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Current Directions in Biomedical engineering 2023年第1期9卷 303-306页

作者： Kasparick, Martin Klotz, Tobias Andersen, Björn Thürk, Gregor Neumuth, Thomas Rockstroh, Max Rother, Benjamin Golatowski, Frank B. Braun Melsungen AG Carl-Braun-Straße 1 Melsungen 34212 Germany Drägerwerk AG & Co. KGaA Lübeck Germany ICCAS University of Leipzig Leipzig Germany Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

Patients and caregivers suffer from alarm-related noise in today's hospitals. While this is a topic for all fields of care, this challenge is especially relevant for intensive care units (ICUs). The noise harms patients, hinders the recovery process, or can even lead to psychosis. For the caregivers, noise causes an enormous stress level and in combination with the high number of clinically irrelevant or false alarms it leads to alarm fatigue and desensitization. These problems result in documented deaths of patients. Therefore, we present a demonstrator of a Silent ICU. Based on a distributed alarm system, the medical devices at the bedside do not create any audio alarm signals, as long as a remote alarm notification system is connected and works properly. An ICU bed place consists of devices from different manufacturers. Thus, a standardized interconnection is necessary. Therefore, we use IEEE 11073 Service-oriented Device Connectivity (SDC) to create a cross-manufacturer distributed alarm system with components from three different companies. A fourth company provides a documentation system for this demonstrator. Patients and caregivers will greatly benefit from Silent ICUs and smart distributed alarm systems that will be build based on interoperable cross-manufacturer environments. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Intensive care units

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The Future of EV: Real-Time Development of an Intelligent Wireless Charging System for Electric Vehicles 1

The Future of EV: Real-Time Development of an Intelligent Wi...

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1st International Conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Rajalingam, A. Darwin Nesakumar, A. Sathya, S. Krishnankutty, Jishor Erat Abid, Y. Pagunuran, Jubert R. College of Engineering and Technology University of Technology and Applied Sciences Engineering Department Shinas Oman R. M. K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Department of VLSI Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350361780

The world is always on the lookout for new ways to put technology to use, and it is changing at a rate no one has ever seen before. For decades, the car industry has done nothing to alter. The advent of electric vehicles, which run on electricity rather than fossil fuels, was the big breakthrough. There have been many investigations and appreciated structures as well as outcomes for wirelessly powering electric automobiles, both passively and rapidly. This might result in a more rapid acceptance of electric vehicles globally, as it is an emerging technology in automotive manufacturing that has not yet been widely used. We cross-validated our Intelligent Wireless Charging System (IWCS), a wireless power transmission charging circuit for electric vehicles, with the Classical Charging System (CCS) to assess the efficacy of the proposed model. To solve the problem of battery overheating during charging while plugged in, as well as to extend the vehicle's battery life, the suggested model is employed. Batteries temperature handling is the primary concern for EVs due to the increased heat losses while plugged-in charging, which in turn reduces the battery's lifespan. Currently, electric cars mostly employ water-cooled systems to cool the battery, which isn't ideal for EVs due to the added size and weight. Air cooling is another option for cooling systems;it's already used in internal combustion engines but isn't very effective in electric vehicles since charging the battery produces too much heat. There is a considerable decrease in thermal output when we employ wireless charging technology. The proposed system's primary objective is to provide wireless power transfer using inductive coupling as its basis. © 2024 IEEE.

关键词： Energy transfer

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Enhancing Four-Class Motor Imagery Detection Through Advanced Feature Extraction Techniques 21

Enhancing Four-Class Motor Imagery Detection Through Advance...

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2024 IEEE/ACS 21st International Conference on computer Systems and Applications, AICCSA 2024

作者： Souissi, Jihen Karmani, Sourour Belwafi, Kais Djemal, Ridha National Engineering School of Sfax Sfax University ATMS Laboratory ENIS Tunisia Higher Institute of Applied Sciences and Technology of Sousse University of Sousse University of Monastir Tunisia Laboratory of Electronics and Microelectronics FSM Tunisia University of Sharjah Computer Engineering Department CCI Sharjah United Arab Emirates Sfax University National Engineering School of Sfax ATMS Lab. Electrical Engineering Department United Arab Emirates

ISBN: (纸本)9798331518240

Brain-computer interface (BCI) technology has great potential in control, communication, and neurological diagnostics by interpreting EEG signals. This paper introduces a novel method for extracting distinguishing features from EEG signals using a Common Spatial Patterns (CSP) model, enhanced with a Phase Space Reconstruction model and followed by an autoregressive (AR) model. Initially, EEG signals are denoised using an IIR Butterworth filter before feature extraction. Two classifiers, Linear Discriminant Analysis (LDA) and Multi-Layer Perceptron (MLP), are employed to differentiate features across four motor imagery (MI) tasks. For a four-class MI task, combining spatial and temporal-frequency domain features, LDA achieves an accuracy of 67.40%, while MLP reaches 64.78%. LDA yields precision and recall scores of 67.40% and 67.20%, respectively, for the F1-score, whereas MLP records precision, recall, and F1-scores of 65.36%, 64.78%, and 64.28%, respectively. The proposed architecture is evaluated using the BCI Competition IV set 2a dataset, proving its effectiveness in EEG signal classification for BCI applications. © 2024 IEEE.

