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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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Droplet 3D cryobioprinting for fabrication of free-standing and volumetric structures

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Aggregate 2024年第5期5卷 433-444页

作者： Joshua Weygant Ali Entezari Fritz Koch Ricardo AndréGalaviz Carlos Ezio Garciamendez Pável Hernández Vanessa Ortiz David Sebastián Rendon Ruiz Francisco Aguilar Andrea Andolﬁ Ling Cai Sushila Maharjan Anayancy Osorio Yu Shrike Zhang Division of Engineering in Medicine Department of MedicineBrigham and Women’s HospitalHarvard Medical SchoolCambridgeMassachusettsUSA School of Biomedical Engineering University of Technology SydneyBroadwayNew South WalesAustralia Laboratory for Bioinspired Materials for Biomedical Engineering IMTEK—Department of Microsystems EngineeringUniversity of FreiburgFreiburgGermany Department of Informatics BioengineeringRobotics and Systems Engineering(DIBRIS)University of GenovaGenovaItaly Department of Engineering University of CambridgeCB21PZ CambridgeUK

Droplet-based bioprinting has shown remarkable potential in tissue engineering and regenerative ***,it requires bioinks with low viscosities,which makes it challenging to create complex 3D structures and spatially pattern them with different *** study introduces a novel approach to bioprinting sophisti-cated volumetric objects by merging droplet-based bioprinting and cryobioprinting *** leveraging the beneﬁts of cryopreservation,we fabricated,for theﬁrst time,intricate,self-supporting cell-free or cell-laden structures with single or multiple materials in a simple droplet-based bioprinting process that is facilitated by depositing the droplets onto a cryoplate followed by crosslinking during *** feasibility of this approach is demonstrated by bioprinting several cell types,with cell viability increasing to 80%–90%after up to 2 or 3 weeks of ***,the applicational capabilities of this approach are showcased by bio-printing an endothelialized breast cancer *** results indicate that merging droplet and cryogenic bioprinting complements current droplet-based bioprinting techniques and opens new avenues for the fabrication of volumetric objects with enhanced complexity and functionality,presenting exciting potential for biomedical applications.

关键词： 3D bioprinting biofabrication cryogenic bioprinting droplet printing inkjet tissue engineering

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Balancing Memorization and Generalization in RNNs for High Performance Brain-Machine Interfaces 37

Balancing Memorization and Generalization in RNNs for High P...

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Costello, Joseph T. Temmar, Hisham Cubillos, Luis H. Mender, Matthew J. Wallace, Dylan M. Willsey, Matthew S. Patil, Parag G. Chestek, Cynthia A. Department of Electrical and Computer Engineering Biomedical Engineering Robotics and Neurosurgery University of Michigan Ann ArborMI United States

ISBN: (纸本)9781713899921

Brain-machine interfaces (BMIs) can restore motor function to people with paralysis but are currently limited by the accuracy of real-time decoding algorithms. Recurrent neural networks (RNNs) using modern training techniques have shown promise in accurately predicting movements from neural signals but have yet to be rigorously evaluated against other decoding algorithms in a closed-loop setting. Here we compared RNNs to other neural network architectures in real-time, continuous decoding of finger movements using intracortical signals from nonhuman primates. Across one and two finger online tasks, LSTMs (a type of RNN) outperformed convolutional and transformer-based neural networks, averaging 18% higher throughput than the convolution network. On simplified tasks with a reduced movement set, RNN decoders were allowed to memorize movement patterns and matched able-bodied control. Performance gradually dropped as the number of distinct movements increased but did not go below fully continuous decoder performance. Finally, in a two-finger task where one degree-of-freedom had poor input signals, we recovered functional control using RNNs trained to act both like a movement classifier and continuous decoder. Our results suggest that RNNs can enable functional real-time BMI control by learning and generating accurate movement patterns. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Mammals

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Reconfiguration of Distribution Network based DG and Capacitors using Grey Wolf Algorithm for Power Loss Reduction 3

Reconfiguration of Distribution Network based DG and Capacit...

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3rd International Conference on Intelligent robotics, Mechatronics and Automation Systems, IRMAS 2023

作者： Rajalakshmi, K. Vishnupriyan, S. Saravanakumar, M.N. Parivendhan, J. Lese, S. Department of Robotics and Automation Kings Engineering College TN Chennai India Department of Biomedical Engineering Kings Engineering College TN Chennai India

Network reconfiguration is one of the methods used for power loss reduction in distribution network by altering the close/open position of Tie/Sectionalizing switches without interruption of power to all loads. The other methods used are placing of distribution generators and connecting capacitors. The best results are obtained when all the three are used simultaneously using grey wolf algorithm which is a recent evolutionary algorithm which gives the place of connection and values of capacitor and distribution generators along with sectionalizing switches which are to be opened. This algorithm was implemented for a standard 33 and 69 bus distribution system in a MATLAB environment for comparing with other algorithms with constraints. This algorithm has good exploration (new search) and exploitation (thorough local search) potential for application in many power system optimization problems. © Published under licence by IOP Publishing Ltd.

