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Analysis and visualisation of tremor dynamics in deep brain stimulation patients

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Analysis and visualisation of tremor dynamics in deep brain ...

作者： Bremm, Rene Peter Koch, Klaus Peter Krüger, Rejko Gonçalves, Jorge Hertel, Frank National Department of Neurosurgery Centre Hospitalier de Luxembourg Luxembourg Department of Electrical Engineering Trier University of Applied Sciences Trier Germany University of Luxembourg Esch-sur-Alzette Luxembourg Systems Control Group LCSB University of Luxembourg Esch-sur-Alzette Luxembourg Interventional Neuroscience Group LCSB University of Luxembourg Esch-sur-Alzette Luxembourg

Deep brain stimulation (DBS) is an established therapy for movement disorders such as in Parkinson's disease (PD) and essential tremor (ET). Adjusting the stimulation parameters, however, is a labour-intensive process and often requires several patient visits. Physicians prefer objective tools to improve (or maintain) the performance in DBS. Wearable motion sensors (WMS) are able to detect some manifestations of pathological signs, such as tremor in PD. However, the interpretation of sensor data is often highly technical and methods to visualise tremor data of patients undergoing DBS in a clinical setting are lacking. This work aims to visualise the dynamics of tremor responses to DBS parameter changes with WMS while patients performing clinical hand movements. To this end, we attended DBS programming sessions of two patients with the aim to visualise certain aspects of the clinical examination. PD tremor and ET were effectively quantified by acceleration amplitude and frequency. Tremor dynamics were analysed and visualised based on setpoints, movement transitions and stability aspects. These methods have not yet been employed and examples demonstrate how tremor dynamics can be visualised with simple analysis techniques. We therefore provide a base for future research work on visualisation tools in order to assist clinicians who frequently encounter patients for DBS therapy. This could lead to benefits in terms of enhanced evaluation of treatment efficacy in the future. © 2020 by Walter de Gruyter Berlin/Boston 2020.

关键词： Dynamics

Biochar and Amf Combination Promotes the Phosphorus Utilization to Increase Phragmites Growth: Insights from the Microbial Co-Occurrence Networks to Rhizosphere Lipid Metabolites

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SSRN

SSRN 2022年

作者： Li, Shuangqiang Chi, Shanqing Lin, Caiqiang Cai, Chen Yang, Liheng Peng, Kaiming Huang, Xiangfeng Liu, Jia College of Environmental Science and Engineering Tongji University State Key Laboratory of Pollution Control and Resource Reuse Ministry of Education Key Laboratory of Yangtze River Water Environment Shanghai200092 China Fuzhou Urban and Rural Construction Group Co. Ltd Fuzhou350007 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China

Agricultural biochar and arbuscular mycorrhizal fungi were used to promote the growth of Phragmites in the structural damaged and nutritional imbalanced littoral zone soils. Wheat biochar played significant role in improving soil porosity and supplementing exogenous phosphorus, with increasing available phosphorus from 17.50 ± 0.88 mg/kg to 79.20 ± 3.20 mg/kg. The addition of Diversispora versiformis improved the plant net photosynthetic rate reaching up to 25.66 ± 0.65 μmol·m-2 ·s-1, which was 36.60 % higher than CK. The combination of biochar and fungi contributed to the whole plant dry weight biomass of 32.30 % and 234.00 % higher than the single biochar and AMF amendment groups, respectively. Meanwhile, the analysis of microbial co-occurrence networks showed the most relevant networks node species were mainly Talaromyces, Chaetomiacea and Gemmatimonadetes etc. Root lipid metabolite of Glycerophospholines further proved that phosphorus utilization was also enhanced endogenously in the rhizosphere soil. These results indicated that the combination of biochar and arbuscular mycorrhizal fungi play synergic role in enhancing phosphorus utilization endogenously and exogenously. © 2022, The Authors. All rights reserved.

关键词： Phosphorus

Fast Hildreth-based Model Predictive control of Roll Angle for a Fixed-Wing UAV

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IFAC-PapersOnLine 2020年第2期53卷 5757-5763页

作者： V.T.T. Lam A. Sattar L. Wang M. Lazar Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands School of Engineering Cluster Electrical and Computer Engineering RMIT University Melbourne Australia School of Engineering Cluster Electrical and Biomedical Engineering RMIT University Melbourne Australia

In this paper we consider model predictive control (MPC) design for roll angle control for a fixed-wing unmanned aerial vehicle (UAV) with multiple segmented control surfaces. The challenge of roll angle control for a fixed-wing UAV consists of switching between inner and outer aileron pairs with hard constraints due to safety, energy saving and switching actuators. The novelty consists of formulating a hybrid control problem as a switched linear constrained MPC-QP problem and switched state observer design for fixed-wing UAV. A fast novel QP-solver based on the active-set QP-solver Hildreth is developed to meet the real-time implementation sampling time of T s = 10 ms. The designed MPC controllers are simulated using Matlab. Simulations and the CPU-time from the improved QP-solvers show MPC to be a very good solution for real-time roll angle control of fixed-wing UAVs.

