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Analysis of Failure Causes in the Mammography Machines 9th

Analysis of Failure Causes in the Mammography Machines

9th Latin American Congress on biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on biomedical engineering, CBEB 2022

作者： Hernandez-Contreras, Indira Martinez-Licona, Fabiola M. Electrical Engineering Department Universidad Autonoma Metropolitana Iztapalapa Mexico City Mexico Universidad Autonoma Metropolitana Biomedical Engineering Academic Program Iztapalapa Mexico City Mexico

ISBN: (纸本)9783031494093

Patient safety arises from the need to prevent and protect patients from avoidable mistakes. Two fundamental concepts that shape patient safety are error and adverse events, the consequences may range from potentially dangerous complications, slow recoveries, high medical costs, or unnecessary deaths. Breast cancer has become a global health problem with one of the most expensive burdens among non-communicative diseases. Since screening mammography is the most used method for tumor identification, patient safety applied to this technology is focused on delivering safe and effective service that results in an accurate and reliable diagnosis. This paper presents the analysis of the causes that can induce a potential failure in the mammography machine, and the actions to correct them. We used a risk analysis approach to identify the failures that may occur while using a mammography machine in screening programs. We extracted the information about the failures from specialized consultation and discussion forums and technical and operation manuals. We adapted the concepts of severity, occurrence, and detection involved in calculating the risk priority number according to the Failure Mode and Effects Analysis method, assigning them one of three levels (low, medium, and high). The adapted risk priority level was calculated from the averaged product of levels from the mentioned components. The results were mapped into an Ishikawa diagram, and an action procedure proposal was shown. The causes found are defined mainly concerning the handling of the equipment components, although causes related to the acquisition technique, patient handling, and availability of support information. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Risk assessment

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Supervised learning applied to electrocardiogram statistical features for the detection of premature ventricular contraction

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Research on biomedical engineering 2025年第1期41卷 1-12页

作者： Issa, Khouloud Rammal, Abbas Assaf, Rabih Ghandour, Ahmad Electrical and Communication Engineering Department College of Engineering Phoenicia University Zahrani South Lebanon Statistics and Informatics Department Faculty of Science Lebanese University Beirut Lebanon Mathematics and Computer Sciences Department Faculty of Arts and Sciences Lebanese American University Beirut Lebanon Department of Mathematics Faculty of Arts and Sciences Holy Spirit University of Kaslik Jounieh Lebanon Biomedical Engineering Department Faculty of Engineering Islamic University of Lebanon Wardenieh30014 Lebanon

Purpose: The development of an automated premature ventricular contraction (PVC) detection system has significant implications for early intervention and treatment decisions. This study aims to develop a novel approach using various supervised machine learning (ML) methods for detecting PVCs in electrocardiogram (ECG) recordings. Methodology: To achieve this, we extracted ten distinct statistical and temporal features from 33 long-term ECG recordings from the benchmark MIT-BIH arrhythmia database (MIT-BIH-AD), capturing significant characteristics from the signals. We then investigated the effectiveness of traditional ML algorithms in identifying PVCs based on these features, namely support vector machine (SVM), decision tree (DT), naïve Bayes (NB), k-nearest neighbor (KNN), linear discriminant analysis (LDA), and artificial neural network (ANN). Results: Among these classifiers, the SVM, KNN, ANN, and DT classifiers demonstrated exceptional discriminatory power and classification performance, yielding near-perfect area under the receiver operating characteristic curve (AUC-ROC) values of 97.3%, 95.4%, 95%, and 94.1%, respectively. On the other hand, the SVM classifier emerged as the most accurate, achieving an overall accuracy of 97.39%, indicative of making correct predictions. Conclusion: These findings underscore the generalization of the proposed approach, especially since we worked on an extended dataset encompassing different types of heartbeats to discriminate PVCs from other heartbeat types, not only normal ones, and providing closer alignment with real-world scenarios. Subsequently, the robustness and accuracy of these models highlight their suitability for clinical applications and their potential for efficient implementation and deployment in the diagnosis of cardiovascular diseases (CVDs), as they demand minimal computational resources and time. © The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering 2025.

