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A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram

Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9677-9750页

作者： Musa, Nehemiah Gital, Abdulsalam Ya’u Aljojo, Nahla Chiroma, Haruna Adewole, Kayode S. Mojeed, Hammed A. Faruk, Nasir Abdulkarim, Abubakar Emmanuel, Ifada Folawiyo, Yusuf Y. Ogunmodede, James A. Oloyede, Abdukareem A. Olawoyin, Lukman A. Sikiru, Ismaeel A. Katb, Ibrahim Department of Mathematical Sciences Abubakar Tafawa Balewa University Bauchi Nigeria University of Jeddah Jeddah Saudi Arabia Computer Science and Engineering University of Hafr Al-Batin Hafr Saudi Arabia Computer Science and Engineering University of Hafr Al-Batin Hafr Al-Batin Saudi Arabia Department of Computer Science University of Ilorin Ilorin Nigeria Department of Physics Sule Lamido University Kafin Hausa Nigeria Department of Electrical Engineering Ahmadu Bello University Zaria Zaria Nigeria Department of Medicine University of Ilorin Ilorin Nigeria

The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer vision, object detection, speech recognition, medical imaging and so on, has made deep learning the buzz word that dominates Artificial Intelligence applications. From the last decade, the applications of deep learning in physiological signals such as electrocardiogram (ECG) have attracted a good number of research. However, previous surveys have not been able to provide a systematic comprehensive review including biometric ECG based systems of the applications of deep learning in ECG with respect to domain of applications. To address this gap, we conducted a systematic literature review on the applications of deep learning in ECG including biometric ECG based systems. The study analyzed systematically, 150 primary studies with evidence of the application of deep learning in ECG. The study shows that the applications of deep learning in ECG have been applied in different domains. We presented a new taxonomy of the domains of application of the deep learning in ECG. The paper also presented discussions on biometric ECG based systems and meta-data analysis of the studies based on the domain, area, task, deep learning models, dataset sources and preprocessing methods. Challenges and potential research opportunities were highlighted to enable novel research. We believe that this study will be useful to both new researchers and expert researchers who are seeking to add knowledge to the already existing body of knowledge in ECG signal processing using deep learning algorithm. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Electrocardiograms

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A Novel DoA Algorithm for Coherent Signals with Asymmetric Multipath Phase Delays Based on a Modified Toeplitz Matrix Reconstruction

A Novel DoA Algorithm for Coherent Signals with Asymmetric M...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Dawod, Firas Slewa Roy, Sayan Dept. of Electrical Engineering and Computer Science South Dakota Mines Rapid CitySD57701 United States

ISBN: (纸本)9781665442282

This paper presents a new direction of arrival (DoA) method based on a modified Toeplitz matrix reconstruction (NMTMR) algorithm. The proposed method overcomes one of the primary challenges of the traditional Toeplitz DoA algorithm, the asymmetric multipath phase delay scenarios. Unlike the conventional Toeplitz algorithm, the NMTMR algorithm can maintain the diagonality of the signal covariance matrix (Rss) and hence can retain the full rank of the array covariance matrix (Rc) under different multipath phase delay scenarios. Specifically, the proposed NMTMR algorithm incorporates some pre- and post-signal processing and reconstruction steps to omit the elements that contributed to the deterioration of the diagonality of the signal covariance matrix (Rss). A successful demonstration of the proposed algorithm has also been presented using MATLAB simulation to validate the viability of the algorithm, albeit with the cost of increasing the number of the required antennas. © 2023 IEEE.

关键词： Direction of arrival

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The impact of different prosumer configurations on achieving savings due to the increase in electricity prices 4

The impact of different prosumer configurations on achieving...

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4th International Conference on Smart Grid Metrology, SMAGRIMET 2023

作者： Simic, Zvonimir Misljenovic, Nemanja Dubravac, Marina Topic, Danijel Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9798350323597

This paper investigates the consumption, and the cost of electricity for different configurations of prosumers in Croatia and additionally considers the current increase in electricity prices. In April 2022, electricity prices for households increased by 15%. Furthermore, from October 2022, electricity prices for households with annual electricity consumption above 5000 kWh are 50% higher than for households with annual electricity consumption below 5000 kWh. The load shifting from a period with a higher price to a period with a lower price can reduce electricity costs but cannot reduce the total amount of electricity imported from the distribution grid. Therefore, there is a possibility to install a PV power plant to meet consumers' own needs for electricity and to reduce the total amount of electricity imported from the distribution grid. Prosumers with different configurations regarding a PV power plant, battery energy storage, and optimal load shifting are simulated, and the total amount of electricity imported from the grid and total electricity costs are compared. According to simulation results, a prosumer with a PV power plant can reduce electricity consumption below 5000 kWh. On the other side, a prosumer with a PV power plant, battery energy storage, and optimal load shifting can significantly reduce total electricity costs. © 2023 IEEE.

关键词： Electric batteries

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Universal Fourier optics model for virtual coherence scanning interferometers 9

Universal Fourier optics model for virtual coherence scannin...

