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Characterization of the phagocytic ability of white blood cells separated using a single curvature spiral microfluidic device 利用单曲率螺旋微流控装置分析白细胞的吞噬能力
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-08-08 DOI: 10.1007/s13534-024-00414-y
Sanjay Mane, Paul Jacob, Vadiraj Hemadri, Prasenjit Dey, Sunil Bhand, S. Tripathi
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引用次数: 0
Quantitative biomechanical analysis in validating a video-based model to remotely assess physical frailty: a potential solution to telehealth and globalized remote-patient monitoring 通过定量生物力学分析验证基于视频的身体虚弱远程评估模型:远程医疗和全球化远程患者监测的潜在解决方案
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-27 DOI: 10.1007/s13534-024-00410-2
Mohammad Dehghan Rouzi, Myeounggon Lee, Jaewon Beom, Sanam Bidadi, Abderrahman Ouattas, Gozde Cay, A. Momin, Michele K. York, M. Kunik, Bijan Najafi
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引用次数: 0
Integrated deep learning approach for generating cross-polarized images and analyzing skin melanin and hemoglobin distributions 生成交叉偏振图像并分析皮肤黑色素和血红蛋白分布的综合深度学习方法
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-26 DOI: 10.1007/s13534-024-00409-9
Geunho Jung, Jonghan Lee, Semin Kim
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引用次数: 0
A low-complexity and high-frequency ASIC transceiver for an ultrasound imaging system 用于超声波成像系统的低复杂度高频 ASIC 收发器
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-25 DOI: 10.1007/s13534-024-00411-1
Jaeho Lee, Keun Young Huh, Dongil Kang, Jaemyung Lim, Byunghun Lee, Byunghun Lee
{"title":"A low-complexity and high-frequency ASIC transceiver for an ultrasound imaging system","authors":"Jaeho Lee, Keun Young Huh, Dongil Kang, Jaemyung Lim, Byunghun Lee, Byunghun Lee","doi":"10.1007/s13534-024-00411-1","DOIUrl":"https://doi.org/10.1007/s13534-024-00411-1","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Snn and sound: a comprehensive review of spiking neural networks in sound 尖峰神经网络与声音:声音尖峰神经网络综合评述
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-11 DOI: 10.1007/s13534-024-00406-y
S. Baek, Jaewon Lee
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引用次数: 0
Ventral tegmental area deep brain stimulation reverses ethanol-induced dopamine increase in the rat nucleus accumbens 腹侧被盖区深部脑刺激可逆转乙醇诱导的大鼠伏隔核多巴胺增加
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-09 DOI: 10.1007/s13534-024-00408-w
Abhinav Goyal, Juan M. Rojas Cabrera, C. Blaha, Kendall H. Lee, Hojin Shin, Yoonbae Oh
{"title":"Ventral tegmental area deep brain stimulation reverses ethanol-induced dopamine increase in the rat nucleus accumbens","authors":"Abhinav Goyal, Juan M. Rojas Cabrera, C. Blaha, Kendall H. Lee, Hojin Shin, Yoonbae Oh","doi":"10.1007/s13534-024-00408-w","DOIUrl":"https://doi.org/10.1007/s13534-024-00408-w","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Computational analysis on 3D airway model of obstructive sleep apnea patient for optimal maxillomandibular advancement 对阻塞性睡眠呼吸暂停患者的三维气道模型进行计算分析,以优化上下颌前移术
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-07 DOI: 10.1007/s13534-024-00407-x
Kideok Kim, Kunhee Lee, Jiyoung Hwang, Ui-Lyong Lee, Joong Yull Park
{"title":"Computational analysis on 3D airway model of obstructive sleep apnea patient for optimal maxillomandibular advancement","authors":"Kideok Kim, Kunhee Lee, Jiyoung Hwang, Ui-Lyong Lee, Joong Yull Park","doi":"10.1007/s13534-024-00407-x","DOIUrl":"https://doi.org/10.1007/s13534-024-00407-x","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141670883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Spiking neural networks for biomedical signal analysis 用于生物医学信号分析的尖峰神经网络
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-07-05 DOI: 10.1007/s13534-024-00405-z
Sang Ho Choi
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引用次数: 0
Spiking neural networks for physiological and speech signals: a review. 用于生理和语音信号的尖峰神经网络:综述。
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-06-25 eCollection Date: 2024-09-01 DOI: 10.1007/s13534-024-00404-0
Sung Soo Park, Young-Seok Choi

