Department of Computer and Communications Engineering Faculty of Engineering Beirut Lebanon Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany Computer Science University of Kassel Department of Computer Architecture and System Programming Faculty of Electrical Engineering Germany

ISBN: (纸本)9781728123585

Epilepsy is a medical problem that tackles lots of patients. It limits the life activity of such patients due to the seizures that occur anytime and anywhere. Thus, creating a monitoring system that could make their life easier and allow them to perform daily life activities as safe as possible has been studied. This paper is a continuity for a project where a system monitors epileptic patients using a set of wearable sensors connected to several processing units, the main sensors are Electroencephalogram (EEG) for the electrical activity of the brain, electrocardiogram (ECG) for the electrical activity of the heart, and accelerometers to monitor the posture of the patient, features extracted from EEG and ECG signals are used for prediction/detection of seizures. Thus, the objective of this paper is to present a comparative study in order to choose the appropriate classification method for seizure prediction and detection. Five classification methods were studied: Decision Trees, Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Ensemble Learning. For each of the classification methods, the accuracy, the specificity, the sensitivity, the precision, the false detection rate and the Fmeasure were studied and compared. The results for seizure prediction system show that the highest accuracy, specificity and F-Measure, and lowest false detection rate were achieved with Bagged Trees Ensemble Learning, the highest sensitivity and precision were achieved with Quadratic Support Vector Machine. However, for seizure detection system, the highest accuracy and F-Measure were achieved with Linear Support Vector, the highest sensitivity and specificity were achieved with Fine Gaussian Support Vector Machine, and the highest precision and lowest false detection rate were achieved with Subspace Discriminant Ensemble Learning. © 2020 IEEE.

关键词： Support vector machines

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Design and Implementation of a QoL Improvement system for Visually Impaired Patients

Design and Implementation of a QoL Improvement System for Vi...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Roy Abi Zeid Daou Jad Beaino Johnny Hawat Ramy Ibrahim Ali Hayek Josef Boercsoek Jose Javier Serrano Olmedo Mechatronics department Faculty of Engineering Université La Sagesse Beirut Lebanon MART Learning Education and Research Center Chananir Lebanon Department Lippstadt 2 Hardware Engineering University of Applied Science Hamm-Lippstadt Hamm Department of Computer Architecture and System Programming Faculty of Electrical Engineering/Computer Science University of Kassel Germany Lab of Bioinstrumentation and Nanomedicine Centro de Tecnología Biomédica Universidad Politécnica de Madrid Spain

Visually impaired people encounter several challenges in their mobility and navigation. Their daily activities are obstructed due to their inability to adapt or recognize accurately their surroundings, especially outside their house which they are more familiar with. Thus, it becomes the main reason of accidents, falling off, getting lost in unknown areas, etc. Furthermore, one of the sensory systems that helps the body to process data about the external environment is the visual system. Blind people also lose touch with the outside world, develops poor motor habits, which results in postural problems as a result. This project will assist visually impaired people in their daily life and simplify normal tasks through a system combining two previously designed projects, “Smart Shoes for Blind and Visually Impaired People”, and “Human posture monitoring device”. The multifunctional system is developed with the goal of securing safe movements for visually impaired people as well as maintaining a good back posture by detecting leaning postures (LP). The purpose of the smart shoe is to identify obstacles and protect the user from unintended accidents. A compatible Android application has been developed to alert the user when there is an obstruction or when he is walking on a wet surface. Voice alarms will be used to acoustically alert the user. If the user collapses, a message with their position will be sent right away to a relative. On the other hand, the smart vest will identify the position of the user's back and alert him to maintain a straight posture through the same application as well. As the system is dealing with human health, some safety measurements would be taken into consideration to implement a safe electrical system in order to reduce error and to increase accuracy.

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest

Design and Implementation of a Smart Human Posture Monitorin...

