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Add-On Type Internal Resistance and Current Sensor Fault Estimation Algorithm Based on the Correlation of the Current-Voltage Data

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Transactions of the Korean Institute of Electrical Engineers 2025年第4期74卷 717-726页

作者： Kim, Young-Seoung Na, Kun-Woo Seo, U-Jeong Kim, Wooyong Dept. of Biomedical and Robotics Engineering Incheon National University Korea Republic of

Lithium-ion batteries have established themselves as a critical energy source for electric vehicles and energy storage systems. As their usage continues to grow, the issues of battery currents due to current sensor failures can lead to overcharging, over-discharging, and potentially hazardous incidents such as battery fires. To address this issue, this study proposes a current sensor fault detection algorithm based on the analysis of the data covariance matrix. The proposed algorithm is designed as an add-on type solution, enabling calculations using only voltage data extracted from the Battery Management System (BMS). It detects current sensor faults in real-time, thereby mitigating potential risks. Furthermore, the study demonstrates the algorithm’s applicability by cross-validating its performance using data from both new and aged battery models. Through this approach, the algorithm addresses current sensor fault issues across various battery states, contributing to the prevention of critical incidents such as battery fires. © The Korean Institute of Electrical Engineers.

关键词： Covariance matrix

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Add-on-type Current Sensor Freezing Fault Diagnosis Algorithm Based on Current–Voltage Data Correlation for Battery Disconnect Units

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Journal of Electrical engineering and Technology 2025年第4期20卷 2543-2552页

作者： Kim, Youngseoung Na, Kunwoo Seo, Ujeong Kim, Wooyong Dept. of Biomedical & Robotics Engineering Incheon National University Incheon Korea Republic of

Lithium-ion batteries have become a crucial energy source in electric vehicles and energy storage systems. Battery safety and reliability have emerged as significant issues with their increased usage. Failure in non-contact current sensors can lead to inaccuracies in internal current measurement, posing serious risks like overcharging and over-discharging, which may cause fires within battery circuits. To address these challenges, this study proposes an add-on-type current sensor fault diagnosis algorithm based on data analysis using a covariance matrix. The current sensor freezing fault can be captured by determining the internal resistance using the current–voltage relationship. The proposed algorithm enables fault detection without imposing additional load or modifications on the existing battery system. The performance of the proposed current sensor fault diagnosis algorithm was experimentally verified by using two cylindrical battery cells having different life conditions. © The Author(s) under exclusive licence to The Korean Institute of Electrical Engineers 2025.

关键词： Covariance matrix

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Micro/nanosystems for controllable drug delivery to the brain

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The Innovation 2024年第1期5卷 139-157页

作者： Mingzhen Tian Zhichao Ma Guang-Zhong Yang Institute of Medical Robotics School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Drug delivery to the brain is crucial in the treatment for central nervous system *** significant progress has been made in recent years,there are still major challenges in achieving controllable drug delivery to the *** clinical needs arise from various factors,including controlled drug transport,handling large drug doses,methods for crossing biological barriers,the use of imaging guidance,and effective models for analyzing drug *** advances in micro/nanosystems have shown promise in addressing some of these *** include the utilization of microfluidic platforms to test and validate the drug delivery process in a controlled and biomimetic setting,the development of novel micro/nanocarriers for large drug loads across the blood-brain barrier,and the implementation of micro-intervention systems for delivering drugs through intraparenchymal or peripheral *** this article,we present a review of the latest developments in micro/nanosystems for controllable drug delivery to the *** also delve into the relevant diseases,biological barriers,and conventional *** addition,we discuss future prospects and the development of emerging robotic micro/nanosystems equipped with directed transportation,real-time image guidance,and closed-loop control.

关键词： equipped doses barriers

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On Flexible Trajectory Description for Effective Rigid Body Motion Reproduction and Recognition

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Journal of Shanghai Jiaotong university(Science) 2023年第3期28卷 339-347页

作者：杨健鑫郭遥 Institute of Medical Robotics School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Recognizing and reproducing spatiotemporal motions are necessary when analyzing behaviors andmovements during human-robot interaction. Rigid body motion trajectories are proven as compact and informativeclues in characterizing motions. A ﬂexible dual square-root function (DSRF) descriptor for representing rigid bodymotion trajectories, which can offer robustness in the description over raw data, was proposed in our previousstudy. However, this study focuses on exploring the application of the DSRF descriptor for effective backwardmotion reproduction and motion recognition. Speciﬁcally, two DSRF-based reproduction methods are initiallyproposed, including the recursive reconstruction and online optimization. New trajectories with novel situationsand contextual information can be reproduced from a single demonstration while preserving the similarities withthe original demonstration. Furthermore, motion recognition based on DSRF descriptor can be achieved byemploying a template matching method. Finally, the experimental results demonstrate the effectiveness of theproposed method for rigid body motion reproduction and recognition.