关键词： Model Predictive control Quadratic Programming Fixed-Wing Unmanned Aerial Vehicle Active Set Methods

A Guide to Image and Video based Small Object Detection using Deep Learning: Case Study of Maritime Surveillance

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arXiv 2022年

作者： Rekavandi, Aref Miri Xu, Lian Boussaid, Farid Seghouane, Abd-Krim Hoefs, Stephen Bennamoun, Mohammed The Department of Computer Science and Software Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The Department of Electrical Electronics and Computer Engineering The University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia The School of Mathematics and Statistics The University of Melbourne Melbourne Australia submarine optronics undersea combat systems and undersea command and control maritime division Defence Science and Technology Group Australia

Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects. Typically, small objects appear in real-world due to large camera-object distance. Because small objects occupy only a small area in the input image (e.g., less than 10%), the information extracted from such a small area is not always rich enough to support decision making. Multidisciplinary strategies are being developed by researchers working at the interface of deep learning and computer vision to enhance the performance of SOD deep learning based methods. In this paper, we provide a comprehensive review of over 160 research papers published between 2017 and 2022 in order to survey this growing subject. This paper summarizes the existing literature and provide a taxonomy that illustrates the broad picture of current research. We investigate how to improve the performance of small object detection in maritime environments, where increasing performance is critical. By establishing a connection between generic and maritime SOD research, future directions have been identified. In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the datasets are provided. © 2022, CC BY-NC-SA.

关键词： Object recognition

Waves in weakly ionised solar plasmas

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arXiv 2022年

作者： Alharbi, Abdulaziz Ballai, I. Fedun, V. Verth, G. Plasma Dynamics Group School of Mathematics and Statistics University of Sheffield Hounsfield Road Hicks Building SheffieldS3 7RH United Kingdom Department of Mathematics Jamoum University College Umm Al-Qura University Jamoum Makkah25375 Saudi Arabia Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

Here we study the nature and characteristics of waves propagating in partially ionised plasmas in the weakly ionised limit, typical for the lower part of the solar atmosphere. The framework in which the properties of waves are discussed depends on the relative magnitude of collisions between particles, but also on the relative magnitude of the collisional frequencies compared to the gyro-frequency of charged particles. Our investigation shows that the weakly ionised solar atmospheric plasma can divided into two regions and this division occurs, roughly, at the base of the chromosphere. In the solar photosphere the plasma is non-magnetised and the dynamics can described within the three-fluid framework where acoustic waves associated to each species can propagate. Due to the very high concentration of neutrals, the neutral sound waves propagates with no damping, while for the other two modes the damping rate is determined by collisions with neutrals. The ion and electron-related acoustic modes propagate with a cut-off determined by the collisional frequency of these species with neutrals. In the weakly ionised chromosphere only electrons are magnetised, however, the strong coupling of charged particles reduces the working framework to a two-fluid model. The disassociation of charged particles creates electric currents that can influence the characteristic of waves. The propagation properties of waves with respect to the angle of propagation are studied with the help of polar diagrams. Copyright © 2022, The Authors. All rights reserved.

关键词： Damping

Event-triggered Discrete-time Sliding Mode control for High-order systems via Reduced-order Model Approach

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IFAC-PapersOnLine 2020年第2期53卷 6207-6212页

作者： Kiran Kumari Bijnan Bandyopadhyay Johann Reger Abhisek K. Behera Systems and Control Engineering Indian Institute of Technology Bombay India Control Engineering Group Technische Universität Ilmenau 98684 Ilmenau Germany Faculty of Mechanical Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Department of Statistics University of Haifa Haifa 31905 Israel

We propose the design of event-triggered (ET) discrete-time sliding mode (DTSM) control for a high-order discrete-time system via a reduced-order model-based approach. This design includes a triggering mechanism using a reduced-order state vector and a controller based on the modified Bartoszewicz’ reaching law for a reduced-order model of the system, to stabilize the uncertain high-order system. The main advantages of using a reduced-order vector in the event condition are the low-order synthesis of the controller and the sampling pattern, which may be sparser than the full vector-based design. This motivation arises from the fact that relaxing a few components of the state vector in the triggering mechanism may decrease its rate of violation. An added advantage of the proposal is that the transmission of the reduced-order vector, particularly in a network-based implementation, can outperform the full-order based design due to the severe challenges that exist in the data network. The robust performance for the closed-loop system is achieved using the DTSM control. We show that our proposal guarantees the stability of the full-order plant with the reduced-order triggering mechanism. The control execution is Zeno-free because of the inherent discrete nature of the control. The efficiency of the proposed method is shown using the simulation results of a numerical example.

