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Prototyping a Flowmeter for a Continuous Positive Airway Pressure Device 9th

Prototyping a Flowmeter for a Continuous Positive Airway ...

9th Latin American Congress on biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on biomedical engineering, CBEB 2022

作者： Motta-Ribeiro, Gabriel C. Giannella-Neto, Antonio Programa Doutor Empreendedor Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro Rio de Janeiro Brazil Biomedical Engineering Program Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9783031494062

Continuous positive airway pressure (CPAP) is an effective therapy for obstructive sleep apnea. Although the controlled variable in CPAP devices is pressure, flow measurement can supplement monitoring of therapy effectiveness. Here, we describe desired sensor characteristics, application constraints and a theoretical framework for designing a differential pressure flowmeter for a CPAP device. Our aim is to validate this framework through experimental verification of the permanent pressure loss and flow-pressure curve of a 3D-printed prototype. Pressure at patient interface was less than 5% lower than that measured before the restrictive element, despite pressure drop in such element being always above that threshold. The predicted quadratic flow-pressure relationship was achieved with a 97% approximation. These findings indicate that the type of restrictive element chosen for the prototype, a Venturi tube, is suitable for the application, and the used framework is adequate for sensor design. However, refinements to the current geometry are needed to adjust flow sensibility and the fitting to other CPAP device’s components. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Flowmeters

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Efficient Nearly Piecewise Continuous Signal Basis Expansion by Precision Calculation

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IEEE Access 2025年 13卷 95963-95976页

作者： Lee, Hsin-Jung Lee, Cheng-Che Chen, Kuei-Chen Luo, Shao-Yun Chang, Shu-Ping Ding, Jian-Jiun National Taiwan University Graduate Institute of Electronics Engineering Taipei 10617 Taiwan National Taiwan University Graduate School of Advanced Technology Taipei 10617 Taiwan National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics Taipei 10617 Taiwan National Taiwan University Graduate Institute of Communication Engineering Taipei 10617 Taiwan

Many one-dimensional (1D) signals, including ECG signals, economic data, particle distributions, seismic waveforms, image rows, and traffic statistics, are nearly piecewise continuous. These signals vary gradually in most regions but vary rapidly in certain narrow regions. Due to the non-uniform distribution of gradients, it is very challenging to well expand these nearly piecewise continuous signals. In this paper, we propose a novel algorithm, called “precise calculation,” to adaptively expand such signals. It categorizes signals into three types and then segments each type into smooth and large-gradient parts by using gradient-based analysis, adaptive thresholding, and morphology refinement. After decomposition, adaptive expansion is applied in each segment. Experiments on 1D ECG signals, electron-density distributions, seismic waveforms, image-row data, and economic time-series demonstrate that the proposed methods accurately expand nearly piecewise continuous signals. Under a fixed number of basis functions, our approach achieves significantly lower approximation errors than existing methods, highlighting its effectiveness for high-fidelity signal reconstruction. While applying only 5% of the expansion functions, experiments show that, for ECG signals, the expansion errors obtained by the proposed method range from 0.0003 to 0.0094—significantly lower than those achieved using only the DCT (0.0023–0.1506) and the Legendre method (0.00318–0.1677). © 2013 IEEE.

关键词： ECG signal expansion efficient one-dimensional basis expansion large-gradient part nearly piecewise continuous signal Signal expansion

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Microvolt T-Wave and Ventricular Repolarization Duration Alternans 9th

Microvolt T-Wave and Ventricular Repolarization Duration Alt...

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9th Latin American Congress on biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on biomedical engineering, CBEB 2022

作者： Winkert, Thaís Nadal, Jurandir Benchimol-Barbosa, Paulo Roberto Biomedical Engineering Program COPPE Institute Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Hospital Universitário Pedro Ernesto Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9783031494031