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International Conference on Advances in Biomedical Engineering (ICABME)

作者： Roy Abi Zeid Daou Elio Geha Youssef Aoun Ali Hayek Josef Boercsoek Jose Javier Serrano Olmedo Biomedical Engineering department Furn El Chebbak Université La Sagesse Beirut Lebanon Education and Research Center MART Learning Chananir Lebanon Biomedical Technologies Department Faculty of Public Health Lebanese German University Jounieh Lebanon Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 University of Applied Science Hamm-Lippstadt Hamm Department of Computer Architecture and System Programming Faculty of Electrical Engineering /Computer Science University of Kassel Germany Lab of Bioinstrumentation and Nanomedicine Centro de Tecnologia Biomedica Universidad Politecnica de Madrid Spain

Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. This research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. The vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. This box also displays the daily count of instances where the user has leaned. This system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. The results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. The accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant.

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Designing and validating a cost effective safe network: application to a PACS system

Designing and validating a cost effective safe network: appl...

引用

International Conference on Advances in Biomedical Engineering (ICABME)

作者： Georges EL HAJAL Roy ABI ZEID DAOU Yves DUCQ Josef Börcsök IMS laboratory Univ. Bordeaux Talence France Faculty of Public Health Lebanese German University Institute for Computer Architecture and System Programming University of Kassel 34121 Kassel Germany

Network security has been a major issue long time ago. Confidentiality, integrity and availability of data are the primary concerns of any network administrator. Recently, several attacks have resulted in huge losses of resources and of data availability. For example, in May 2017, medical entities in the United Kingdom have been paralyzed due to WannaCry ransomware world-wide cyber-attack. Thus, the main objective of this paper is to propose a more secured network architecture that will be designed for the case of the PACS - Picture Archiving and Communication system - that is used for storing and transmitting radiography images and reports through the hospital internal network. This paper presents an off-the-shelf solution based on the concept of one-way link data diode and open source softwares to assure safety and security in a cost effective manner. The novelty of this approach is in the design of a data diode that limits the physical connection to two network interfaces, and eliminates the need for a third network connection needed to provide a carrier signal for the transmitter. This system has shown some latency in data transfer but has increased the safety and the security of files transferred between the PACS network and the external network.

关键词： Picture archiving and communication systems Security Biomedical imaging Hospitals Malware computer architecture

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Smart Medicine Box system 2

Smart Medicine Box System

引用

2nd IEEE International Multidisciplinary Conference on Engineering Technology, IMCET 2018

作者： Zeidan, Hiba Karam, Khalil Daou, Roy Abi Zeid Hayek, Ali Boercsoek, Josef Biomedical Technologies Department Lebanese German University Faculty of Public Health Jounieh Lebanon Department of Computer Architecture and System Programming Kassel University Kassel Germany

ISBN: (纸本)9781538645000

An advanced medicine box monitoring, analysis and control system is proposed in this paper. The latter design is based on a smart and safe medical box that assists patients in taking their pills treatment on time. Two main functionalities characterize this system: safety which assures the wellbeing of the patient and the good functioning of the system by duplicating the electrical components and the security that helps keeping the medication out of the reach of the children by automatically looking the medical box whenever the patient takes his pills. This system can also be monitored by the patient parents as it will be linked to a phone application. This application will be used to configure the medical box by calculating the weight of each pill, setting the schedule of medical intake, alarming the user of the number of remaining pills, generating alarms whenever the patient does not take the required number of pills or doesn't take them at all, and so on... This system was implemented and tested by more than 50 patients who were taking several medication types (each one of them takes one medication only) and were using different mobile phone. The overall results were very acceptable with a faulty alarm generation below 3%. © 2018 IEEE.