The integration of Spiking Neural Networks (SNNs) into the analysis and interpretation of physiological and speech signals has emerged as a groundbreaking approach, offering enhanced performance and deeper insights into the underlying biological processes. This review aims to summarize key advances, methodologies, and applications of SNNs within these domains, highlighting their unique ability to mimic the temporal dynamics and efficiency of the human brain. We dive into the core principles of SNNs, their neurobiological underpinnings, and the computational advantages they bring to signal processing, particularly in handling the temporal and spatial complexities inherent in physiological and speech data. Comparative analyses with conventional neural network models are presented to underscore the superior efficiency, lower power consumption, and higher temporal resolution of SNNs. The review further explores challenges and future prospects, highlighting the potential of SNNs to revolutionize wearable healthcare monitoring systems, neuroprosthetic devices, and natural language processing technologies. By providing a comprehensive overview of current strategies, this review aims to inspire innovative approaches in the field, fostering advances in real-time and energy-efficient processing of complex biological signals.

将尖峰神经网络(SNN)整合到生理和语音信号的分析和解释中,已成为一种开创性的方法,不仅能提高性能,还能深入了解潜在的生物过程。本综述旨在总结 SNNs 在这些领域的主要进展、方法和应用,突出其模仿人脑时间动态和效率的独特能力。我们深入探讨了 SNN 的核心原理、其神经生物学基础以及它们为信号处理带来的计算优势,尤其是在处理生理和语音数据固有的时间和空间复杂性方面。综述还介绍了与传统神经网络模型的比较分析,以强调神经网络的卓越效率、低功耗和更高的时间分辨率。综述进一步探讨了挑战和未来前景,强调了 SNNs 在革新可穿戴医疗监控系统、神经义肢设备和自然语言处理技术方面的潜力。通过对当前策略的全面概述,本综述旨在激发该领域的创新方法,促进复杂生物信号的实时和节能处理方面的进步。
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引用次数: 0
Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives. 探索尖峰神经网络在生物医学应用中的潜力:优势、局限和未来展望。
IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL Pub Date : 2024-06-20 eCollection Date: 2024-09-01 DOI: 10.1007/s13534-024-00403-1
Eunsu Kim, Youngmin Kim

In this paper, a comprehensive exploration is undertaken to elucidate the utilization of Spiking Neural Networks (SNNs) within the biomedical domain. The investigation delves into the experimentally validated advantages of SNNs in comparison to alternative models like LSTM, while also critically examining the inherent limitations of SNN classifiers or algorithms. SNNs exhibit distinctive advantages that render them particularly apt for targeted applications within the biomedical field. Over time, SNNs have undergone extensive scrutiny in realms such as neuromorphic processing, Brain-Computer Interfaces (BCIs), and Disease Diagnosis. Notably, SNNs demonstrate a remarkable affinity for the processing and analysis of biomedical signals, including but not limited to electroencephalogram (EEG), electromyography (EMG), and electrocardiogram (ECG) data. This paper initiates its exploration by introducing some of the biomedical applications of EMG, such as the classification of hand gestures and motion decoding. Subsequently, the focus extends to the applications of SNNs in the analysis of EEG and ECG signals. Moreover, the paper delves into the diverse applications of SNNs in specific anatomical regions, such as the eyes and noses. In the final sections, the paper culminates with a comprehensive analysis of the field, offering insights into the advantages, disadvantages, challenges, and opportunities introduced by various SNN models in the realm of healthcare and biomedical domains. This holistic examination provides a nuanced perspective on the potential transformative impact of SNN across a spectrum of applications within the biomedical landscape.

本文对尖峰神经网络(SNN)在生物医学领域的应用进行了全面探讨。与 LSTM 等替代模型相比,本研究深入探讨了经实验验证的 SNN 的优势,同时还严格审查了 SNN 分类器或算法的固有局限性。SNNs 具有独特的优势,特别适合生物医学领域的目标应用。随着时间的推移,SNN 在神经形态处理、脑机接口 (BCI) 和疾病诊断等领域受到了广泛的关注。值得注意的是,SNN 在处理和分析生物医学信号(包括但不限于脑电图(EEG)、肌电图(EMG)和心电图(ECG)数据)方面表现出非凡的亲和力。本文首先介绍了 EMG 的一些生物医学应用,如手势分类和运动解码。随后,重点扩展到 SNN 在脑电图和心电图信号分析中的应用。此外,本文还深入探讨了 SNN 在特定解剖区域(如眼睛和鼻子)的各种应用。在最后几节,论文对该领域进行了全面分析,深入探讨了各种 SNN 模型在医疗保健和生物医学领域的优势、劣势、挑战和机遇。这种全面的研究提供了一个细致入微的视角,让我们了解 SNN 在生物医学领域的各种应用中可能产生的变革性影响。
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引用次数: 0
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Biomedical Engineering Letters
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