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Modeling Aspects in Optical Metrology IX 2023

作者： Lehmann, Peter Pahl, Tobias Riebeling, Jörg Measurement Technology Faculty of Electrical Engineering and Computer Science University of Kassel Wilhelmshoeher Allee 71 Kassel34121 Germany

ISBN: (数字)9781510664487

ISBN: (纸本)9781510664470

Optical surface topography measurements sometimes suffer from systematic errors. In order to predict such deviations, modeling of optical profilers is a substantial part of the European project TracOptic (Traceable Optics). Within the framework of this project, we recently developed the UFO (Universal Fourier Optics) model, which simulates virtual CSI measurements of surface topographies that fulfill the requirements of the scalar Kirchhoff approximation. The model enables a fast computation of 'measured' surface topographies as it is based on discrete Fourier transforms. It treats the surface under investigation as a two-dimensional phase object assuming a linear dependence of the interference phase on surface height and axial spatial frequency. The scattered light field is transferred to the Fourier domain and multiplied by a partial two-dimensional transfer function (TF) representing a horizontal cross section of the three-dimensional TF at a certain axial spatial frequency or evaluation wavelength, respectively. The TF includes parameters of the interference microscope and the reference field distribution. Inverse Fourier transform enables the reconstruction of the phase object. The coherence peak position of an interference signal results from numerical differentiation with respect to the axial spatial frequency and is generally used to overcome the 2π ambiguity of the phase profile. Parameters affecting final results of reconstructed surface topographies are the central wavelength and the spectral bandwidth of the illuminating light as well as the numerical aperture of the objective lens and the chosen evaluation wavelength. We discuss results of the UFO model with respect to the prediction of systematic deviations of measured surface topographies. © 2023 SPIE.

关键词： Function evaluation

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Towards Real-Time Motion Planning for Industrial Robots in Collaborative Environments 49

Towards Real-Time Motion Planning for Industrial Robots in C...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Bhuiyan, Teham Kutschank, Benno Pruter, Karim Flach, Huy Kastner, Linh Lambrecht, Jens Berlin Institute of Technology Chair Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350331820

In collaborative environments, real-time motion planning is crucial for industrial robots to navigate safely and efficiently. Traditional planning algorithms, such as Rapidly-exploring Random Trees (RRT) or Probabilistic Roadmaps (PRM), often face challenges in coping with dynamic environments due to their inherent computational complexity. To address this issue, we propose an approach based on Deep Reinforcement Learning (DRL) for real-time motion planning of industrial robots. Our method leverages the power of machine learning and neural networks to enable robots to make intelligent decisions in real-time, ensuring prompt and adaptive navigation. However, applying DRL to industrial robots poses unique challenges, as vision-based training is difficult and distance sensors commonly used in mobile robots are unavailable. To overcome these challenges, we employ depth cameras to generate distance information and convert the obtained point cloud into voxels using the Open3D library. The obstacles are then loaded into the simulation environment in real-time, allowing the agent to perceive and react to the dynamic environment. To achieve a low simulation-to-real-gap, we propose a hardware-in-the-loop (HIL) approach, where the real robot mimics the movements of the simulated robot. We demonstrate the effectiveness of our system through real-world experiments. Our code is available on GitHub [1]. © 2023 IEEE.

关键词： Industrial robots

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FireBot - An Autonomous Surveillance Robot for Fire Prevention, Early Detection and Extinguishing 15

FireBot - An Autonomous Surveillance Robot for Fire Preventi...

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15th International Conference on computer and Automation engineering, ICCAE 2023

作者： Balen, Josip Damjanovic, Davor Maric, Petar Vdovjak, Kresimir Arlovic, Matej Martinovic, Goran Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9798350396225

Every year, fire is responsible for numerous deaths, as well as huge material losses. Therefore, prevention and early detection of fire have become a priority for society, as well as the main research and development issue for many scientists and various industries. This paper describes our work in the development of FireBot, an autonomous surveillance robot. The Firebot is equipped with modern technologies and state-of-the-art navigational and computer vision methods that enable autonomous navigation, obstacle avoidance, video surveillance, fire prevention and detection, and fire extinguishing. It utilizes both infrared thermal (IRT) and RGB cameras paired with a modern convolutional neural network (CNN) for fault and fire detection, as well as various other sensors for analyzing air composition, processing of surrounding sounds, and detecting irregularities in its environment in general. The best performing CNN was implemented and tested in real-world environments for fire detection purposes, the results of which are presented in this paper. A state-of-the-art SLAM algorithm paired with LiDAR and a depth camera is used for mapping and navigation. The architecture presented in this paper, along with all functionalities planned for future work, represents an innovative autonomous surveillance system that will make a great contribution in the field of fire prevention and detection. © 2023 IEEE.

