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Remote Motor Rehabilitation: EMG-IMU based Deep Learning Model Improves the Estimate of Wrist Kinematics

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Remote Motor Rehabilitation: EMG-IMU based Deep Learning Mod...

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Ilaria Siviero Florian Helmhold Andreas M. Ray Carlos Bibián Gloria Menegaz Ander Ramos Murguialday Silvia F. Storti Dept. of Computer Science University of Verona Verona Italy Inst. of Medical Psychology and Behavioral Neurobiology University of Tübingen Tübingen Germany GTC of Neuroscience / IMPRS for Cognitive and Systems Neuroscience Tübingen Germany Dept. of Engineering for Innovation Medicine University of Verona Verona Italy TECNALIA Basque Research and Technology Alliance San Sebastian Spain Dept. of Neurology and Stroke University of Tübingen Tübingen Germany Athenea Neuroclinics San Sebastian Spain

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Technology for motor rehabilitation faces challenges in uncontrolled settings, such as at home. In these real-world scenarios, robust signals like electromyographic (EMG) and inertial measurement unit (IMU) data are crucial for decoding continuous human actions. Classical modeling methods, such as linear, adaptive, or static filters, lack the capacity to capture complex relationships between surface EMG and kinematics, as well as generalizability across subjects. We propose a deep learning (DL) model for the continuous decoding of hand motion. Custom-made wearable devices acquired EMG-IMU data from 27 healthy subjects performing a wrist flexion/extension task. Two regression models were compared with a hybrid convolutional neural network and a gated recurrent unit. To address inter-subject variability, a leave-one-subject-out cross-validation approach was implemented. The DL model showed a mean R 2 increase of 0.18 compared to the polynomial regressor. Our approach enhances wrist kinematics decoding providing a generalized model based on data captured with wearable devices. The findings hold potential for innovative home-based telemedicine solutions in motor rehabilitation.

关键词： Wrist Deep learning Adaptation models Biological system modeling Telemedicine Kinematics Motors Electromyography Decoding Wearable devices

Goal-Aware RSS for Complex Scenarios via Program Logic

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arXiv 2022年

作者： Hasuo, Ichiro Eberhart, Clovis Haydon, James Dubut, Jérémy Bohrer, Rose Kobayashi, Tsutomu Pruekprasert, Sasinee Zhang, Xiao-Yi Pallas, Erik André Yamada, Akihisa Suenaga, Kohei Ishikawa, Fuyuki Kamijo, Kenji Shinya, Yoshiyuki Suetomi, Takamasa Tokyo101-8430 Japan Dept. Computer Science Worcester Polytechnic Institute 100 Institute Road WorcesterMA01609-2280 United States Inst. Software & Systems Engineering University of Augsburg Universitätstraße 6a AugsburgD-86135 Germany Cyber Physical Security Research Center AIST Aomi 2-4-7 Tokyo135-0064 Japan Graduate School of Informatics Kyoto University Kyoto606-8501 Japan Mazda Motor Corporation Fuchu730-8670 Japan SOKENDAI The Graduate University for Advanced Studies Japan Tokyo Japan

We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in addition to collision avoidance as in the original RSS—requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules;we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement. © 2022, CC BY-NC-ND.

关键词： computer circuits

SPECTRAL PARTITIONING OF TIME-VARYING NETWORKS WITH UNOBSERVED EDGES

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arXiv 2019年

作者： Schaub, Michael T. Segarra, Santiago Wai, Hoi-To Inst. for Data Systems and Society MIT & Department of Engineering Science University of Oxford Department of Electrical and Computer Engineering Rice University Department of SEEM Chinese University of Hong Kong NT Hong Kong

We discuss a variant of ‘blind’ community detection, in which we aim to partition an unobserved network from the observation of a (dynamical) graph signal defined on the network. We consider a scenario where our observed graph signals are obtained by filtering white noise input, and the underlying network is different for every observation. In this fashion, the filtered graph signals can be interpreted as defined on a time-varying network. We model each of the underlying network realizations as generated by an independent draw from a latent stochastic blockmodel (SBM). To infer the partition of the latent SBM, we propose a simple spectral algorithm for which we provide a theoretical analysis and establish consistency guarantees for the recovery. We illustrate our results using numerical experiments on synthetic and real data, highlighting the efficacy of our approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Time varying networks

A Univariate Persistent Brain Network Feature Based on the Aggregated Cost of Cycles from the Nested Filtration Networks

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A Univariate Persistent Brain Network Feature Based on the A...

