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Brain-Machine Based Rehabilitation Motor Interface and Design Evaluation for Stroke Patients 1

引用

Proceedings of the 20th Web Information Systems and Applications Conference, WISA 2023

作者： Cai, Jiayi Cai, Jialiang Faculty of Humanities and Arts Macau University of Science and Technology China Macao Institute of Materials Science and Engineering Macau University of Science and Technology China

ISBN: (数字)9789819962228

ISBN: (纸本)9789819962211

Based on the brain-computer interface is an important way of existing and future medical rehabilitation medicine, based on post-stroke motor rehabilitation plays a very important role, researchers through the study and clinical brain-computer interface experiments and evaluation of the way, can improve 18% the efficiency of rehabilitation. The intention of the movement is converted into electrical signals that the machine can recognize and interact with the body to achieve active control of the patient. A technology that helps patients in the rehabilitation period to regain their motor functions and self-care abilities. In this paper, a brain-machine interface-based upper limb motor rehabilitation training system is designed, which uses brain-machine fusion as the rehabilitation motor therapy model and combines the muscle strength and movement morphology characteristics of the upper limb on the hemiplegic side of the patient. This study is based on the first clinical trial application of this system, and the focus was validated and improved in all six patients who were followed up. This study was designed from the perspective of combining a brain-machine interface system and upper limb rehabilitation assistive robot system, and combined with the human-computer interaction platform to apply this wearable upper limb movement prosthesis for the disabled in clinical trials for rehabilitation training and assistive therapy, providing effective guidance and assistance for patients with such needs. The research results of this paper have been patented and granted. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Brain computer interface

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Constrained Graph Searching on Trees 1

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17th International Joint Conference on Theoretical computer science - Frontier of Algorithmic Wisdom, IJTCS-FAW 2023

作者： Wang, Lusheng Yang, Boting Zhan, Zhaohui Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong Department of Computer Science University of Regina ReginaSK Canada City University of Hong Kong Shenzhen Research Institution Shenzhen China

ISBN: (数字)9783031393440

ISBN: (纸本)9783031393433

Megiddo et al. (1988) introduced the edge searching problem, which is to find the minimum number of searchers to capture the robber in the edge searching model. Dyer et al. (2008) introduced the fast searching problem that is to find the minimum number of searchers to capture the robber in the fast searching model. In this paper, we consider these two graph searching problems under some constraints. One constraint is that a subset of vertices, called start vertices, are initially occupied by searchers before we place additional searchers on the graph. Another constraint is that some of the searchers must end their search at certain vertices called halt vertices. We focus on trees with n vertices. Let k be the number of times to move searchers from start vertices. For the edge searching problem, we give an O(kn)-time algorithm for computing the edge search number of a tree that contains only start vertices or only halt vertices. For a tree that contains both start vertices and halt vertices, we present an O(n2) -time algorithm to compute the edge search number. We show that all these problems are monotonic. For the fast searching problem, we propose a linear-time algorithm for computing the fast search number of a tree that contains only start vertices or only halt vertices. For a tree with n vertices that contains s start vertices and h halt vertices, we give an O((s+ h) n) -time algorithm to compute the fast search number. © 2023, Springer Nature Switzerland AG.

关键词： Clustering algorithms

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Named Entity Recognition to Extract Knowledge from Clinical Texts 4th

Named Entity Recognition to Extract Knowledge from Clinica...

引用

4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Scarpino, Ileana Vallelunga, Rosarina Luzza, Francesco Department of Medical and Surgical Sciences University of Catanzaro Catanzaro Italy Department of Health Science University of Catanzaro Catanzaro Italy

ISBN: (纸本)9783031812460

Clinical texts encompass a wide range of information such as patient’s history, disease diagnosis and prescribed drugs, reflecting details and nuances that are valuable in providing knowledge. In the present study, a Natural Language Processing approach, specifically Named Entity Recognition (NER), is applied to extract important concepts from gastroenterology clinical texts. NER is a task of text analytics to identify, in written documents, named entities ranging from general concepts to information in specific fields. The application is performed through freely available Python packages of the spaCy library adapted to the English language. Although the spaCy’s NER is generic, models trained in the clinical domain are used to identify categories belonging to the medical sector of interest. In particular, the main goal is to find as much entities as possible by paying attention to major bowel diseases, such as Ulcerative Colitis and Crohn’s disease. We performed two experiments, the first one involves the use of the ScispaCy package for scientific text processing. The second one applies Med7 that is a spaCy NER model for labeling drug information trained for identification of seven medication-related concepts, dosage, drug names, duration, form, frequency, route of administration, and strength. The results show that two approaches applied for NER analysis perform well to extract knowledge from gastroenterology clinical texts. The results obtained will allow to evaluate the efficiency of the proposed methodology and to analyze, through the extracted entities, the profile and aspects of the diseases considered and the associated drugs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gastroenterology

