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16th International Conference on Developments in eSystems engineering, DeSE 2023

作者： Gad, Abdalla Fteiha, Bara' Alatawi, Jawaher Mohammed, Mahra Almansoori, Mahra Ghazal, Mohammed Yousaf, Jawad Almajali, Eqab Hussain, Abir Jafar Abu Dhabi University Electrical Computer and Biomedical Engineering Department Abu Dhabi United Arab Emirates University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350381344

This work proposes a flexible, foldable, lightweight, robust, and smart cane to aid visually impaired individuals and patients in navigating unfamiliar environments safely. The developed smart cane is equipped with an ultrasonic sensor, RFID reader, and an AI machine vision sensor for object detection and identification in the range of 30 cm to 9 m. A mobile application with a text-to-voice feature is developed that connects with the cane using Bluetooth to provide voice warnings to the user based on processed sensor output. The developed cane is also equipped with a vibration sensor activated when an obstacle is closer than 30 cm, serving as a backup of voice warnings. Object detection and classification using multiple sources (AI vision sensor, ultrasonic sensor, and RFID readers) ensures robust and uninterrupted operation in case of failure of one sensor. In emergencies, users can send text messages with their location to a pre-selected caretaker's phone number using the installed SOS button. The rechargeable battery offers more than 24 hours of operation and warns users when the battery is low. The prototype has been successfully executed and tested in various environments and aims to improve the safety and quality of life for visually impaired individuals and hospital patients. © 2023 IEEE.

关键词： Object detection

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EEG2Text: Open Vocabulary EEG-to-Text Translation with Multi-View Transformer

EEG2Text: Open Vocabulary EEG-to-Text Translation with Multi...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Liu, Hanwen Hajialigol, Daniel Antony, Benny Han, Aiguo Wang, Xuan Virginia Tech Department of Computer Science BlacksburgVA United States Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA United States Virginia Tech Department of Biomedical Engineering and Mechanics BlacksburgVA United States

ISBN: (纸本)9798350362480

Deciphering the intricacies of the human brain has captivated curiosity for centuries. Recent strides in Brain-computer Interface (BCI) technology, particularly using motor imagery, have restored motor functions such as reaching, grasping, and walking in paralyzed individuals. However, unraveling natural language from brain signals remains a formidable challenge. Electroencephalography (EEG) is a non-invasive technique used to record electrical activity in the brain by placing electrodes on the scalp. Previous studies of EEG-to-text decoding have achieved high accuracy on small closed vocabularies, but still fall short of high accuracy when dealing with large open vocabularies. We propose a novel method, EEG2Text, to improve the accuracy of open vocabulary EEG-to-text decoding. Specifically, EEG2Text leverages EEG pre-training to enhance the learning of semantics from EEG signals and proposes a multi-view transformer to model the EEG signal processing by different t spatial regions of the brain. Experiments show that EEG2Text has superior performance, outperforming the state-of-the-art baseline methods by a large margin of up to 5% in absolute BLEU and ROUGE scores. EEG2Text shows great potential for a high-performance open-vocabulary brain-to-text system to facilitate communication. Our code is available at: https://***/ForeverNightmare/EEG2Text. © 2024 IEEE.

关键词： Electroencephalography

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Infrastructure-dependent ramp-metering control for METANET-s 63

Infrastructure-dependent ramp-metering control for METANET-s

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Kamalifar, Ayda Cenedese, Carlo Cucuzzella, Michele Ferrara, Antonella University of Pavia Department of Electrical Computer Science and Biomedical Engineering Pavia27100 Italy Eth Zürich Department of Information Technology and Electrical Engineering Zürich Switzerland Nijenborgh 4 Groningen9747 AG Netherlands