IEEE International Symposium on Biomedical Imaging

作者： Mohammad Farazi Liang Zhan Natasha Lepore Paul M. Thompson Yalin Wang School of Computing Informatics and Decision Systems Eng. Arizona State Univ. Tempe AZ Electrical and Computer Engineering Univ. of Pittsburgh Pittsburgh PA CIBORG Lab Children's Hospital Los Angeles Los Angeles CA Imaging Genetics Center Inst. for Neuroimaging and Informatics Univ. of Southern California Los Angeles CA

ISBN: (数字)9781538693308

ISBN: (纸本)9781538693315

A threshold-free feature in brain network analysis can help circumvent the curse of arbitrary network thresholding for binary network conversions. Here, Persistent Homology is the inspiration for defining a new aggregation cost based on the number of cycles, or for tracking the first Betti number in a nested filtration network within the graph. Our theoretical analysis shows that the proposed aggregated cost of cycles (ACC) is monotonically increasing and thus we define a univariate persistent feature based on the shape of ACC. The proposed statistic has advantages compared to the First Betti Number Plot (BNP1), which only tracks the total number of cycles at each filtration. We show that our method is sensitive to both the topology of modular networks and the difference in the number of cycles in a network. Our method outperforms its counterparts in a synthetic dataset, while in a realworld one it achieves results comparable with the BNP1. Our proposed framework enriches univariate measures for discovering brain network dissimilarities for better categorization of distinct stages in Alzheimer's Disease (AD).

关键词： Topology Indexes Network topology Diffusion tensor imaging Shape Biomedical imaging

Relations Between Evaluations of NIST Tests and Lyapunov Exponents of Sequences Generated by the Piecewise Logistic Map over Integers

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Relations Between Evaluations of NIST Tests and Lyapunov Exp...

International Workshop on Signal Design and Its Applications in Communications (IWSDA)

作者： Sota Eguchi Takeru Miyazaki Shunsuke Araki Satoshi Uehara Yasuyuki Nogami Graduate School of Environmental Engineering The Univ. of Kitakyusyu Faculty of Environmental Engineering The Univ. of Kitakyushu Faculty of Computer Science and Systems Engineering Kyushu Inst. of Technology Graduate School of Natural Science and Technology Okayama University

In this paper, we focus on binary sequences obtained from piecewise logistic map over integers, and show the relation between the Lyapunov exponents of the maps and results of the NIST tests for the sequences. When the Lyapunov exponent is a negative value, we confirm that the branch diagram is sparse and the bit occurrence rate is also greatly biased. We also give a sample of that the positive/negative signs of the Lyapunov exponents mostly coincide on the evaluations of the NIST tests. From the branching diagram of the piecewise logistic map, we can moreover find that there are many good pseudorandom sequences generated by the individual control parameters of the map.

关键词： Logistics NIST Bifurcation Generators Environmental engineering Random sequences Indexes

Ultrahigh bandwidth applications of microcombs: Neural networks and optical data transmission

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TechRxiv

TechRxiv 2021年

作者： Moss, David J. Tan, M. Xu, X. Corcoran, B. Wu, J. Boes, A. Nguyen, T. Chu, S. Little, B. Morandotti, R. Mitchell, A. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Department of Physics City University of Hong Kong Tat Chee Avenue Hong Kong Xi’an Institute of Optics and Precision Mechanics Precision Mechanics of CAS Xi’an China INRS-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada Inst. of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