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Physics-Informed Neural Networks for Solar Wind Prediction 1

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26th International Conference on Pattern Recognition, ICPR 2022

作者： Johnson, Rob Boubrahimi, Soukaïna Filali Bahri, Omar Hamdi, Shah Muhammad Department of Computer Science Utah State University LoganUT84322 United States

ISBN: (数字)9783031377310

ISBN: (纸本)9783031377303

Solar wind modeling is categorized into empirical and physics-based models that both predict the properties of solar wind in different parts of the heliosphere. Empirical models are relatively inexpensive to run and have shown great success at predicting the solar wind at the L1 Lagrange point. Physics-based models provide more sophisticated scientific modeling based on magnetohydrodynamics (MHD) that are computationally expensive to run. In this paper, we propose to combine empirical and physics-based models by developing a physics-guided neural network for solar wind prediction. To the best of our knowledge, this is the first attempt to forecast solar wind by combining data-driven methods with physics constraints. Our results show the superiority of our physics-constrained model compared to other state-of-the-art deep learning predictive models. © 2023, Springer Nature Switzerland AG.

关键词： Deep learning

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Parallelize Accelerated Triangle Counting Using Bit-Wise on GPU 1

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Proceedings of the 20th Web Information Systems and Applications Conference, WISA 2023

作者： Lin, Li Ouyang, Dian He, Zhipeng Li, Chengqian School of Computer Science and Network Engineering Guangzhou University Guangzhou China

ISBN: (数字)9789819962228

ISBN: (纸本)9789819962211

Triangle counting is a graph algorithm that calculates the number of triangles in a graph, the number of triangles is a key metric for a large number of graph algorithms. Traditional triangle counting algorithms are divided into vertex-iterator and edge-iterator when traversing the graph. As the scale of graph data grows, the use of CPU with other architectural platforms for triangle counting has become mainstream. Our accelerating method proposes an algorithm for triangle counting on a single machine GPU, and performs a two-dimensional partition algorithm for large-scale graph data, in order to ensure that large graph data can be correctly loaded into GPU memory and the independence of each partition to obtain the right result. According to the high concurrency of GPU, a bit-wise operation intersection algorithm is proposed. We experiment with our algorithm to verify that our method effectively speeds up triangle counting algorithm on a single-machine GPU. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graphics processing unit

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Jointly Learning Structure-Augmented Semantic Representation and Logical Rules for Knowledge Graph Completion 1

引用

Proceedings of the 20th Web Information Systems and Applications Conference, WISA 2023

作者： Jiang, Jinxing Xu, Lizhen School of Computer Science and Engineering Southeast University Jiangsu Nanjing211189 China

ISBN: (数字)9789819962228

ISBN: (纸本)9789819962211

Knowledge Graph Complementation (KGC) aims to predict the missing triples in incomplete knowledge graphs (KGs). However, existing approaches rely either on structural features, semantic features or logical rules. There is not yet a unified way to exploit all three features mentioned above. To address this problem, this paper proposes a new KGC framework, SSL, which jointly embeds structure-augmented semantics representation in the natural language description of triples with their logical rules. First, SSL fine-tunes a pre-trained language model to capture the semantic information in the natural language description corresponding to the triple. Then, for logical rules corresponding to different relation types, we augment them to embeddings of entities and relations to activate stronger representation capabilities. Finally, by jointly training, we can obtain more expressive embeddings for the downstream KGC task. Our extensive experiments on a variety of KGC benchmarks have demonstrated the effectivity of our method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Knowledge graph

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ITAQ: Image Tag Recommendation Framework for Aquatic Species Integrating Semantic Intelligence via Knowledge Graphs 1

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5th Iberoamerican and the 4th Indo-American Knowledge Graphs and Semantic Web Conference, KGSWC 2023

作者： Nitin Hariharan, S.S. Deepak, Gerard Ortiz-Rodríguez, Fernando Panchal, Ronak Department of Computer Science and Engineering Alagappa Chettiar Government College of Engineering and Technology Karaikudi India Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Universidad Autonoma de Tamaulipas Ciudad Victoria Mexico Cognizant Technology Solutions Pune India