关键词： Distributed power generation

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Role of IoT in characterization and material properties of synthesis of chromel composite

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Interactions 2024年第1期245卷 1-9页

作者： Siva, T. Bruno, A. Dyson Hepsiba, D. Vijay Anand, L.D. Ram, S. Priya, L. Department of Mechanical Engineering Meenakshi Ramaswamy Engineering College Tamilnadu Thathanur Ariyalur India Department of Mechanical Engineering PSNA College of Engineering and Technology Dindigul India Division of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore India Division of Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering andTechnology Hyderabad India Department of Information Technology Bannari Amman Institute of Technology Erode Sathyamangalam638 401 India

The chromel metal matrix composite (MMC) was fabricated through stir casting process reinforced with Tantalum Carbides (TaC). It was used to further increase the substance properties. The morphology characteristics and chemical compositions have been studied through Scanning Electron Microscope (SEM) and Energy Dispersive Analysis of X- Ray (EDAX) respectively. The substance properties such as hardness, density, impact and tensile strength were measured. The quality of the casting components are achieved through monitoring of internet of things (IoT). IoT enabled stir casting system is used to fabricate the chromel composite. The casting process is fully automated by IoT. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Tensile strength

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Taguchi and ANN approaches for predicting the FSW parameters to analyse the mechanical properties

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Interactions 2024年第1期245卷 1-12页

作者： Manickam, Selvaraj Kavitha, N. Rao, N. Srinivasa Indira, K.P. Pydi, Hari Prasadarao Cheepurupalli, N. Rao Department of Automation and Robotics IMPACT College of Engineering and Applied Sciences Bangalore India Department of Physics NPR College of Engineering and Technology Tamilnadu Natham Dindigul624 401 India Department of Mechanical Engineering Shri Vishnu Engineering College for Women Bhimavaram India Department of Biomedical Engineering Saveetha School of Engineering SIMATS Chennai Kuthambakkam India Department of Mechanical Engineering College of Engineering and Technology Bule Hora University Bule Hora Ethiopia Department of Mineral Processing and Metallurgical Engineering Faculty of Mines Aksum University Aksum Ethiopia

Taguchi design utilized to execute mathematical analysis to assess friction stir welding factors on the mechanical properties like ultimate tensile strength (UTS) and Hardness (BHN). Tool rotational speed (TO), pin depth of tool (PI) and welding speed (WE) were selected. The collected experimental data were used to train ANN model using the LM backpropagation algorithm, aiming to achieve accurate predictions of the maximize the mechanical properties. The optimized ANN was structured as a multilayer perceptron with a feed-forward architecture, consisting of 3 input nodes, 10 neurons in the hidden layer, and 2 output node (3-10-3 structure). The developed model accurately which predicted UTS and BHN values, with an overall R of 0.99335 which indicates a high level of accuracy. The optimal settings for UTS at the highest and lowest levels in Exp. No 8 and Exp. No 3 are identified as TO3-WE2-PI1(1600 rpm, 200 mm/min, and 0.3 mm) and TO1-WE3-PI3 (1200 rpm, 250 mm/min, and 0.9 mm). © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Aluminum alloys

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Acoustic reflector-enabled forward-viewing ultrasound image-guided access

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Journal of Medical Imaging 2025年第2期12卷 025002页

作者： Tang, Yichuan Rahaman, Ashiqur Gonzalez, Araceli B. Abouaf, Issac Malik, Aditya Sorokin, Igor Zhang, Haichong Worcester Polytechnic Institute Department of Robotics Engineering WorcesterMA United States Worcester Polytechnic Institute Department of Biomedical Engineering WorcesterMA United States University of Massachusetts Medical School Department of Urology WorcesterMA United States

Purpose: Existing ultrasound (US) image-guided needle access methods applied in various surgical procedures (such as percutaneous nephrolithotomy) face the challenge of keeping the needle tip visible during the insertion process due to the unguaranteed alignment between the US image and needle. We propose a needle insertion mechanism with reflector-integrated US imaging, where the US image plane and the needle are mechanically aligned, and the needle is inserted in a forward- viewing style to provide more intuitive access. Approach: An acoustic reflector is used to redirect the US image plane while the needle goes through the slit in the middle of the acoustic reflector so that the needle path aligns with the US image plane. Both the bracket holding the needle and the acoustic reflector are rotatable to provide clinicians with the flexibility to search for the optimal needle insertion orientation. Effects of the slit in the reflector on the quality of post-reflection ultrasound images were evaluated. Needle tip visibility was evaluated in water and ex vivo beef tissue. Needle access accuracy was evaluated using point targets embedded in gelatin, and errors between the needle tip and point targets are estimated from X-ray images. Results: The slit in the reflector has limited effects on post-reflection image quality. The needle tip was visible in water and in ex vivo tissue, and its visibility was quantified using a signal-to-noise ratio. Needle access results showed an average insertion error of less than 3 mm. Conclusions: Our results demonstrate the clinical potential of the reflector-enabled forward-viewing US image-guided access mechanism. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Ultrasonography

