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Home monitoring of motor fluctuations in Parkinson’s disease patients

Journal of Reliable Intelligent Environments 2019年第3期5卷 145-162页

作者： Borzì, Luigi Varrecchia, Marilena Olmo, Gabriella Artusi, Carlo Alberto Fabbri, Margherita Rizzone, Mario Giorgio Romagnolo, Alberto Zibetti, Maurizio Lopiano, Leonardo Department of Control and Computing Engineering Politecnico di Torino Turin Italy Department of Neuroscience Rita Levi Montalcini University Hospital Città della Salute e della Scienza Regional Reference Center for Parkinson’s Disease and Movement Disorders Turin Italy

In Parkinson’s disease, motor fluctuations (worsening of tremor, bradykinesia, freezing of gait, postural instability) affect up to 70% of patients within 9 years of L-dopa therapy. Nevertheless, the assessment of motor fluctuations is difficult in a medical office, and is commonly based on poorly reliable self-reports. Hence, the use of wearable sensors is desirable. In this preliminary trial, we have investigated bradykinesia and freezing of gait—FOG—symptoms by means of inertial measurement units. To this purpose, we have employed a single smartphone on the patient’s waist for FOG experiment (38 patients), and on patient thigh for LA (93 subjects). Given the sound performance achieved in this trial (AUC = 0.97 for FOG and AUC = 0.92 for LA), motor fluctuations may be estimated in domestic environments. To this end, we plan to perform measures and data processing on SensorTile, a tiny IoT module including several sensors, a microcontroller, a BlueTooth low-energy interface and microSD card, implementing an electronic diary of motor fluctuations, posture and dyskinesia during activity of daily living. © 2019, The Author(s).

关键词： Wearable sensors

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Automatic identification of hypertension and assessment of its secondary effects using artificial intelligence: A systematic review (2013–2023)

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Computers in Biology and Medicine 2024年 172卷 108207-108207页

作者： Gudigar, Anjan Kadri, Nahrizul Adib Raghavendra, U. Samanth, Jyothi Maithri, M. Inamdar, Mahesh Anil Prabhu, Mukund A. Hegde, Ajay Salvi, Massimo Yeong, Chai Hong Barua, Prabal Datta Molinari, Filippo Acharya, U. Rajendra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Cardiovascular Technology Manipal College of Health Professions Manipal Academy of Higher Education Manipal576104 India Department of Mechatronics Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Department of Cardiology Kasturba Medical College Manipal Academy of Higher Education Manipal576104 India Manipal Hospitals Karnataka Bengaluru560102 India Biolab PolitoBIOMedLab Department of Electronics and Telecommunications Politecnicodi Torino Turin Italy School of Medicine Faculty of Health and Medical Sciences Taylor's University Subang Jaya47500 Malaysia Cogninet Brain Team Cogninet Australia SydneyNSW2010 Australia Faculty of Business Education Law & Arts University of Southern Queensland ToowoombaQLD4350 Australia Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia School of Mathematics Physics and Computing University of Southern Queensland SpringfieldQLD4300 Australia Centre for Health Research University of Southern Queensland ToowoombaQLD4350 Australia

Artificial Intelligence (AI) techniques are increasingly used in computer-aided diagnostic tools in medicine. These techniques can also help to identify Hypertension (HTN) in its early stage, as it is a global health issue. Automated HTN detection uses socio-demographic, clinical data, and physiological signals. Additionally, signs of secondary HTN can also be identified using various imaging modalities. This systematic review examines related work on automated HTN detection. We identify datasets, techniques, and classifiers used to develop AI models from clinical data, physiological signals, and fused data (a combination of both). Image-based models for assessing secondary HTN are also reviewed. The majority of the studies have primarily utilized single-modality approaches, such as biological signals (e.g., electrocardiography, photoplethysmography), and medical imaging (e.g., magnetic resonance angiography, ultrasound). Surprisingly, only a small portion of the studies (22 out of 122) utilized a multi-modal fusion approach combining data from different sources. Even fewer investigated integrating clinical data, physiological signals, and medical imaging to understand the intricate relationships between these factors. Future research directions are discussed that could build better healthcare systems for early HTN detection through more integrated modeling of multi-modal data sources. © 2024 The Authors

关键词： Medical imaging

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Simulations and Experiments of Time-Varying Takagi Factorization via Zhang Neural Network

Simulations and Experiments of Time-Varying Takagi Factoriza...