关键词： human-robot interaction rigid body motion trajectory trajectory description motion reproduction and recognition

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Detection of neurodegenerative diseases using hybrid MODWT and adaptive local binary pattern

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Neural Computing and Applications 2024年第31期36卷 19417-19433页

作者： Prasanna, J. George, S. Thomas Subathra, M.S.P. Department of Biomedical Engineering Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore641114 India Department of Robotics Engineering Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore641114 India

Neurodegenerative diseases cause significant irregularities in walking patterns, impacting gait dynamics and rhythms analyzed through gait time series. Human gait analysis is a promising avenue for identifying unique walking patterns. Automated computer-aided techniques show potential in tracking pathological progression, particularly through non-invasive methods using football contact sensors. In this study, wavelet coefficients extracted via the maximal overlapped discrete wavelet transform from gait time series provide valuable insights into neurological deficiencies and deviations in gait. We employed various local binary patterns (LBPs), including inverse LBP, adaptive right-shifted LBP, and adaptive left-shifted LBP (ALS-LBP) on wavelet coefficients for classifying neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), Parkinson’s disease (PD), and healthy control (HC). Histogram-oriented features were extracted using different binary pattern techniques on gait time series. The feature subset was classified using the long short-term memory classifier. The study achieved maximum accuracy across all experimental cases, analyzing signals from left, right, and both feet during stride, swing, and stance. This approach demonstrated 100% classification accuracy for tasks involving HC versus PD, ALS versus HD, and ALS versus PD. The proposed method could open avenues for early-stage diagnosis of neurodegenerative diseases. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Discrete wavelet transforms

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Estimating Force Exerted by the Fingers Based on Forearm Ultrasound

Estimating Force Exerted by the Fingers Based on Forearm Ult...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Bimbraw, Keshav Zhang, Haichong K. Worcester Polytechnic Insitute Robotics Engineering Worcester United States Worcester Polytechnic Insitute Robotics Engineering and Biomedical Engineering Worcester United States

ISBN: (纸本)9798350346459

Biosignal-based finger force estimation is an active area of research, with applications in teleoperation, human-machine interaction, and rehabilitation robotics. Traditionally, surface electromyography has been used to estimate hand grip and finger forces. In this paper, we show that forearm ultrasound can be used to estimate the force exerted by the fingers. A wireless ultrasound probe strapped to the forearm and a force sensor was used to estimate the ground truth. Accuracy percentages and root mean square error (RMSE) values were obtained for the shuffled and non-shuffled data subjected to a test-train split for all the fingers. It was found that the classification accuracy was 98.4 percent for the shuffled data, and 82 percent for the non-shuffled data averaged over all the fingers. For continuous estimation, the average RMSE was 0.02 N for the shuffled data and 0.2 N for the non-shuffled data. With a maximum force of 5 N, the average RMSE accounted for 4 percent of the maximum force for the non-shuffled data, and 0.4 percent for the shuffled data. These results show the potential of utilizing forearm ultrasound for estimating finger forces. © 2023 IEEE.

关键词： Remote control

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Acoustic black hole effect enhanced micromanipulator

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Microsystems & Nanoengineering 2024年第5期10卷 345-352页

作者： Qiu Yin Haoyong Song Zhaolong Wang Zhichao Ma Wenming Zhang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghaiChina institute of Medical Robotics School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina College of Mechanical and Vehicle Engineering Hunan UniversityChangshaChina School of Energy Science and Engineering Harbin Institute of TechnologyHarbinP.R.China

Microparticle manipulation is a critical concern across various felds including microfabrication,flexible electronics and tissue ***-activated sharp structures have been designed as simple and flexible tools to manipulate microparticles with their good compatibility,fast response,and broad ***,there still lacks rational acoustic-structure design for effective energy concentration at the acoustic-activated sharp structures for microparticle ***,we present the acoustic black hole(ABH)effect as enhancement for the acoustic *** provides great reliability,simplicity and ease of use,supporting custom design of high-throughput patterning ***,compared to commonly used configurations,such as cylindrical or conical microneedles,those microneedles with ABH profle exhibit superior acoustic energy focusing at the tip and induce stronger acoustofluidic *** average acoustic flow velocity induced by the ABH microneedle is 154 times greater than that of the conical one and 45 times greater than that of the cylindrical ***,the average acoustic radiation force(ARF)produced by the ABH microneedle against acrylic microparticles is about 319 times greater than that of the cylindrical one and 16 times greater than that of the conical *** results indicate that ABH design significantly enhances microparticle *** demonstrate this concept with ABH effect enhanced microparticle manipulation and study the parameters influencing its performance including operating frequency,operating voltage and particle ***,considering the flexibility of this system,we employ it for various patterning and high-throughput microparticle *** work paves the way for controllable microparticle manipulation,holding great potential for applications in microfabrication and biomedicine.