ISBN: (纸本)9798350316339

In this paper, we propose a novel infrastructure-dependent ramp-metering control for the recently proposed METANET with service station (METANET-s) model, i.e., a second-order macroscopic traffic model that, compared to the classical METANET, incorporates the dynamics of service stations on highways. We study the effect of a ramp-metering control scheme on a highway stretch with a service station and show that it is capable of actively regulate internal traffic demand attempting to exit the service station via its on-ramp, on top of contributing to decrease the traffic congestion on the mainstream. In fact, the proposed control scheme effectively prevents the backlog of vehicles attempting to merge back onto the mainstream. This dynamic control mechanism is further endowed by a route guidance control strategy increasing the share of vehicles stopping at the service station during main-stream congestion periods, e.g. via incentives. The combined effect of our control schemes allows to take full advantage of the presence of service stations, reducing the overall traffic congestion. Simulation results demonstrate the effectiveness of the proposed control strategies. © 2024 IEEE.

关键词： Traffic congestion

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An Artificial Heart System for Testing and Evaluation of Cardiac Pacemakers

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computers, Materials & Continua 2022年第12期73卷 6269-6287页

作者： Martin Augustynek Jan Kubicek Jaroslav Thomas Marek Penhaker Dominik Vilimek Michal Strycek Ondrej Sojka Antonino Proto Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of Ostrava17.Listopadu 15Ostrava–Poruba70800Czech Republic

The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is *** paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s *** this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming *** electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation *** LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in *** results demonstrate the capability of proposed system to evaluate the paced and sensed *** proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing *** addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.

关键词： Artificial heart cardiac conduction system electrical cardiac stimulation pacemaker

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Hand Movements Detection Using EMG Signals for Human-computer Interface and convolution neural network 20

Hand Movements Detection Using EMG Signals for Human-Compute...

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20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Nazari, Jamal Nosheri, Azar Ghamangiz Mousavi, Seyed Amirhossein Islamic Azad University Qazvin Branch Department of Electrical Engineering and Mechatronics Engineering Qazvin Iran Islamic Azad University Mashhad Branch Department of Computer Engineering Mashhad Iran Islamic Azad University Mashhad Branch Department of Biomedical Engineering Mashhad Iran

ISBN: (纸本)9798350383942

This article presents a study on the effectiveness of a Convolutional Neural Network -based approach for hand movement detection using electromyography (EMG) signals. The study involved 40 participants and used Myo armbands to record EMG signals. The CNN model consisted of three convolutional layers, three max-pooling layers, and two fully connected layers. The model achieved an F1-score of 0.981, precision of 0.981, and recall of 0.981, outperforming two other machine learning algorithms, SVM and RF. The study's results demonstrate the potential of using CNNs for detecting hand movements using EMG signals, which can be applied in prosthetics and robotics for controlling prosthetic limbs and robotic arms. The study's findings suggest that CNN-based approaches have great potential for future research in the field of EMG-based hand movement detection. © 2024 IEEE.

关键词： Machine learning

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Surrogate Simulation of Subject-Specific Lateral Pinch via Deep Learning 46

Surrogate Simulation of Subject-Specific Lateral Pinch via D...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Lindbeck, Erica M. Diaz, Maximillian T. Nichols, Jennifer A. Harley, Joel B. University of Florida Department of Electrical and Computer Engineering GainesvilleFL United States University of Florida J. Crayton Pruitt Family Department of Biomedical Engineering GainesvilleFL United States

ISBN: (纸本)9798350371499

Musculoskeletal modeling and simulation is often a lengthy and computationally expensive process, particularly when developing and using personalized models. We present a deep learning-based adaptive surrogate model for lateral pinch, which accepts both musculoskeletal parameters and muscle activations as input for personalization and simulation. This model matches traditional OpenSim forward dynamics with an average root-mean-squared error (RMSE) of 2.27 N, within standard errors of experimental measurements, while demonstrating sensitivity to both categories of input and performing thousand of simulations in seconds (10-1000x faster than traditional multi-body simulations). In addition to direct use as a surrogate, the differentiable nature of the model may support future use in optimization problems, while its flexibility may support adaptation to modeling of experimental data. © 2024 IEEE.