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IEEE Advanced Information Technology, Electronic and Automation control Conference (IAEAC)

作者： Zanyu Tang Tianyu Zeng Zhenyu Li Jianrong Chen Yunong Zhang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Modern Control Technology Guangzhou China College of Information Science and Engineering Jishou University Jishou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China School of Public Health Administration Youjiang Medical University for Nationalities Baise China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

The problem of Takagi factorization (TF) for complex time-varying symmetric matrix is proposed in this paper. To solve this difficult and challenging problem, a continuous-time TF (CTTF) model of derivative equation system form is proposed via Zhang neural network (ZNN) method. For the sake of digital hardware implementation, we also build up the corresponding discrete-time (DT) ZNN solution models with different precisions of the derivative equation system discretization. Specifically, an eight-instant DTTF (EIDTTF) model are proposed. We also comparatively use two other multi-instant (e.g., four-instant and six-instant, i.e., FIDTTF and SIDTTF, respectively) models by discretizing the CTTF model. The effective solution step-size intervals of the proposed DTTF models are further discussed lastly. The results of simulations and experiments substantiate the correctness, effectiveness and superiority of the proposed CTTF and DTTF models.

关键词： Symmetric matrices Conferences Neural networks Hardware Numerical models Mathematical model Information technology

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The development of pineapple leaf diseases classification using convolutionary neural network for mobile apps

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AIP Conference Proceedings 2024年第1期3135卷

作者： Muhammad Najmi Hasnol Mizam Sulaiman Mahzan Siti Fairuz Nurr Sadikan Mohd Ab Malek Md Shah Mohd Aliff Afira Sani College of Computing Informatics & Mathematic Universiti Teknologi MARA Melaka Malaysia. Faculty of Plantation & Agrotechnology Universiti Teknologi MARA Melaka Malaysia. Department of Law Universiti Teknologi MARA Melaka Malaysia. Department of Instrumentation and Control Engineering Universiti Kuala Lumpur Johore Malaysia.

Pineapple diseases are linked to worms, viruses, bacteria, and fungi. Insects including ants, scales, mealybugs, and souring beetles are some of the most prevalent pests that can harm the pineapple industry over time if early pineapple leaf disease detection is not made There are many smallholders especially in the rural area who lack of latest technology, knowledge, and experience about pineapple disease treatment and management. Thus, lack of a precise diagnosis method prevents them from understanding the disease and creates an effective control for its spread. This issue further impacts the effectiveness of pineapple production, subsequently affecting their income and the country’s, as well as jeopardizing national food security. This study presents an innovative approach aimed at enhancing early detection and management of pineapple leaf diseases by integrating a Convolutional Neural Network (CNN) algorithm and import it using TensorFlow Lite into an android mobile. The CNN model achieved an impressive total accuracy of 98% in precisely classifying three types of pineapple leaf diseases: Leaf Spot, Mealybug Wilt, and Pink Disease. When implemented in the mobile application, the system attained an overall confidence of 83.33% by leveraging both camera-captured and gallery images. Although the accuracy gained is impressive, additional research and adjustments can be conducted to improve the system’s performance and achieve even higher levels of accuracy.

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Cavity-Quantum Electrodynamics with Moiré Flatband Photonic Crystals

arXiv

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arXiv 2024年

作者： Wang, Yu-Tong Ye, Qi-Hang Yan, Jun-Yong Qiao, Yufei Chen, Chen Cheng, Xiao-Tian Li, Chen-Hui Zhang, Zi-Jian Huang, Cheng-Nian Meng, Yun Zou, Kai Zhan, Wen-Kang Zhao, Chao Hu, Xiaolong Tee, Clarence Augustine T.H. Sha, Wei E.I. Huang, Zhixiang Liu, Huiyun Jin, Chao-Yuan Ying, Lei Liu, Feng State Key Laboratory of Extreme Photonics and Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China School of Physics Zhejiang Key Laboratory of Micro-nano Quantum Chips and Quantum Control Zhejiang University Hangzhou310027 China School of Precision Instrument and Optoelectronic Engineering Tianjin University Tianjin300072 China Key Laboratory of Optoelectronic Information Science and Technology Ministry of Education Tianjin300072 China Laboratory of Solid State Optoelectronics Information Technology Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Science Beijing101804 China College of Physics and Electrical Information Engineering Zhejiang Normal University Hangzhou310058 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom International Joint Innovation Center Zhejiang University Haining314400 China