关键词： Event-triggered control Discrete-time sliding mode Model-order reduction

Harmonic-Gaussian double-well potential stochastic resonance with its application to enhance weak fault characteristics of machinery

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arXiv 2023年

作者： Qiao, Zijian Chen, Shuai Lai, Zhihui Zhou, Shengtong Sanjuán, Miguel A.F. School of Mechanical Engineering and Mechanics Ningbo University Ningbo315211 China State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang330013 China Yangjiang529500 China Zhejiang Provincial Key Laboratory of Part Rolling Technology Ningbo315211 China Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Nonlinear Dynamics Chaos and Complex Systems Group Departamento de Física Universidad Rey Juan Carlos Tulipán s/n Móstoles Madrid28933 Spain

Noise is ubiquitous and unwanted in detecting weak signals, which would give rise to incorrect filtering frequency-band selection in signal filtering-based methods including fast kurtogram, teager energy operators and wavelet packet transform filters and meanwhile would result in incorrect selection of useful components and even mode mixing, end effects and etc. in signal decomposition-based methods including empirical mode decomposition, singular value decomposition and local mean decomposition. On the contrary, noise in stochastic resonance (SR) is beneficial to enhance weak signals of interest embedded in signals with strong background noise. Taking into account that nonlinear systems are crucial ingredients to activate the SR, here we investigate the SR in the cases of overdamped and underdamped harmonic-Gaussian double-well potential systems subjected to noise and a periodic signal. We derive and measure the analytic expression of the output signal-to-noise ratio (SNR) and the steady-state probability density (SPD) function under approximate adiabatic conditions. When the harmonic-Gaussian double-well potential loses its stability, we can observe the antiresonance phenomenon, whereas adding the damped factor into the overdamped system can change the stability of the harmonic-Gaussian double-well potential, resulting that the antiresonance behavior disappears in the underdamped system. Then, we use the overdamped and underdamped harmonic-Gaussian double-well potential SR to enhance weak useful characteristics for diagnosing incipient rotating machinery failures. Theoretical and experimental results show that adjusting both noise intensity and system parameters can activate overdamped and underdamped harmonic-Gaussian double-well potential SR in which there is a bell-shaped peak for the SNR. Additionally, the underdamped harmonic-Gaussian double-well potential SR is independent of frequency-shifted and rescaling transform to process large machine parameter signal

关键词： Empirical mode decomposition

Enabling Invariant Models to Describe Time-Varying Dynamics: A Case Study ⁎

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IFAC-PapersOnLine 2021年第14期54卷 1-6页

作者： Petrus E.O.G.B. Abreu Victor D.R. Dreke Luis A. Aguirre Claudio Garcia Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil Control Systems Group Eindhoven University of Technology 5600 MB Eindhhover The Netherlands Department of Telecommunications and Control Engineering Escola Politécnica da Universidade de São Paulo Av. Prof. Luciano Gualberto 158 São Paulo SP Brazil

This work addresses the problem of identifying nonlinear and time-varying behaviors using Nonlinear polynomial AutoRegressive models with eXogenous inputs (NARX). Two approaches are investigated. The first one is based on a recursive algorithm with an adaptive forgetting factor to update the parameters of black-box models. The second approach aims to include a certain class of regressors to identify invariant models, i.e. with constant parameters, to describe such behaviors. An experimental case study of a pH neutralization process is carried out, which indicated the presence of behaviors that resemble varying dynamics features. Time-invariant models with a specific class of regressors are proposed and seem to be a promising way to deal with such dynamics.

关键词： Gray-box identification pH system NARX model varying dynamics

Data-Driven Predictive control for Linear Parameter-Varying systems

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arXiv 2021年

作者： Verhoek, Chris Abbas, Hossam S. Tóth, Roland Haesaert, Sofie Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven5600MB Netherlands Institute for Electrical Engineering in Medicine Universität zu Lübeck Lübeck23558 Germany Kende u. 13-17 Budapest1111 Hungary

Based on the extension of the behavioral theory and the Fundamental Lemma for Linear Parameter-Varying (LPV) systems, this paper introduces a Data-driven Predictive control (DPC) scheme capable to ensure reference tracking and satisfaction of Input-Output (IO) constraints for an unknown system under the conditions that (i) the system can be represented in an LPV form and (ii) an informative data-set containing measured IO and scheduling trajectories of the system is available. It is shown that if the data set satisfies a persistence of excitation condition, then a data-driven LPV predictor of future trajectories of the system can be constructed from the IO data set and online measured data. The approach represents the first step towards a DPC solution for nonlinear and time-varying systems due to the potential of the LPV framework to represent them. Two illustrative examples, including reference tracking control of a nonlinear system, are provided to demonstrate that the data-based LPV-DPC scheme, achieves similar performance as LPV model-based predictive control. Copyright © 2021, The Authors. All rights reserved.

关键词： Linear systems