The ventricular tachyarrhythmia is an important cause of sudden cardiac death, impacting economic, social, and health systems. Microvolt T-wave alternans (MTWA) represent transmural gradient alternation in phase-3 ventricular action potential duration, leading to T-wave amplitude shortening in every other beat. The T-peak T-end interval (TpTe) represents the terminal ventricular repolarization duration and is explained by differences in phase-3 repolarization times from ventricular epicardial to endocardial fibers. Whether TpTe alternation occurs in patients with MTWA is unknown. This work investigated whether terminal ventricular repolarization duration alternation is present in MTWA patients. Seven 12-lead ECG records from Physionet T-wave Alternans Database were analyzed. The TpTe alternans was assessed in even and odds beats, in a series of 128 consecutive beats. In even and odd beats, TpTe intervals were ensembled and averaged, and the magnitude of TpTe alternans was defined as the difference between averages (ΔTpTe). The MTWA was quantified by the difference between the average peak of the T-wave in even and odd beats. ΔTpTe and MTWA were compared by Pearson’s coefficient. Even and odd beats on TpTe alternans and MTWA were compared with non-paired Student t-tests. ΔTpTe positively correlated with MTWA (r = 0.5;p © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Electrocardiograms

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Recent advances in electronic devices for monitoring and modulation of brain

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Nano Research 2021年第9期14卷 3070-3095页

作者： Yong Won Kwon Yoon Sun Jun Young-Geun Park Jiuk Jang Jang-Ung Park Nano Science Technology Institute Department of Materials Science and EngineeringYonsei UniversitySeoul 03722Republic of Korea Center for Nanomedicine Institute for Basic Science(IBS)Seoul 03722Republic of Korea Graduate Program of Nano Biomedical Engineering(NanoBME) Advanced Science InstituteYonsei UniversitySeoul 03722Republic of Korea

The brain is actuated by billions of neurons with trillions of interconnections that regulate human *** the mechanisms of these systems that induce sensory reactions and respond to disease remains one of the greatest challenges in science,engineering,and *** advances in nanomaterials and nanotechnologies have led to the extensive research of electronic devices for brain interfaces to better understand the neural activities of the brains complex nervous *** development of sensor devices for monitoring the physiological signals of the brain related to traumatic injury status has accompanied by the progress of electronic neural probes in *** addition,these neurological and stereotactic surgical revolutions hold immense potential for clinical analysis of pharmacological systems within cerebral ***,we review the progress of electronic devices interfacing with brain in terms of the materials,fabrication technologies,and device *** activity can be measured and modulated by brain probes based on newly developed nanofabrication ***,in vivo pathological monitoring of the brain and pharmacological assessment has been developed in miniaturized and wireless *** also consider the key challenges and prospects for further development,and explore the future directions emerging in the latest research.

关键词： neural interfaces neural recording neuromodulation intracranial pressure monitoring microfluidic drug delivery

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Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

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2024 7th International Conference on Healthcare Service Management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Rectifying Adversarial Examples Using Their Vulnerabilities

SSRN

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SSRN 2024年

作者： Morimoto, Fumiya Ono, Satoshi Department of Information Science and Biomedical Engineering Graduate School of Science and Engineering Kagoshima University 1-21-40 Korimoto Kagoshima890-0065 Japan

Recent studies have exposed a vulnerability in deep neural network (DNN)- based classifiers, revealing their susceptibility to misrecognizing adversarial examples (AEs). AEs are minimally perturbed input data imperceptible to human observations, posing a substantial threat in security-critical systems, such as traffic sign recognition in autonomous driving and image-based personal authentication. The integration of DNNs into systems directly has raised concerns due to the potential exploitation of AEs in real-world scenarios. The risks associated with this vulnerability have prompted extensive research to develop defense mechanisms that mitigate the threats posed by AEs. Current methods primarily focus on discriminating AEs based on features of input samples, emphasizing detection without addressing the correct categorization of samples before an attack. While some tasks may suffice by merely rejecting detected AEs, others, such as traffic sign recognition in autonomous driving, necessitate the identification of the correct original input category. This study proposes a label-rectification method to detect AEs capable of estimating their correct labels in the original images. The proposed method rectifies misclassification results to align with those of the original images through a process involving the re-attacking of AEs. Our findings demonstrate superior and consistently stable performance in rectifying AEs generated by various attack approaches compared to conventional detection methods. © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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Assessment of Simple Adhesive Substrates for Quantifying Microplastics