关键词： Frequency domain analysis

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Quantized Wavelet Dilated Convolutional Neural Network Based Intelligent Surveillance System for Public Safety in IoT Security Networks 4

Quantized Wavelet Dilated Convolutional Neural Network Based...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Sowmya, R. Rawat, Ruchira Mishra, Dinesh Megha, Mamtaben Kamleshbhai Patel, Monikaben Maheshbhai Kannan, Sathish Tamil Nadu Chennai600077 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Mangalayatan University-Jabalpur Department of Computer Science and Engineering Madhya Pradesh Jabalpur483001 India Natubhai V. Patel College of Pure and Applied Sciences A Constituent College of Cvm University Department of Computer Science Gujarat Anand388120 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Vlsi Microelectronics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331540364

Smart cities have produced vast amounts of surveillance video data that can be processed to identify anomalies since the introduction of visual sensors. A novel Quantized Wavelet Auxiliary Encoder Self-Attention Dilated Convolutional Neural Network with Gold Rush Optimizer (QWAESDCNN-GRO) designed to enhance security and reduce crime potential. Through the integration of the Quantized Discrete Haar Wavelet Transform (QDHWT), frame-level features have been extracted. Subsequently, the recovered features are fed to the Auxiliary Guided Knowledge Encoder-Decoder (AGED), which uses them to rank the features. These features are then sent to the Self-Attention Causal Dilated Convolutional Neural Network (SACDCNN) with Gold Rush Optimization (GRO) for anomaly detection. Performance indicators including Fl-score, recall, accuracy, precision, and AUC are compared with those of earlier techniques in order to assess the effectiveness of the recommended strategy. Using the UCF-Crime dataset, the model achieved an accuracy of 99.87% and an error rate of 0.021%. On the Hockey Fights dataset, it obtained an accuracy of 99.88% and an error rate of 0.019%. © 2024 IEEE.

关键词： Convolutional neural networks

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Low-Complexity Channel Estimation for RIS-Assisted ISAC System

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China Communications 2025年第4期22卷 296-308页

作者： Chen Zhen Li Jianqing Zhang Haijun Zhang Wei The Institute of Microelectronics University of MacaoMacao 999078China School of Computer Science and Engineering Macao University of Science and TechnologyMacao 999078China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology BeijingBeijing 100083China Henan Academy of Science Applied Physics Institute Co. LtdZhengzhou 450008China

Integrated sensing and communication(ISAC),assisted by reconfigurable intelligent surface(RIS)has emerged as a breakthrough technology to improve the capacity and reliability of 6G wireless ***,a significant challenge in RIS-ISAC systems is the acquisition of channel state information(CSI),largely due to co-channel interference,which hinders meeting the required reliability *** address this issue,a minimax-concave penalty(MCP)-based CSI refinement scheme is *** approach utilizes an element-grouping strategy to jointly estimate the ISAC channel and the RIS phase shift *** previous methods,our scheme exploits the inherent sparsity in RIS-assisted ISAC channels to reduce training overhead,and the near-optimal solution is derived for our studied RIS-ISAC *** effectiveness of the element-grouping strategy is validated through simulation experiments,demonstrating superior channel estimation results when compared to existing benchmarks.

关键词： channel estimation element grouping integrated sensing and communication(ISAC) RIS

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Hybrid Deep Learning Approaches for Data Security in Cloud Environments 2

Hybrid Deep Learning Approaches for Data Security in Cloud E...

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Rekha, S. Sharma, Manish Kannan, Sathish Upadhye, Vijay Jagdish Patil, Harshal Rajkumar, S. PSG College of Arts and Science Department of Computer Science Tamil Nadu Coimbatore641 014 India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Tamil Nadu Chennai602105 India Parul Institute of Applied Sciences Parul University Research and Development Cell Department of Microbiology Gujarat Waghodia India Computer Science and Engineering Maharashtra Pune412115 India Institute of Technology Hawassa University Faculty of Manufacturing Department of Mechanical Engineering Ethiopia

ISBN: (纸本)9798350327533

More recent studies have concentrated on methods to improve the security and privacy of cloud operations for the benefit of user data. For example, in order to safeguard sensitive data kept by a cloud-deployed procedure, it is important to guarantee secure transmission of sensitive data across multiple stakeholders. Researchers have investigated deeply into the subject of cloud security concerns, which include data breaches, denial of service, data loss, service rejection, and threats from malicious users. These issues typically stem from problems like multi-tenancy, lack of control over data, and trust issues. Cloud providers are primarily responsible for ensuring the security of the cloud platform. This study proposes a CNN-BiLSTM-AM hybrid model that combines Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (Bi-LSTM), and Attention Mechanism (AM). In order to determine how well our proposed hybrid model worked, this study tested it extensively against the traditional CNN and Long Short-Term Memory (LSTM) techniques. An established standard for evaluating intrusion detection systems, the CICIDS 2017 dataset was used in the study. The experimental results demonstrated that the proposed hybrid model outperformed the competition. The proposed hybrid model delivers the highest performance measure of accuracy (99.2%), detection rate (98.807%), and precision (99.59%). © 2024 IEEE.