We report ultrahigh bandwidth applications of Kerr microcombs to optical neural networks and to optical data transmission, at data rates from 44 Terabits/s (Tb/s) to approaching 100 Tb/s. Convolutional neural networks (CNNs) are a powerful category of artificial neural networks that can extract the hierarchical features of raw data to greatly reduce the network complexity and enhance the accuracy for machine learning tasks such as computer vision, speech recognition, playing board games and medical diagnosis [1-7]. Optical neural networks can dramatically accelerate the computing speed to overcome the inherent bandwidth bottleneck of electronics. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency with an extremely low spacing of 48.9 GHz. We demonstrate a universal optical vector convolutional accelerator operating at 11 Tera-OPS/s (TOPS) on 250,000 pixel images for 10 kernels simultaneously — enough for facial image recognition. We use the same hardware to sequentially form a deep optical CNN with ten output neurons, achieving successful recognition of full 10 digits with 900 pixel handwritten digit images. We also report world record high data transmission over standard optical fiber from a single optical source, at 44.2 Terabits/s over the C-band, with a spectral efficiency of 10.4 bits/s/Hz, with a coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. Our work demonstrates the ability of optical soliton crystal micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications. © 2021, CC0.

关键词： Diagnosis

FairSearch: A tool for fairness in ranked search results

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arXiv 2019年

作者： Zehlike, Meike Castillo, Carlos Sühr, Tom Kitanovski, Ivan Humboldt Universität zu Berlin Max Planck Inst. for Software Systems Germany Universitat Pompeu Fabra Spain Technische Universität Berlin Germany Faculty of Computer Science and Engineering University Saint Cyril and Methodius Macedonia

Ranked search results and recommendations have become the main mechanism by which we find content, products, places, and people online. With hiring, selecting, purchasing, and dating being increasingly mediated by algorithms, rankings may determine business opportunities, education, access to benefits, and even social success. It is therefore of societal and ethical importance to ask whether search results can demote, marginalize, or exclude individuals of unprivileged groups or promote products with undesired features. In this paper we present FairSearch, the first fair open source search API to provide fairness notions in ranked search results. We implement two well-known algorithms from the literature, namely FA*IR (Zehlike et al., [2017]) and DELTR (Zehlike and Castillo, [2018]) and provide them as stand-alone libraries in Python and Java. Additionally we implement interfaces to Elasticsearch for both algorithms, a well-known search engine API based on Apache Lucene. The interfaces use the aforementioned Java libraries and enable search engine developers who wish to ensure fair search results of different styles to easily integrate DELTR and FA*IR into their existing Elasticsearch environment. Copyright © 2019, The Authors. All rights reserved.

关键词： Search engines

Properties of Knuth’s Quadratic Congruential Sequences with Modulus m = 2W p

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Properties of Knuth’s Quadratic Congruential Sequences with...

International Workshop on Signal Design and Its Applications in Communications (IWSDA)

作者： Takeru Miyazaki Shunsuke Araki Kohei Kawase Satoshi Uehara Yasuyuki Nogami Faculty of Environmental Engineering The University of Kitakyushu Kitakyushu Fukuoka Japan Faculty of Computer Science and Systems Engineering Kyushu Inst. of Technology Iizuka Fukuoka Japan Graduate School of Environmental Engineering The University of Kitakyushu Kitakyushu Fukuoka Japan Graduate School of Natural Science and Technology Okayama University Okayama Japan

The following topics are dealt with: binary sequences; set theory; computational complexity; matrix algebra; correlation methods; polynomials; error statistics; binary codes; random sequences; linear codes.

关键词：

Terahertz dynamic aperture imaging at stand-off distances using a compressed sensing protocol

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arXiv 2019年

作者： Augustin, S. Jung, P. Frohmann, S. Hübers, H.-W. Dept. of Phys. Humboldt-Univ. zu Berlin and the Inst. of Optical Sensor Syst. of the Ger. Aerosp. Ctr. Berlin Department of Electrical Engineering and Computer Science Technische Universität Berlin Institute of Optical Sensor Systems of the German Aerospace Center Berlin

In this text, results of a 0:35 terahertz (THz) dynamic aperture imaging approach are presented. The experiments use an optical modulation approach and a single pixel detector at a stand-off imaging distance of ≈1m. The optical modulation creates dynamic apertures of 5cm diameter with ≈2000 individually controllable elements. An optical modulation approach is used here for the first time at a large far-field distance, for the investigation of various test targets in a fieldof-view of 8 x 8cm. The results highlight the versatility of this modulation technique and show that this imaging paradigm is applicable even at large far-field distances. It proves the feasibility of this imaging approach for potential applications like stand-off security imaging or far field THz microscopy. Copyright © 2019, The Authors. All rights reserved.

关键词： Light modulators