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Micro-electrode array (MEA) electrophysiological signal analysis by descriptive stochastic tests of the probability density structure

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Research on biomedical engineering 2025年第2期41卷 1-13页

作者： Faria, Vinícius Naves Rezende Ramos, Marina Abadia Martinoia, Sérgio Destro-Filho, João-Batista Postgraduate Program in Electrical Engineering Universidade Federal de MG Uberlândia Brazil Postgraduate Program in Biomedical Sciences Universidade Federal de MG Uberlândia Brazil Division of Informatics Bioengineering Robotics and System Engineering Università Degli Studi Di Genova Genova Italy

Purpose: The primary objective of this study is to present, analyze, and quantitatively characterize the electrical signals obtained from neuronal cultures coupled to micro-electrode arrays (MEAs). Special attention is given to the temporal evolution of electrical activity across distinct geometric regions of the MEA devices. Methods: The proposed methodology involves signal acquisition, classical analysis based on spike and burst detection, and, critically, the characterization of the probability density structure of the signals. This is achieved through the quantification of Gaussianity—expressed as the percentage of segments non-Gaussian (PSNG)—and stationarity— expressed as the percentage of segments non-stationary (PSNE). Results: Initial analyses showed that first-order power spectral density quantifiers lacked the statistical robustness required to effectively describe the complex components of MEA signals. In contrast, PSNG and PSNE demonstrated strong potential in capturing the different stages of neuronal culture development. Cluster analysis further supported the discriminative capacity of these quantifiers. Conclusion: The phase corresponding to decreased neuronal activity and onset of cell death—a biologically critical stage—exhibited the strongest correlation among the studied variables. These results suggest a discernible biological organization and highlight the relevance of PSNG and PSNE as promising tools for assessing neuronal culture dynamics. © The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering 2025.

关键词： Cell death

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Detection of Lower-Limb Motion Using a Kneepad Sensor Based on Textile Strain Sensor 18

Detection of Lower-Limb Motion Using a Kneepad Sensor Based ...

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18th International Conference on Nano/Micro Engineered and Molecular Systems, NEMS 2023

作者： Zou, Xiaoyang Li, Xiaoting Xue, Jiaqi Lai, King Wai Chiu City University of Hong Kong Centre for Robotics and Automation Department of Biomedical Engineering Hong Kong

ISBN: (纸本)9798350333480

The monitoring of the knee joint angle during lower-limb motions is crucial for knee disorders patients and their rehabilitation. However, commonly used methods for lower-limb motion detection, such as inertial measurement units (IMUs) and motion capture systems, have limitations such as drift and high cost. To address these issues, we developed a wearable kneepad sensor using textile resistive strain sensors to measure knee angle during lower-limb motion. The strain sensors change in resistance signals caused by their deformation of them when the knee joint bends. To improve the accuracy of knee angle measurements, an encoder was integrated with kneepad sensor onto a prosthetic limb and used linear mapping method to calibrate the kneepad sensor with the encoder data as the ground truth. The calibrated kneepad sensor achieved an R2 value of 0.956, MAE of 6.15°, and MSE of 64.35 while detecting the knee angle. It was demonstrated that the ability of the kneepad sensor to measure knee angles during two types of lower-limb motions, sit-to-stand (STS) and knee extension. It is shown in this work that this comfortable, wearable kneepad sensor can help detect knee angles during lower-limb motions in various environments and has broad applications in healthcare and robotics. © 2023 IEEE.

关键词： Textiles

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Machine Learning-Based Early Seizure Detection: A Random Forest Classifier Approach for Pre-Ictal Stage Prediction in Epilepsy 10

Machine Learning-Based Early Seizure Detection: A Random For...

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10th International Conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Mohammed Vishar, M Anaz Hepsiba, D. Prasanna, R. Vijay Anand, L.D. Karunya Institute of Technology and Sciences Division of Biomedical Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Division of Robotics Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350350951

Abrupt and irregular spikes in the brain's electrical activity are the cause of seizures. This could cause transient aberrant behaviors, sensations, or altered states of awareness or unconsciousness. Movements could include jerky, alternatively tensed arms and legs. One of the most prevalent neurological conditions worldwide, epilepsy affects almost 50 million individuals worldwide, according to a report. Over 25% of epileptic individuals experience uncontrollable seizures even with existing medication and surgical treatment options. Preventing Sudden Unexpected Death in Epilepsy (SUDEP) is aided by early seizure detection. A machine learning methodology for seizure detection was introduced by the proposed *** recognized seizure is diagnosed using the Random Forest Classifier algorithm. Using datasets from the ECG (electrocardiogram) and EEG (electroencephalogram), a pre-trained model is created using supervised and machine learning techniques. Finding seizures in the pre-ictal period is the aim. Using the datasets that are available, the model is trained, demonstrating that there are several causes of epilepsy. The answer is the same despite these variations in the causes. The model predicts and alerts carers, nurses, and hospital administration to an upcoming seizure. For doctors, this early warning is very helpful in enabling timely treatment. © 2024 IEEE.

关键词： Electroencephalography

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