关键词： Decision trees

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An economic centralised combinational load shedding scheme to protect power system in case cascade and major disturbances occur

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International Journal of Ambient Energy 2022年第1期43卷 8949-8958页

作者： Mohammadzadeh, Hossein Mohammadzadeh, Mohammad Department of Electrical Engineering Shahid Chamran University of Ahvaz Ahvaz Iran School of Electrical Computer and Biomedical Engineering Southern Illinois University CarbondaleIL United States

This paper introduces an economic centralised combinational load shedding scheme for self-healing of the power system against cascading significant disturbances. The proposed method utilises the voltage stability risk index (VSRI) to maintain the power system's voltage and frequency stability margin. In this algorithm, the protection against cascading disturbances when the spinning reserve of the system cannot recover has been considered. Moreover, it considered the voltage and economic cost of loads to find the proper location of load shedding and minimised the number of customers being turned off to increase social welfare. Furthermore, a voltage stability index based on the maximum power limit of the transmission lines (L index) and frequency steps is used to offset issues associated with VSRI. According to the simulation results that have been performed over the 39-bus New England system, the proposed scheme has a better performance than the previous methods. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Electric load shedding

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Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis

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IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 122-154页

作者： Lee, Minhun Song, HyeonJu Park, Jeeyoon Jeon, Byeungwoo Kang, Jungwon Kim, Jae-Gon Lee, Yung-Lyul Kang, Je-Won Sim, Donggyu Department of Computer Engineering Kwangwoon University Seoul Korea Republic of Department of Computer Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Kyunggi-do Korea Republic of Communication and Media Research Laboratory Electronics and Telecommunications Research Institute Deajeon Korea Republic of School of Electronics and Information Engineering Korea Aerospace University Kyunggi-do Korea Republic of Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Versatile Video Coding (H.266/VVC) is the newest video coding standard jointly developed by the Joint Video Experts Team (JVET), which is organized by the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). H.266/VVC provides about 40% bitrate reduction compared with High Efficiency Video Coding (H.265/HEVC) for the same visual quality. This paper introduces in detail the core structure of H.266/VVC by highlighting its features within block partitioning structure, intra/inter prediction, transform, quantization, and in-loop filtering, compared to its predecessor (H.265/HEVC). H.266/VVC yields significantly improved the coding performance, but it increased the computational complexity, particularly for the encoder side, which remains a problem to be tackled for successful commercialization in the future. This paper examined the statistical performance of H.266/VVC coding tools from the bitstreams encoded by the VVC test model (VTM12.0) encoder through rate-distortion optimization under the JVET common test conditions. In addition, the complexity and performance analyses are conducted on the block partitioning structure and group of picture structure. It is expected that an optimized H.266/VVC encoder can be designed and developed by minimizing the coding loss based on the analysis data. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Image compression

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Accuracy Testing of PQ Analyzers Using the OMICRON CMC 356 23

Accuracy Testing of PQ Analyzers Using the OMICRON CMC 356

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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Hlavaty, Lukas Bilik, Petr VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic

ISBN: (纸本)9798350335934

This article deals with the accuracy check of the PQ analyzers using the OMICRON CMC 356 calibrator. This article describes the principle and concept of three applications used to test the accuracy of various quantities important in PQ measurements. Furthermore, the GUI of each application, its principle, and description of functionality, software architecture, and implementation in the LabVIEW graphical programming environment are described. The purpose of the applications is the automated generation of a three-phase voltage at the output of the OMICRON CMC 356 calibrator with parameters defined by the operator to test the accuracy of the PQ analyzers. The first application is used to generate the harmonic components according to EN 50160 with definable deviations from the standard and duration intervals. The second application is to generate defined sequence of events (overvoltages, undervoltages, faults) with a definable duration. The third application is used to simulate different types of voltage fluctuations called flicker at the output of the calibrator. © 2023 IEEE.

