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arXiv 2022年

作者： Guo, Xiaorang Shaeri, MohammadAli Shoaran, Mahsa Institute of Electrical and Micro Engineering Center for Neuroprosthetics EPFL Geneva1202 Switzerland Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden01069 Germany Chair of Computer Architecture and Parallel Systems Technische Universität München Garching85748 Germany

Spike detection plays a central role in neural data processing and brain-machine interfaces (BMIs). A challenge for future-generation implantable BMIs is to build a spike detector that features both low hardware cost and high performance. In this work, we propose a novel hardware-efficient and high-performance spike detector for implantable BMIs. The proposed design is based on a dual-detector architecture with adaptive threshold estimation. The dual-detector comprises two separate TEO-based detectors that distinguish a spike occurrence based on its discriminating features in both high and low noise scenarios. We evaluated the proposed spike detection algorithm on the Wave_Clus dataset. It achieved an average detection accuracy of 98.9%, and over 95% in high-noise scenarios, ensuring the reliability of our method. When realized in hardware with a sampling rate of 16kHz and 7-bits resolution, the detection accuracy is 97.4%. Designed in 65nm TSMC process, a 256-channel detector based on this architecture occupies only 682µm2/Channel and consumes 0.07µW/Channel, improving over the state-of-the-art spike detectors by 39.7% in power consumption and 78.8% in area, while maintaining a high accuracy. © 2022, CC BY.

关键词： Data handling

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Development and study of the impacts of automated walking aids on the elderly 20

Development and study of the impacts of automated walking ai...

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20th International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Tangjitjetsada, Maleeya Thianthong, Tawan Rakluea, Chawalit Loedhammacakra, Wisit Rakluea, Paitoon Tangthong, Nipont Mahatthanajatuphat, Chatree Chudpooti, Nonchanutt Rajamangala University of Technology Suvarnabhumi Faculty of Engineering and Architecture Department of Electronics and Telecommunication Engineering Nonthaburi Thailand Siam Airport Ground Services Co. Ltd Bangkok Thailand Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand

ISBN: (纸本)9798350310467

Since Thailand has now completely stepped into an aged society there are more than 20% of the population aged 60 years and over. There was also an increase in those who had problems with their balance. One of the main difficulties for these people is walking on their own. This paper presents an automatic walking aid for people with balance or walking problems. A specially designed automatic walking aid can be adjusted to six levels of height. It has an anti-collision warning system at a distance of up to 40 centimeters and displays GPS coordinates via SMS when falling. The experimental results of the prototype automatic walking aid showed that the walking aid could work as designed and could help people with balance problems walk more comfortably. © 2023 IEEE.

关键词： Walking aids

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Techniques to Facilitate the Use of V2I Communication System as Support for Traffic Sign Recognition Algorithms

Techniques to Facilitate the Use of V2I Communication System...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Marzena Banach Rafał Długosz Poznań University of Technology Institute of Architecture and Spatial Planning Poznan Poland Faculty of Telecommunication Computer Science and Electrical Engineering UTP University of Science and Technology Bydgoszcz Poland

Solutions proposed in this work are related to development of vehicle-to-infrastructure (V2I) communication in the context of its support for Traffic Sign Recognition (TSR) algorithms used in advanced driver assistance systems (ADAS). One of the ideas of the application of the V2I communication, proposed in the literature, is to equip traffic signs (TS) with devices, capable of communicate their meaning to passing vehicles equipped with ADAS functions or autonomous vehicles. We propose grouping TSs and covering groups with single road side unit (RSU) devices. It will facilitate implementation and maintenance of the overall system. This will also reduce the amount of data sent over the network.