SSRN

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SSRN 2022年

作者： Rieland, Julie M. Hu, Zeyuan Deese, Julian S. Love, Brian J. The University of Michigan United States Department of Materials Science and Engineering Department of Biomedical Engineering Macromolecular Science and Engineering Graduate Program

Microplastics are a growing environmental concern, with a large body of evidence documenting substantial distribution of plastic material in virtually all environmental compartments. Countermeasures that help to bind, aggregate, or coalesce these distributed particles might result in lower human and animal exposures. Pressure sensitive adhesives (PSAs) have been identified as a viable microplastic (MP) capture mechanism with a range of potential use conditions. As with any countermeasure, there is a need to evaluate potential solutions in terms of collection efficiency, cost, ease of installation, etc. Expanding on our previous work, spray-coated PSAs were investigated as submerged surfaces as tools to assess MP binding in aqueous dispersions. Resins containing two differing molecular weights of poly(2-ethylhexyl acrylate) PSA (92k and 950k), and a 50:50 by weight mixture of the two resins were applied as spray-coated substrates to compare the effect of resin composition on MP-adhesive binding. Thin films of PSA (92k 6 ± 1 μm, 950k 4 ± 2 μm, 50:50 BD 6.5 ± 1 μm) were sprayed on borosilicate glass slides using a commercial air brush. Polydisperse nylon-12 particles varying in size from 15-30 µm in diameter were dispersed in deionized water at concentrations between 0.01 and 5 mg mL -1 and agitated under ambient conditions to assess adhesive binding as quantitative comparisons of microparticle capture. Mixed assays were also performed comparing binding of common MP species including polyethylene (50, 200 µm), polystyrene (10 µm), and polyester fibers (1000 µm) to understand how varying composition, size, and form factor affect adsorption. The glass slide method showed increasing linear trends of particle binding with increased adhesive exposure time and MP concentration. The lower molecular weight 92K adhesive had lower viscosity, higher wettability for microplastics but also led to a less stable adhesive film complicating analysis. As a field-deployable scheme for mi

关键词： Aggregates

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Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement

Leveraging Joint Spectral and Spatial Learning with MAMBA fo...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wenze Ren Haibin Wu Yi-Cheng Lin Xuanjun Chen Rong Chao Kuo-Hsuan Hung You-Jin Li Wen-Yuan Ting Hsin-Min Wang Yu Tsao Graduate Institute of Communication Engineering National Taiwan University Department of Computer Science and Information Engineering National Taiwan University Academia Sinica Taiwan Department of Biomedical Engineering National Taiwan University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction. Traditional methods, such as CNN or LSTM, attempt to model the temporal dynamics of full-band and sub-band spectral and spatial features. However, these approaches face limitations in fully modeling complex temporal dependencies, especially in dynamic acoustic environments. To overcome these challenges, we modify the current advanced model McNet by introducing an improved version of Mamba, a state-space model, and further propose MCMamba. MCMamba has been completely reengineered to integrate full-band and narrow-band spatial information with sub-band and full-band spectral features, providing a more comprehensive approach to modeling spatial and spectral information. Our experimental results demonstrate that MCMamba significantly improves the modeling of spatial and spectral features in multichannel speech enhancement, outperforming McNet and achieving very promis- ing performance on the CHiME-3 dataset. Additionally, we find that Mamba performs exceptionally well in modeling spectral information.

关键词： Noise reduction Speech enhancement Signal processing Acoustics State-space methods Long short term memory Faces Microphones

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Cannabinoid Modulation of Monoamine Levels in Mouse Brain:Unveiling Neurochemical Dynamics through an Innovative High‑performance Liquid Chromatography‑Fluorescence Detection Bioanalysis

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Journal of Analysis and Testing 2024年第3期8卷 300-314页