Quantum emitters are a key component in photonic quantum technologies. Enhancing their single-photon emission by engineering the photonic environment using cavities can improve the overall efficiency in quantum information processing. However, this enhancement is often limited by the need for precise nanoscale control over emitter’s position within micro/nano-cavities. Inspired by the fascinated physics of moiré pattern, we present an approach to strongly modify the spontaneous emission rate of a quantum emitter using fine-designed multilayer moiré photonic crystal with a robust isolate-flatband dispersion. Theoretical analysis reveals that due to its nearly infinite photonic density of states, the moiré cavity can simultaneously possess high Purcell factor and large tolerance over emitter’s position. We experimentally demonstrate the coupling between this moiré cavity and a quantum dot via the cavity-determined polarization of the dot’s emission. The radiative lifetime of the quantum dot can be tuned by a factor of 40 from 42 ps to 1692 ps, attributed to strong Purcell enhancement and Purcell inhibition effects. Our findings pave the way for moiré flatband cavity-enhanced quantum light sources, quantum optical switches and quantum nodes for quantum internet. Copyright © 2024, The Authors. All rights reserved.

关键词： Particle beams

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Fuzzy Event-triggered Disturbance Rejection control of Nonlinear Systems

Fuzzy Event-triggered Disturbance Rejection Control of Nonli...

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第31届中国过程控制会议（CPCC 2020）

作者： Peng Cheng Yanyan Yin Yanqing Liu Feng Pan Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things Jiangnan University School of Electrical Engineering Computing and Mathematical SciencesCurtin University

In this paper, we describe a novel method for constructing fuzzy based event-triggered disturbance rejection control for nonlinear systems. A new fuzzy event based anti-disturbance controller is designed and a reduced order disturbance observer is constructed. Sufficient conditions for the closed loop system to be asymptotically stable under an H∞ performance index are derived. Based on these conditions, the design of a fuzzy event-triggered state feedback controller is formulated and *** results are presented to demonstrate the correctness and effectiveness of our theoretical findings.

关键词： Fuzzy system Nonlinear systems Event trigger Disturbance rejection Asymptotically stable

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A New Perspective of Graph Data and A Generic and Efficient Method for Large Scale Graph Data Traversal

arXiv

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arXiv 2020年

作者： Zhang, Chenglong State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China

The BFS algorithm is a basic graph data processing algorithm and many other graph data processing algorithms have similar architectural features with BFS algorithm and can be built on the basis of BFS algorithm model. We analyze the differences between graph algorithms and traditional high-performance algorithms in detail, propose a new way of classifying algorithms into data independent algorithm and data correlation algorithm based on their run-time correlation with data, and use this new classification to explain the validity of the methods proposed in this paper. Through a deeper analysis of graph data, we propose a new fundamental perspective on understanding graph data, establishing a link between two basic data structures, graph and tree, and viewing graph data as consisting of smaller subgraphs and edge trees. Small degree vertices are found to be one of important cause of random memory access. Based on this, we propose a general, easy to implement, and efficient method for graph data processing, with the basic idea of treating low-degree vertices and core subgraphs separately, thus significantly reducing the size of random memory access and improving the efficiency of memory access. Finally, we evaluated the performance of the method on three major data center computing platforms (Intel, AMD, and ARM), and the experiments showed that it brought 19.7%, 31.8% and 17.9% performance improvement, respectively, with a performance-power ratio of 282.70 MTEPS/s on the ARM platform, ranking it among the Green graph500 in November 2019. World No. 1 on the big dataset list. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph algorithms

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Visual defect detection for historical building preservation

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Expert Systems with Applications 2025年 291卷

作者： Cheng, Mengqiu Zhang, Xinting Xia, Leihua Chen, Junming Xie, Jiayuan Ma, Zongfang Li, Qing School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Xi'an China School of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Department of Computing Hong Kong Polytechnic University Hong Kong SAR China Faculty of Humanities and Arts Macau University of Science and Technology Macau China Department of Mathematics The University of Hong Kong Hong Kong SAR China