关键词： Roads Autonomous vehicles Standards Vehicle-to-infrastructure Advanced driver assistance systems Global Positioning System

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest 7

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

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7th International Conference on Advances in Biomedical engineering, ICABME 2023

作者： Daou, Roy Abi Zeid Geha, Elio Aoun, Youssef Hayek, Ali Boercsoek, Josef Olmedo, Jose Javier Serrano Université la Sagesse Biomedical Engineering Department Furn El Chebbak Beirut Lebanon Mart Learning Education and Research Center Chananir Lebanon Lebanese German University Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Germany Universidad Politecnica de Madrid Lab of Bioinstrumentation and Nanomedicine Centro de Tecnologia Biomedica Spain

ISBN: (纸本)9798350325850

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. © 2023 IEEE.

关键词： Wearable technology

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Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type

arXiv

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arXiv 2023年

作者： Müller, Romy Dürschmidt, Marcel Ullrich, Julian Knoll, Carsten Weber, Sascha Seitz, Steffen Faculty of Psychology Chair of Engineering Psychology and Applied Cognitive Research TUD Dresden University of Technology Dresden Germany Faculty of Electrical and Computer Engineering Chair of Fundamentals of Electrical Engineering TUD Dresden University of Technology Dresden Germany Faculty of Mathematics and Natural Sciences Department of Computer Science Machine Learning Group Heinrich-Heine-Universität Düsseldorf Düsseldorf Germany

Deep Learning models like Convolutional Neural Networks (CNN) are powerful image classifiers, but what factors determine whether they attend to similar image areas as humans do? While previous studies have focused on technological factors, little is known about the role of factors that affect human attention. In the present study, we investigated how the tasks used to elicit human attention maps interact with image characteristics in modulating the similarity between humans and CNN. We varied the intentionality of human tasks, ranging from spontaneous gaze during categorization over intentional gaze-pointing up to manual area selection. Moreover, we varied the type of image to be categorized, using either singular, salient objects, indoor scenes consisting of object arrangements, or landscapes without distinct objects defining the category. The human attention maps generated in this way were compared to the CNN attention maps revealed by explainable artificial intelligence (Grad-CAM). The influence of human tasks strongly depended on image type: For objects, human manual selection produced maps that were most similar to CNN, while the specific eye movement task has little impact. For indoor scenes, spontaneous gaze produced the least similarity, while for landscapes, similarity was equally low across all human tasks. To better understand these results, we also compared the different human attention maps to each other. Our results highlight the importance of taking human factors into account when comparing the attention of humans and CNN. © 2023, CC BY.

关键词： Eye movements

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Physics-informed mode decomposition neural network for structured light in multimode fibers

Physics-informed mode decomposition neural network for struc...

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IEEE Photonics Conference (IPC)

作者： Qian Zhang Yuan Sui Stefan Rothe Jürgen Czarske Chair of Measurement and Sensor System Technique Faculty of Electrical and Computer Engineering TU Dresden Dresden Germany School of Science Institute of Applied Physics TU Dresden

We propose a novel approach for the referenceless mode decomposition of multimode fibers. A deep neural network with the interaction of a physical model achieves decomposition of 55 modes without pre-training. This pa...

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Using Eye-Tracking to Evaluate Novel Augmented Reality Applications for Maritime Operations 68th

Using Eye-Tracking to Evaluate Novel Augmented Reality Appli...

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68th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2024

作者： Mallam, Steven C. Attarzadeh, Amin Samanta, Akash Bhattacharjee, Ankan Nordby, Kjetil Fisheries and Marine Institute Memorial University of Newfoundland St. John’sNLA1C 5R3 Canada Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland St. John’s Canada Institute of Design The Oslo School of Architecture and Design Akershus Norway

This paper presents the developments across a multi-year collaborative industry-academia R&D project designing and testing novel Augmented Reality (AR) solutions for differing maritime operations and work tasks. We describe the step-wise approach taken in our Human Factors testing program exploring the effects of AR on maritime operators. This paper focuses specifically on our empirical simulator laboratory experiments using differing data collection designs, tools and operational scenarios to investigate operator Situation Awareness, cognitive workload, performance and usability. Moving from comparatively rudimentary measures using static scenarios, desktop data collections and post hoc video analysis to implementing eye-tracking and automated object identification in dynamic scenarios and full-mission simulated environments, we present an overview of how our testing program has evolved and lessons learned. Further, we discuss ongoing research and future plans to better understand the effects of AR on maritime end-users to implement human-centred solutions more effectively in maritime settings. © 2024 Human Factors and Ergonomics Society.