关键词： Cardiovascular Disease Deep Learning Electrocardiogram Heartbeat Normalization

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Electrically tunable planar liquid-crystal singlets for simultaneous spectrometry and imaging

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Light(Science & Applications) 2024年第11期13卷 2589-2598页

作者： Zhou Zhou Yiheng Zhang Yingxin Xie Tian Huang Zile Li Peng Chen Yan-qing Lu Shaohua Yu Shuang Zhang Guoxing Zheng Electronic Information School and School of MicroelectronicsWuhan UniversityWuhan 430072China NUS Graduate School National University of SingaporeSingapore 119077Singapore Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulationand College of Engineering and Applied SciencesNanjing UniversityNanjing 210093China Peng Cheng Laboratory Shenzhen 518055China New Cornerstone Science Laboratory Department of PhysicsUniversity of Hong KongHong KongChina Department of Electrical and Electronic Engineering University of Hong KongHong KongChina Wuhan Institute of Quantum Technology Wuhan 430206China

Conventional hyperspectral cameras cascade lenses and spectrometers to acquire the spectral datacube,which forms the fundamental framework for hyperspectral ***,this cascading framework involves tradeoffs among spectral and imaging performances when the system is driven toward ***,we propose a spectral singlet lens that unifies optical imaging and computational spectrometry functions,enabling the creation of minimalist,miniaturized and high-performance hyperspectral *** a paradigm,we capitalize on planar liquid crystal optics to implement the proposed framework,with each liquid-crystal unit cell acting as both phase modulator and electrically tunable spectral *** with various targets show that the resulting millimeter-scale hyperspectral camera exhibits both high spectral fidelity(>95%)and high spatial resolutions(~1.7 times the diffraction limit).The proposed“two-in-one”framework can resolve the conflicts between spectral and imaging resolutions,which paves a practical pathway for advancing hyperspectral imaging systems toward miniaturization and portable applications.

关键词： crystal planar singlet

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Case-Study on Visible Light Communication for Implant Monitoring

Case-Study on Visible Light Communication for Implant Monito...

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2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022

作者： Koschay, Maximilian Richter, Henryk Statz, Meike Kober, Maria Puschmann, Jonas Plocksties, Franz Storch, Alexander Kuhn, Volker Timmermann, Dirk Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock18119 Germany Institute of Communications University of Rostock Rostock18119 Germany Department of Neurology University Medical Center Rostock Rostock18147 Germany

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

The focus of this paper is the feasibility of Visible Light Communication (VLC) for the monitoring of implants in rodents by example of two approaches. One of the VLC variants is intended for manually triggered transmission and takes advantage of the CMOS sensor rolling shutter principle. The second approach is designed mainly for autonomous monitoring. Trials with freely moving animals have shown that the first approach provides a throughput of 148 bit/s. For the automatic monitoring a transmission every 6 hours is sufficient for a reliable daily update of the implant *** exhibits limited range and channel capacity in comparison to radio frequency (RF) based telemetry. However, the advantage of VLC solutions is the minimal space requirement as only a single LED is needed in addition to the microcontroller on the transmitter side. © 2022 IEEE.

关键词： Visible light communication

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Silent ICU based on IEEE 11073 SDC

Silent ICU based on IEEE 11073 SDC

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作者： Kasparick, Martin Klotz, Tobias Andersen, Björn Thürk, Gregor Neumuth, Thomas Rockstroh, Max Rother, Benjamin Golatowski, Frank B. Braun Melsungen AG Carl-Braun-Straße 1 Melsungen34212 Germany Drägerwerk AG & Co. KGaA Lübeck Germany ICCAS University of Leipzig Leipzig Germany Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

关键词： Intensive care units

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TeleSDC Concept for ISO/IEEE 11073 SDC in telemedicine across unreliable networks

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Current Directions in Biomedical engineering 2021年第2期7卷 403-406页

作者： Pabst, Tobias Stegemann, Dominik Georgi, Christoph Kasparick, Martin Suleder, Julian Neumuth, Thomas Rockstroh, Max Innovation Center Computer Assisted Surgery Institute of Faculty of Medicine University Leipzig Leipzig Germany SurgiTAIX AG Herzogenrath Germany Institute of Applied Microelectronics and Computer Engineering (University Rostock) Rostock Germany ERNW Research GmbH Heidelberg Germany

Telemedicine promises to increase the quality of emergency treatments. Besides the transfer of speech and video data, medical device and patient data will add additional value to the tele-guided emergency personnel. In this paper, we develop a concept for transmitting device and patient data via the open communication standards SDC in a telemedical context, including data transmission over mobile radio networks while considering the limitations of public networks, and opening new usage scenarios for telemedicine. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Telemedicine

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