关键词： Fires

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YOLOv8-Based Real Time Fish Detection and Classification Using Indigenous Bangladesh Fish and its Comparison

YOLOv8-Based Real Time Fish Detection and Classification Usi...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Nathasarma, Rahash Mazumdar, Biswatosh Roy, Binoy Krishna National Institute of Technology Silchar Department of Electrical Engineering Assam Silchar India Sikkim Manipal Institute of Technology Department of Computer Science Sikkim India

ISBN: (纸本)9798331540821

Fisheries management has a significant role in fish farming. Fisheries managers can make informed decisions regarding stock assessment, resource allocation, and disease prevention, contributing to sustainable fishing practices and the preservation of aquatic ecosystems. This paper presents a case study for simultaneous fish detection and classifications using YOLOv8 neural network. The YOLOv8 is a real-time object detection algorithm that can be used to detect fish in images and classify the different categories of fish. We have taken an existing dataset for this study, i.e. indigenous Bangladesh fish dataset of eight different fish species. We trained a YOLOv8 model on that dataset. A detailed description of the training process is provided. The effectiveness of the model is evaluated through the normalised confusion matrix, mean average precision curve of the trained model and other loss plots. The designed model can detect fish and classify fish species with an accuracy of about 99% and comparatively better than previous works. © 2024 IEEE.

关键词： Invertebrates

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Enhanced Anomaly Detection in Automotive Systems Using SAAD: Statistical Aggregated Anomaly Detection 26

Enhanced Anomaly Detection in Automotive Systems Using SAAD:...

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26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2024

作者： Goina, Dacian Hogea, Eduard Maties, George West University of Timisoara Faculty of Mathematics and Computer Science Timisoara Romania Gheorghe Asachi Technical University of Iasi Faculty of Electrical Engineering Iasi Romania

ISBN: (纸本)9798331532833

This paper presents a novel anomaly detection methodology termed Statistical Aggregated Anomaly Detection (SAAD). The SAAD approach integrates advanced statistical techniques with machine learning, and its efficacy is demonstrated through validation on real sensor data from a Hardware-in-the-Loop (HIL) environment within the automotive domain, where physical components of the vehicle are interfaced with simulation models. The HIL setup provides a controlled, real-time testing framework that replicates actual driving conditions, allowing for the validation of the vehicle's control systems under various operational scenarios without the need for a physical vehicle prototype. The key innovation of SAAD lies in its ability to significantly enhance the accuracy and robustness of anomaly detection when combined with Fully Connected Networks (FCNs) augmented by dropout layers. Comprehensive experimental evaluations indicate that the standalone statistical method achieves an accuracy of 72.1%, whereas the deep learning model alone attains an accuracy of 71.5%. In contrast, the aggregated method achieves a superior accuracy of 88.3% and an F1 score of 0.921, thereby outperforming the individual models. These results underscore the effectiveness of SAAD, demonstrating its potential for broad application in various domains, including automotive systems. © 2024 IEEE.

关键词： Hardware-in-the-loop simulation

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EMG Based MIDI Controller

EMG Based MIDI Controller

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2023 International Young Engineers Forum in electrical and computer engineering, YEF-ECE 2023

作者： Pedrosa, Sebastiao Costa, Aniko NOVA University Lisbon Nova School of Science and Tenchology Electrical and Computer Engineering Departmant Caparica2829-516 Portugal

ISBN: (纸本)9798350300420

MIDI is a standard that has been used for musical performance since the early eighties and has been gaining increasing popularity ever since for its ease of use and versatility. The objective for this work is to implement a MIDI controller that takes input from the user's hand/arm motion, and as such, send MIDI data to a MIDI interface. Hand movement was captured using three EMG sensors (Olimex Shield-EKG-EMG) along the forearm region to capture muscle activity. These will be connected to an Arduino UNO board and send sensor data into a Raspberry PI 4B board for data analysis. Then, in order to compare and determine which one is best to detect four different hand gestures, said activity will be analyzed using three different machine learning algorithms, namely Random Forest (RF), Support Vector Machines (SVM) and a three hidden layer neural network (NN). After classification, depending on the gesture, the controller converts these movements into their correspondent MIDI note for musical performance. Finally, performance will be tested using virtual instruments on a digital audio work station (DAW), namely Ableton Live 9. © 2023 IEEE.

关键词： Controllers

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TriMoFaceNet: A Trimmed MobileFaceNet Architecture for Resource-constrained Environments 6

TriMoFaceNet: A Trimmed MobileFaceNet Architecture for Resou...

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6th International Conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2024

作者： Prakash, Pritesh Singh, Prinsh Kumar Jerripothula, Koteswar Rao Central Research Lab Bharat Electronics Ltd. Ghaziabad India Department of Electrical Engineering IIT Kanpur India Department of Computer Science and Engineering IIIT-Delhi India

ISBN: (纸本)9781510681781

As one of the most popular vision applications, face verification systems can be needed in all kinds of scenarios, including resource-constrained environments. In this paper, we propose a trimmed variant of MobileFaceNet, which can perform as well as MobileFaceNet but with fewer memory and computational requirements. We essentially make two changes to the bottlenecks: reversing the expansion-projection process and adding one more depth-wise convolution layer. While the first one significantly reduces the number of parameters and calculations, the second one increases them. We try to strike a balance between the two to have a complex enough network architecture that can perform face verification as well as the original one. We could cut down the model size by almost a quarter in this manner, and we name the resultant network TriMoFaceNet. © 2024 SPIE.

关键词： Network architecture

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