关键词： Head-up displays

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A moving least-square approach for current slope estimation in an inverter fed IPMSM using field programmable gateway arrays

A moving least-square approach for current slope estimation ...

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International Conference on electrical Machines, ICEM

作者： J. P. Degel S. Haehnlein C. Kloeffer M. Doppelbauer chair of the Electrical Technical Institute (ETI) Karlsruhe Institute of Technology (KIT) of Karlsruhe Germany faculty of electrical engineering medical technology and computer science (EMI) Hochschule Offenburg of Offenburg Germany

ISBN: (数字)9781728199450

ISBN: (纸本)9781728199467

In this work a method for the estimation of current slopes induced by inverters operating interior permanent magnet synchronous machines is presented. After the derivation of the estimation algorithm, the requirements for a suitable sensor setup in terms of accuracy, dynamic and electromagnetic interference are discussed. The boundary conditions for the estimation algorithm are presented with respect to application within high power traction systems. The estimation algorithm is implemented on a field programmable gateway array. This moving least-square algorithm offers the advantage that it is not dependent on vectors and therefore not every measured value has to be stored. The summation of all measured values leads to a significant reduction of the required storage units and thus decreases the hardware requirements. The algorithm is designed to be calculated within the dead time of the inverter. Appropriate countermeasures for disturbances and hardware restrictions are implemented. The results are discussed afterwards.

关键词： Current measurement Switches Voltage measurement Mathematical model Estimation Magnetic field measurement Field programmable gate arrays

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Label-free Identification of Nonelectrogenic Cancer Cells using Adhesion Noise

Label-free Identification of Nonelectrogenic Cancer Cells us...

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BioSensors Conference (BioSensors), IEEE

作者： Maximilian Ell Ralf Zeitler Roland Thewes Günther Zeck TU Wien Faculty of Electrical Engineering and Information Technology Institute of Biomedical Electronics Vienna Austria zerodev Stuttgart Germany TU Berlin Faculty of Electrical Engineering and Computer Science Chair of Sensor and Actuator Systems Berlin Germany

Time-continuous detection of cells on substrates without the need of optical microscopic imaging is of broad interest in biotechnological applications. We present a method how to detect cancer cells using voltage noise caused by cell adhesion which is recorded by high-density CMOS-based microelectrode arrays. We analyze our data in terms of spectral power density for two different types of arrays, each of them being optimized in a different working regime.

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Using the Polar Transform for Efficient Deep Learning-Based Aorta Segmentation in CTA Images

arXiv

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arXiv 2022年

作者： Benčević, Marin Habijan, Marija Galić, Irena Babin, Danilo Faculty of Electrical Engineering Computer Science and Information Technology J. J. Strossmayer University Osijek Croatia imec-TELIN-IPI Faculty of Engineering Architecture Ghent University Belgium

Medical image segmentation often requires segmenting multiple elliptical objects on a single image. This includes, among other tasks, segmenting vessels such as the aorta in axial CTA slices. In this paper, we present a general approach to improving the semantic segmentation performance of neural networks in these tasks and validate our approach on the task of aorta segmentation. We use a cascade of two neural networks, where one performs a rough segmentation based on the U-Net architecture and the other performs the final segmentation on polar image transformations of the input. Connected component analysis of the rough segmentation is used to construct the polar transformations, and predictions on multiple transformations of the same image are fused using hysteresis thresholding. We show that this method improves aorta segmentation performance without requiring complex neural network architectures. In addition, we show that our approach improves robustness and pixel-level recall while achieving segmentation performance in line with the state of the art. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

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