ISBN: (数字)9783031477454

ISBN: (纸本)9783031477447

In the era of Web 3.0, there is an increasing demand for social image tagging that incorporates knowledge-centric paradigms and adheres to semantic web standards. This paper introduces the ITAQ framework, a recommendation framework specifically designed for tagging images of aquatic species. The framework continuously integrates strategic knowledge curation and addition at various levels, encompassing topic modelling, metadata generation, metadata classification, ontology integration, and enrichment using knowledge graphs and sub graphs. The ITAQ framework calculates context trees from the enriched knowledge dataset using AdaBoost classifier which is a lightweight machine learning classifier. The CNN classifier handles the metadata, ensuring a well-balanced fusion of learning paradigms while maintaining computational feasibility. The intermediate derivation of context trees, computation of KL divergence, and Second Order Co-occurrence PMI contribute to semantic-oriented reasoning by leveraging semantic relatedness. The Ant Lion optimization is utilized to compute the most optimal solution by building upon the initial intermediate solution. Finally, the optimal solution is correlated with image tags and categories, leading to the finalization of labels and annotations. An overall precision of 94.07% with the lowest value of FDR of 0.06% and accuracy of 95.315 % has been achieved by the proposed work. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Adaptive boosting

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Unifying Reality and Virtuality: Constructing a Cohesive Metaverse Using Complex Numbers 1

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4th International Conference on Spatial Data and Intelligence, SpatialDI 2023

作者： Li, Haibo Department of Media Technology and Interaction Design School of Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

ISBN: (数字)9783031329104

ISBN: (纸本)9783031329098

In this position paper we present a novel mathematical framework for building metaverses, which is a potential way to unify reality and virtuality to create a cohesive whole universe. We argue that the nature of metaverses is inherently mathematical, and propose that the system of complex numbers could play a key role in constructing them. Specifically, we provide context for our argument and offer a supporting example, the analytic signal, to demonstrate how to construct its imaginary counterpart with the Hilbert transform to a given real signal and how to unify them to form a cohesive complex signal that facilitates the analysis of local dynamic behaviors of the signal. This framework has significant potential for building a metaverse. By leveraging the power of complex numbers, one can create a unified mathematical system that merges the physical and virtual worlds. We believe that this proposal will inspire further research and development of metaverses in this field and that our framework will contribute to the construction of a metaverse that offers unprecedented levels of interactivity and immersion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtual reality

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The Smart Coverage Path Planner for Autonomous Drones Using TSP and Tree Selection 1

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9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023

作者： Sundarrajan, M. Jothi, Akshya Prabakar, D. Kadry, Seifedine SRM Institute of Science and Technology Chennai India Department of Applied Data Science Noroff University College Kristiansand Norway Ajman University Ajman346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

ISBN: (数字)9783031440847

ISBN: (纸本)9783031440830

The problem of efficiently covering an area with a limited number of sensors or cameras is an important research topic in various fields such as surveillance, monitoring, and inspection. This problem can be posed as a Traveling Salesman Problem (TSP), where the optimal path needs to be found to visit all the coverage points and return to the starting point. However, the computational complexity of solving TSP increases exponentially with the number of coverage points, making it impractical for large-scale applications. This paper proposes a novel approach to solving the coverage problem as a TSP by incorporating tree selection algorithms to improve efficiency and accuracy. The proposed approach represents the study area as a graph, with each node representing a coverage point and the edges representing the distance between them. To reduce computational complexity, we use various tree selection algorithms to select the best possible starting point for the TSP algorithm. To evaluate the effectiveness of the proposed approach, we conduct simulations using different scenarios with varying numbers of coverage points. The simulation results demonstrate that the proposed approach significantly improves the quality of coverage while reducing computational complexity compared to traditional TSP algorithms. Moreover, the proposed approach can be applied in a wide range of real-world applications, such as surveillance, monitoring, or inspection, where efficient and accurate coverage of an area is essential. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Drones

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A Real-Time Support with Haptic Feedback for Safer Driving Using Monocular Camera 23rd

A Real-Time Support with Haptic Feedback for Safer Driving...

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23rd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2024

作者： De Magistris, Giorgio Guercio, Lorenzo Starna, Francesco Russo, Samuele Kryvinska, Natalia Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome via Ariosto 25 Rome00185 Italy Department of Psychology Sapienza University of Rome via Dei Marsi 78 Roma00185 Italy Faculty of Management Comenius University in Bratislava Bratislava Slovakia

ISBN: (纸本)9783031806063

Each year, car accidents impact billions of people, resulting in numerous casualties. Consequently, road safety remains a top priority for nations worldwide. This project aims to enhance driver safety through a feedback system that relies solely on a monocular camera mounted atop the vehicle. The proposed system is a real-time application designed to warn drivers of imminent road hazards, which are classified by their level of risk. Our method employs various computer vision techniques and incorporates a simple 2D-3D correspondence to estimate the longitudinal and lateral distances of objects ahead of the vehicle, under certain simplifying assumptions. The system conducts a comprehensive danger analysis by evaluating potential hazards within the vehicle’s path. Depending on the danger level, warnings are delivered to the driver with varying degrees of invasiveness, using haptic feedback. The proposed method was tested on the KITTI dataset, yielding positive results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hazards

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