关键词： Pelletizing

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Monitoring system for Prediction and Detection of Epilepsy Seizure

Monitoring System for Prediction and Detection of Epilepsy S...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Nashaat el Halabi Roy Abi Zeid Daou Roger Achkar Ali Hayek Josef Börcsök Department of Computer and Communications Engineering American University of Science and Technology Beirut Lebanon MART Learning Education and Research Center Chananir Lebanon Department of Computer Architecture and System Programming University of Kassel Germany

Epilepsy is a neurological disorder associated with abnormal electrical activity in the brain, which causes seizures. The occurrence of seizure is not predictable; the duration between seizures, as well as the symptoms, varies from patient to another. Since the seizures are not predictable, and most of epileptic patients suffer from physical risky symptoms during the seizure, such patients are not able to perform daily work activities. The objective of this project is to design and implement a monitoring system for epileptic patients; the system should continuously check some vital signs, analyze the measurements, and decide whether the patient is nearly to have a seizure or not. Whenever a seizure is predicted, the system initiates an alarm. In addition, a notification should be sent to the health care responsible, as well as one preferred contact. By implementing the monitoring system, people who suffer from epilepsy will have more chance to work and live a normal life. Thus, this paper presents the concept of the overall system and shows results of the implemented systems: EEG, ECG and Fall Detection system. Results have shown that the fall detection accuracy reached 99.89% whereas the accuracy of the prediction using the ANN was about 97.34%.

关键词： Electroencephalography Epilepsy Feature extraction Tools Monitoring Artificial neural networks Support vector machines

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FPGA Implementation of a Safety system-on-Chip Based on 1oo4 architecture Using LEON3 Processor

FPGA Implementation of a Safety System-on-Chip Based on 1oo4...

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International Conference on computer and Applications (ICCA)

作者： Mohamed Abdelawwad Ali Hayek Ahmed Alsuleiman Josef Börcsök Chair for Computer Architecture and System Programming University of Kassel Kassel Germany

To ensure the reliability and safety in applications such as aeronautics, automotive, industrial automation, railway and space, several redundancy-based embedded architectures are used. In this work, the design of a 1oo4 safety system-on-Chip based on LEON3 processor with two different design approaches is presented. In both of the approaches, four LEON3 processors with a shared debug support unit, debug link and system peripherals are designed. However, one memory controller is interfaced with the system in the first approach while in the second approach four memory controllers are interfaced. Both the designs are implemented using the XUPV5-XC5VLX110T Xilinx development board (ML509). The performance of the system is verified in this work using the Xilinx ChipScope tool.

关键词： Safety Random access memory computer architecture Process control systems architecture Debugging Field programmable gate arrays

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Validation of the Proposed Fault Injection, Test and Hardness Analysis for Combinational Data-Flow Verilog HDL Designs Under the RASP-FIT Tool

Validation of the Proposed Fault Injection, Test and Hardnes...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Abdul Rafay Khatri Ali Hayek Josef Börscök Department of Computer Architecture and System Programming University of Kassel Kassel Germany Universitat Kassel Kassel Hessen DE

Owing to the condensed size of components in digital designs on the FPGA, it is difficult to guarantee an acceptable degree of reliability due to soft-errors. These designs are mostly available in Hardware Description Languages (HDL) at various abstraction levels, e.g. gate-level, data-flow, and behavioural. Fault Injection (FI) is a well-known technique to assess the dependability of such designs. Broadly, FI techniques for FPGA-based designs are categorized into emulation and simulation-based techniques. Simulation-Based FI (SBFI) tools work on hardware models of designs and help designers to test and verify designs at an early phase of the FPGA design & development flow. Testing, dependability analysis, and fault simulation applications require a faulty model of the original design during fault injection campaign. Therefore, we require a tool which can automatically generate the faulty model of the original design written at any abstraction levels and perform fault injection testing and dependability analysis. In this paper, a fault injection tool (RASP-FIT) is presented, which consists of an automatic code modifier (fault injection algorithm), fault injection control unit and result analyser. Previously, the tool is used for code-modification, test and hardness analysis for gate-level designs. In this paper, an enhancement of a code modifier along with result analyser techniques are applied to the data-flow benchmark designs and presented.

关键词： Circuit faults Tools Hardware design languages Logic gates Benchmark testing Prototypes

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