关键词： Power quality

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Study of AI-Driven Fashion Recommender Systems

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SN computer Science 2023年第5期4卷 1-19页

作者： Shirkhani, Shaghayegh Mokayed, Hamam Saini, Rajkumar Chai, Hum Yan Department of Computer Science Electrical and Space Engineering Luleå Tekniska Universitet Luleå Sweden Department of Mechatronics and Biomedical Engineering Universiti Tunku Abdul Rahman Selangor Malaysia

The rising diversity, volume, and pace of fashion manufacturing pose a considerable challenge in the fashion industry, making it difficult for customers to pick which product to purchase. In addition, fashion is an inherently subjective, cultural notion and an ensemble of clothing items that maintains a coherent style. In most of the domains in which Recommender Systems are developed (e.g., movies, e-commerce, etc.), the similarity evaluation is considered for recommendation. Instead, in the Fashion domain, compatibility is a critical factor. In addition, raw visual features belonging to product representations that contribute to most of the algorithm’s performances in the Fashion domain are distinguishable from the metadata of the products in other domains. This literature review summarizes various Artificial Intelligence (AI) techniques that have lately been used in recommender systems for the fashion industry. AI enables higher-quality recommendations than earlier approaches. This has ushered in a new age for recommender systems, allowing for deeper insights into user-item relationships and representations and the discovery patterns in demographical, textual, virtual, and contextual data. This work seeks to give a deeper understanding of the fashion recommender system domain by performing a comprehensive literature study of research on this topic in the past 10 years, focusing on image-based fashion recommender systems taking AI improvements into account. The nuanced conceptions of this domain and their relevance have been developed to justify fashion domain-specific characteristics. © 2023, The Author(s).

关键词： Artificial Intelligence (AI) computer vision Content-based image retrieval (CBIR) Deep learning Fashion recommender system

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Alzheimer’s Disease and Frontotemporal Dementia: Differential Diagnosis Using Electroencephalogram Signal 1

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13th National Technical Symposium on Unmanned System Technology, NUSYS 2023

作者： Rostamikia, Mehran Sarbaz, Yashar Farzamnia, Ali Biomedical System Modeling Lab Biomedical Engineering Department Electrical and Computer Engineering Faculty University of Tabriz Tabriz Iran Faculty of Engineering Universiti Malaysia Sabah Sabah Kota Kinabalu Malaysia School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (数字)9789819720279

ISBN: (纸本)9789819720262

Dementia is a neurological disorder that affects a person’s cognitive and social skills, leading to a decline in their overall mental functioning. Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) are two common types of dementia. Frontotemporal dementia mostly affects the frontal and temporal lobes of the brain. These areas are responsible for executive functions, decision-making, language, behavior regulation, and personality traits. Alzheimer’s disease primarily damages the cerebral cortex, which is responsible for higher cognitive functions such as memory, language, and perception. The electroencephalogram (EEG) signal has many advantages in diagnosing these disorders, including low cost and high temporal resolution. This study compares AD and FTD patients with healthy subjects by extracting specific features from EEG signals. Two machine learning algorithms were used for the separation, Support Vector Machines (SVMs) and k-Nearest Neighbors (KNNs), and 10-Fold Cross-Validation was applied to validate the performance of this method and an accuracy of 91.2% (sd = 7.8) was achieved using the SVM classifier for diagnosing the disease and 71.1% (sd = 8.6) for classifying AD and FTD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Image Enhancement Algorithm for Liver CT Scan using Digital Image Processing 6

Image Enhancement Algorithm for Liver CT Scan using Digital ...

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6th International Conference on Digital Medicine and Image Processing, DMIP 2023

作者： Linsangan, Noel B. Martin, Melissa B. Cacnio, Jose Lorenzo I. Su, Jenn-Lung School of Electrical Electronics and Computer Engineering Mapua University Philippines Department of Biomedical Engineering Chung Yuan Christian University Taiwan

ISBN: (纸本)9798400709425

Image Enhancement is defined as the process of improving the quality of a digitally-stored image by manipulating it by means of image processing. Image enhancement is often applied in various images such as a Computed Tomography scan, a medical image employing tomography created by computer processing. The image produced in these scans are grayscale in nature and requires a much simpler image processing technique compared to colored images. The techniques that will be used for the enhancement of a Liver CT scan shall follow the standards of "Digital Image Processing"and shall be coded in computer programming software (Borland C++ Builder 6). Digital image processing is the use of computer algorithms to perform image processing on digital images, the word algorithm being a series of steps, reoccurring or not. This research will demonstrate and describe in detail the different algorithms that were applied (e.g. grayscale transformation, histograms, histogram equalization, etc.) and the resulting recommended algorithm that will be used to reduce the noise of a liver CT scan image. © 2023 ACM.