关键词： cylindrical Acoustic simplicity

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A Fast Walsh-Hadamard transform (FWHT) For Detection of Freezing of Gait in Parkinson's disease using Machine learning techniques. 4

A Fast Walsh-Hadamard transform (FWHT) For Detection of Free...

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4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Nancy, R. Thomas George, S. Prasanna, J. Subathra, M.S.P. Karunya Institute of Technology and Science Department of Robotics Engineering Coimbatore India Karunya Institute of Technology and Science Department of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350349856

Freezing of gait stands out as the most severe detrimental motor signs of advanced PD patients with an increased prevalence in the elderly, and frequently leads to falls and injuries among individuals associated with PD. This research proposes an efficient detection method for freezing of gait based on the Fast Walsh -Hadamard Transform (FWHT). The approach involves decomposing the gait signals, and key features are derived by analyzing the statistical parameters and entropy characteristics of the decomposed coefficients. The Artificial Neural Network (ANN) and K-Nearest Neighbor classifier (KNN) are employed to classify the obtained statistical and entropy measures. The tests utilize the benchmark dataset DAPHNET for performance assessment. Remarkably, the K-nearest neighbor (KNN) algorithm demonstrated noteworthy outcomes, achieving 98.42%, 98.24%, 98.57%, 98.38%, and 98.45% accuracy, specificity, sensitivity, positive predictive value, and negative predictive value, respectively. © 2024 IEEE.

关键词： Neural networks

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Leveraging OpenAI Whisper Model to Improve Speech Recognition for Dysarthric Individuals

Leveraging OpenAI Whisper Model to Improve Speech Recognitio...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Vinotha, R. Hepsiba, D. Vijay Anand, L.D. Karunya Institute of Technology and Sciences Division of Biomedical Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Coimbatore India

ISBN: (纸本)9798350361537

Automatic Speech Recognition (ASR) systems are pivotal in facilitating human-technology interactions through voice commands. However, individuals with dysarthria face significant challenges in benefiting from these technologies due to their speech disorder. This paper proposes finetuning the Whisper model for Dysarthric Speech Recognition (DSR) by incorporating additional features extracted from Mel-frequency cepstral coefficients (MFCCs). By combining spectrograms and MFCCs within an attention mechanism, the model creates a richer feature representation, with spectrograms providing broader context and MFCCs highlighting crucial formant frequencies. The attention mechanism dynamically weighs the importance of each feature based on specific speech segments and dysarthric speech characteristics. Furthermore, a hierarchical attention approach is adopted, which encompasses a two-stage attention mechanism. This mechanism directs attention at both local and global levels, facilitating the capture of both fine-grained details and broader contextual information within the speech signal. This study involved the development and training of 45 speaker-adaptive dysarthric ASR systems. The proposed model achieves an average Word Recognition Accuracy (WRA) of 74.08%, showing a notable enhancement compared to the benchmark of 69.23%. The findings underscore the efficacy of the proposed approach in addressing dysarthria-related challenges in ASR systems. © 2024 IEEE.

关键词： Spectrographs

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Comparative Analysis of PID Controller Tuning Methods for Heat Exchanger Control: A MATLAB Simulation Study

Comparative Analysis of PID Controller Tuning Methods for He...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Jencia, J. Anand, L.D. Vijay Hepsiba, D. Karunya Institute of Technology and Sciences Division of Robotics Engineering Coimbatore India Karunya Institute of Technology and Sciences Division of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350361537

This paper compares the performance of Proportional-Integral-Derivative (PID) controller tuning methods for a heat exchanger process using MATLAB simulations. The effectiveness of two popular techniques, Ziegler-Nichols, Cohen and coon, and Internal Model Control (IMC), is investigated. The three methods are applied to tune the PID controller for a first-order plus time delay (FOPDT) model of the heat exchanger. The simulation results are analyzed to evaluate the closed-loop response characteristics, focusing on metrics like settling time, rise time, and overshoot. The performance of the Ziegler-Nichols, Cohen and coon and IMC tuning methods are compared in achieving desired control objectives for the heat exchanger process. The study aims to identify which tuning approach offers a superior response in terms of stability, speed, and accuracy for this specific application. © 2024 IEEE.

关键词： MATLAB

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