作者： Fonseca Carla Cunha Susana Ferreira Ricardo Lapo Pais Mariana Goncalves Joana Camins Antoni Ettcheto Miren Barbosa Rui Fortuna Ana Laboratory of Pharmacology Faculty of PharmacyUniversity of CoimbraPolo das Ciencias da SaudeAzinhaga de Santa CombaCoimbra 3000‑548Portugal CIBIT/ICNAS-Coimbra Institute for Biomedical Imaging and Translational Research University of CoimbraCoimbra 3000‑548Portugal Department of Pharmacology Toxicology and Therapeutic ChemistryFaculty of Pharmacy and Food ScienceUniversitat de BarcelonaBarcelona 08028Spain Institute of Neurosciences Universitat de BarcelonaBarcelona 08035Spain Faculty of Sciences and Technology Doctoral Program in Biomedical EngineeringUniversity of CoimbraCoimbra 3004‑516Portugal Biomedical Research Networking Centre in Neurodegenerative Diseases(CIBERNED) Carlos Ⅲ Health InstituteMadrid 28031Spain Institut d’Investigacio Sanitaria Pere Virgili(IISPV) Reus 43204Spain CNC-Center for Neuroscience and Cell Biology University of CoimbraCoimbra 3004-504Portugal

Homeostasis of monoaminergic pathways is compromised in aging and neurodegenerative/neurological diseases such as Alzheimer’s disease and *** the other hand,their modulation has also been linked to the mechanism of action of several ***,monitoring the levels of noradrenaline(NA),adrenaline(AD),dopamine(DA),and serotonin(5-HT),as well as those of tryptophan(TRYP),the precursor of 5-HT,and DA metabolites,namely 3,4-dihydroxyphenylacetic acid(DOPAC)and homovanillic acid(HVA),is fundamental for assessing disease severity and *** work aimed to develop and validate the first High-Performance Liquid Chromatography(HPLC)coupled with fluorescence detector(FLD)method that simultaneously and accurately quantifies NA,AD,DA,DOPAC,HVA,5-HT and TRYP in mouse brain and prefrontal cortex(PFC)*** sample preparation by protein precipitation was required to extract the *** curves were plotted using the background subtraction approach to reduce the interference of the endogenous *** and inter-day accuracy and precision were within the ranges defined by ICH(The International Council for Harmonisation)guideline for bioanalytical method *** validation,the impact of cannabidiol(CBD),cannabigerol(CBG),and cannabidivarin(CBDV)was explored in mice brains post-administration,revealing significant alterations in specific neurotransmitter levels upon cannabinoid exposure and shedding light on the complex modulation of neurochemical dynamics by *** research highlights the fit-for-purpose of the HPLC-FLD method and provides insights into potential mechanisms underlying phytocannabinoid actions in the central nervous system(CNS).

关键词： Neurotransmitter HPLC Mice Brain Prefrontal cortex Cannabinoid

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Volume holographic illuminator for Airy light-sheet microscopy

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Optics Express 2024年第1期32卷 167-178页

作者： Hsu, Hung-Chuan Vyas, Sunil Wu, Jui-Ching Huang, Kuang-Yuh Liao, Hsien-Shun Yeh, J. Andrew Luo, Yuan Department of Mechanical Engineering National Taiwan University Taipei10617 Taiwan Institute of Medical Devices and Imaging System National Taiwan University Taipei10051 Taiwan Department of Clinical Laboratory Science and Medical Biotechnology National Taiwan University Taipei10048 Taiwan Institute of Nano Engineering and Microsystems National Tsing Hua University Hsinchu30013 Taiwan YongLin Institute of Health National Taiwan University Taipei10087 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan Graduate School of Advanced Technology National Taiwan University Taipei106319 Taiwan

Airy light sheets combined with the deconvolution approach can provide multiple benefits, including large field of view (FOV), thin optical sectioning, and high axial resolution. The efficient design of an Airy light-sheet fluorescence microscope requires a compact illumination system. Here, we show that an Airy light sheet can be conveniently implemented in microscopy using a volume holographic grating (VHG). To verify the FOV and the axial resolution of the proposed VHG-based Airy light-sheet fluorescence microscope, ex-vivo fluorescently labeled Caenorhabditis elegans (C. elegans) embryos were imaged, and the Richardson-Lucy deconvolution method was used to improve the image contrast. Optimized parameters for deconvolution were compared with different methods. The experimental results show that the FOV and the axial resolution were 196 µm and 3 µm, respectively. The proposed method of using a compact VHG to replace the common spatial light modulator provides a direct solution to construct a compact light-sheet fluorescence microscope. © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Image enhancement

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