关键词： computerized tomography

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Cognitive Analysis based on Brain Connectivity for Learning Task fMRI Data using CONN Software Package 1

Cognitive Analysis based on Brain Connectivity for Learning ...

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1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Jatoi, Munsif Ali Teevino, Sadam Hussain Dharejo, Fayaz Ali Salim Habib University Department of Biomedical Engineering Sindh Karachi Pakistan Tenologico de Monterrey School of Engineering and Sciences Mexico Khalifa University Department of Electrical Engineering and Computer Science United Arab Emirates

ISBN: (纸本)9798350373042

The educational psychology is dependent upon the cognition and learning. The productive research in this domain yields the results for improvements in novel pedagogical methods at various educational level. The learning and memory are closely affiliated with brain structure and functioning i.e., neurobiology which has been the topic of research in philosophy, psychology and social sciences. Hence, to study the learning mechanism for improvements in educational methods, its essential to understand theoretical background of cognitive analysis through brain sciences. The human brain consists of billions of neurons with trillions of synaptic connections structurally and functionally organized in multiple scales of space and time, respectively. This complex structure is responsible for various complex and simple mental/physical tasks such as learning, memory, listening, sequencing, reasoning, motion, thinking, controlling, etc. The brain activity is analyzed through either source analysis or connectivity analysis. The connectivity analysis is carried out by either anatomical way, which is termed as anatomical connectivity, or through the functional way, which is termed as functional connectivity. However, the third explores the cause and effect relationship for a set of neurons and is termed as effective connectivity. This research work produces a generalized review for educational learning and then its relationship with connectivity analysis, including its introduction, graph theory implication, discussion for its types, and parameter discussion. Finally, functional connectivity was implemented on brain data using the CONN software package to compare various degrees, Eigenvalue, and betweenness centrality using fMRI data. The results show that the Eigenvalue centrality measure performs the best result for functional connectivity compared with other centrality measures. © 2024 IEEE.

关键词： Software packages

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Modeling of a Hexagonal Microstrip Patch Antenna for Breast Cancer Detection

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Journal of engineering and Science in Medical Diagnostics and Therapy 2024年第3期7卷 031007页

作者： Chowdhury, Nure Alam Wang, Lulu Islam, Md Shazzadul Gu, Linxia Kaya, Mehmet Department of Biomedical Engineering and Science Florida Institute of Technology MelbourneFL32901 United States Biomedical Device Innovation Center Shenzhen Technology University Shenzhen518118 China Department of Electrical and Computer Engineering International Islamic University Malaysia Jalan Gombak Selangor Kuala Lumpur53100 Malaysia

Breast cancer is a global problem, and it is inevitable to detect cancerous cells at early stages. In recent years, microwave imaging (MWI) technology has been widely applied in biomedical applications for its nonionizing radiation. Therefore, in this paper, a low profile hexagonal microstrip patch antenna has been proposed for the technology to detect breast cancer. This antenna has wide operating bandwidth of 13.5 GHz (6.6 GHz to 20.1 GHz), and the return loss is as low as -50.83 dB at 8 GHz. To evaluate the antenna performances, the proposed antenna has been simulated in two different simulation software like HFSS and CST MWS. The antenna has achieved a maximum gain of 8.82 dBi with a quasi-omnidirectional radiation pattern. A three-layered human body mimicking breast phantom with different dielectric properties has been designed with and without tumor mimicking tissue. The difference between the dielectric properties of the tumor and the dielectric properties of different layers of breast phantom in the presence of external radiation field can inform the existence of tumor inside the breast phantom. An array of eight elements of proposed antenna is distributed around the breast phantom to detect the tumor with a minimum radius of 2 mm. Because of the low profile and compact in size (7:9 mm X 11:4 mm), the proposed antenna is suitable for multistatic MWI technology for breast cancer detection at early stage. Copyright © 2024 by ASME.

关键词： Tumors

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