Advancements in automated building defect detection technology are essential for preserving historical architecture. Although existing intelligent technologies have made notable progress in detecting defects in modern residential buildings, their application to historical buildings faces significant challenges due to the complexity of structures, material diversity, and long-term natural and human-induced deterioration. This study focuses on historical buildings in Guangzhou, China, and introduces a dedicated task for detecting defects in such buildings. To support this task, a high-quality, customized dataset has been developed as a research foundation. To address challenges such as image blurriness during data collection and the complex structural characteristics of historical buildings, this study proposes a baseline model named Deblur-DetNet. The model employs a two-stage approach that integrates image deblurring and defect detection, significantly enhancing both accuracy and robustness. Experimental results demonstrate that the proposed method performs exceptionally well in the task of historical building defect detection, particularly in identifying fine-grained defects. This research provides robust technical support for the protection and restoration of historical buildings and establishes a solid foundation for further studies in cultural heritage preservation. Our dataset is available at https://***/file/d/1-9NiAw0hzomWHOA9RMEMXOOwIq5HScPx/view?usp=sharing. © 2025

关键词： Computer vision Defect detection Historical building Image deblurring technology

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ZND-ZeaD Models and Theoretics Including Proofs for Takagi Factorization of Complex Time-Dependent Symmetric Matrix

ZND-ZeaD Models and Theoretics Including Proofs for Takagi F...

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第33届中国控制与决策会议

作者： Zhuosong Fu Min Yang Jinjin Guo Jianrong Chen Yunong Zhang School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education School of Electronics and Information Technology Sun Yat-sen University School of Public Health and Management Youjiang Medical University for Nationalities

Takagi factorization(TF) is a kind of matrix factorization(also termed,decomposition) *** this paper,the problem of TF for complex time-dependent symmetric matrix(simply termed,time-dependent Takagi factorization)is presented and theoretically *** simplify the tough problem,we first consider converting it into an equivalent equation ***,a continuous-time(CT) TF(CTTF) model is presented and derived theoretically,by adopting ZND(Zhang neural dynamics,or termed,Zhang neural network) method and a dimensional reduction *** order to facilitate the implementation on digital hardware platforms,the corresponding discrete-time(DT) ZND solution models(or termed,algorithms) with different discretization precisions of the CTTF model are presented and taken into theoretical ***,we present and investigate a discrete-time TF(DTTF) model,termed eight-instant DTTF(8IDTTF) model,by using a new eight-instant Zhang et al discretization(ZeaD,also termed,Zhang time discretization,ZTD) formula to discretize the CTTF ***,two other DTTF models,termed four-instant DTTF(4IDTTF) and six-instant DTTF(6IDTTF) models,are presented respectively,on the basis of two corresponding multiinstant ZeaD ***,the effective solution step-size intervals of the three DTTF models are further presented and proved.

关键词： Time-dependent Takagi factorization Dimensional reduction Zhang neural dynamics(ZND) Kronecker product Zhang et al discretization(ZeaD) formulas

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Underwater Sensor Network Clock Synchronization Algorithm Based on Markov Chain Group Consistency

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Ruan Jian Xue Bao/Journal of Software 2019年 30卷 27-39页

作者： Wei, Lian-Suo Su, Yang Li, Hua Wu, Di School of Computer and Control Engineering Qiqihar University Qiqihar161006 China School of Computing Science and Technology Harbin Engineering University Harbin150001 China

Most of the existing UWSNs clock synchronization algorithms use nodes to exchange data frequently, but neglect the synchronization information received by neighbor nodes within the scope of node-based communication, so there are some problems such as high energy consumption and low synchronization efficiency in synchronization communication, which affect the accuracy of network clock synchronization. Therefore, based on the analysis of the influence of UWSNs multi-objective optimization network topology evolution process on clock synchronization, this paper uses the theory of group consistency and Markov chain to establish the synchronization cycle regulation mechanism and clock synchronization model without too much increase of the average transmission radius and communication energy consumption. Then, using linear regression fitting method, the inter-cluster synchronization and intra-cluster synchronization are established. Finally, the performance of UWSNs clock synchronization algorithm is verified by simulation. © Copyright 2019, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Synchronization

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