关键词： Adversarial machine learning

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An 8-ENOB Sampling-Rate Reconfigurable Asynchronous SAR ADC for Space Applications

An 8-ENOB Sampling-Rate Reconfigurable Asynchronous SAR ADC ...

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2022 International Conference on Microelectronics, ICM 2022

作者： Karim, Rashid Grassi, Marco Malcovati, Piero University of Pavia Department of Electrical Computer and Biomedical Engineering Italy

ISBN: (纸本)9781665493246

This paper presents a novel architecture and design of an 8-bits Asynchronous Successive-Approximation-Register (ASAR) Analog-to-Digital-Converter (ADC) targeted for multi-channel readout ASICs for space applications. Unlike other ASAR ADCs, this ADC uses a variable delay cell which provides the desired delay only to the rising-edge of the internally generated clock signal. In addition, the ADC has the capability to conFigure its sampling-rate (fs), from typical 40 kS/s to 167 kS/s, with proportional power consumption. Moreover, the proposed architecture is adaptable to the frequency and duty cycle of the only external low duty cycle 'CLKsampling' signal, which can be customized for the desired application. Designed in a 0.35 μm CMOS process with a supply voltage of 3.3 V, the ADC achieves in schematic-level simulations an ENOB of 7.93 bits, a peak SNDR of 49.5 dB, DNL and INL of © 2022 IEEE.

关键词： Space applications

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High-fidelity super-resolution imaging with deconvolution by pixel reassignment (DPR)

High-fidelity super-resolution imaging with deconvolution by...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Zhao, Bingying Mertz, Jerome Department of Electrical and Computer Engineering Boston University MA02215 United States Department of Biomedical Engineering Boston University MA02215 United States

We demonstrated a novel super-resolution analytical approach, deconvolution by pixel reassignment (DPR), which can enhance the spatial resolution in fluorescence microscopy beyond the diffraction limit with high fidel... 详细信息

ISBN: (纸本)9781957171258

关键词： Pixels

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3D phase imaging from intensity measurements with non-paraxial multiple scattering model

3D phase imaging from intensity measurements with non-paraxi...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023

作者： Zhu, Jiabei Tian, Lei Department of Electrical and Computer Engineering Boston University MA02215 United States Department of Biomedical Engineering Boston University MA02215 United States

We propose a novel algorithm based on the split-step non-paraxial model for different intensity diffraction tomography setups to recover the 3D refractive index distribution of multiple-scattering biological samples. ... 详细信息

ISBN: (纸本)9781957171289

关键词： Multiple scattering

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Biomechanical Evaluation of Fingers Repetitive Voluntary Tasks in Chronic Stroke Survivors

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IEEE Access 2023年 11卷 143649-143656页

作者： Adeel, Muhammad Peng, Chih-Wei Lee, I-Jung Lin, Bor-Shing National Taipei University Department of Computer Science and Information Engineering New Taipei City237303 Taiwan Taipei Medical University School of Biomedical Engineering College of Biomedical Engineering Taipei11031 Taiwan Taipei Medical University School of Gerontology and Long-Term Care College of Nursing Taipei11031 Taiwan National Taipei University College of Electrical Engineering and Computer Science New Taipei City237303 Taiwan

A chronic stroke affects hand mobility limiting the normal functioning of the finger joints. The voluntary tasks with a repetitive motion can identify the limitation in the range of motion (ROM) to enhance the hand functioning of stroke survivors. Therefore, we compared two voluntary tasks fast ball squeezing (FBS) and slow ball squeezing (SBS), and analyzed the variability of these tasks for finger pressure and ROM in chronic stroke survivors. An experimental study with 22 healthy and 39 chronic stroke participants was conducted. All of them wore an upper limb motion capture device (UMCD) to record the active (AROM) of finger joints during FBS and SBS tasks for 20 repetitions. The data were analyzed into the joint angle and pressure to compare these tasks and their variability. While comparing the FBS and SBS tasks, left-side pressure and both sides' ROM attained the level of significance (p © 2013 IEEE.

关键词： Joints (anatomy)

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