Biomedical Engineering Letters最新文献

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

Biomedical Engineering Letters Pub Date : 2024-08-08 DOI: 10.1007/s13534-024-00414-y

Sanjay Mane, Paul Jacob, Vadiraj Hemadri, Prasenjit Dey, Sunil Bhand, S. Tripathi

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

Biomedical Engineering Letters 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

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

Biomedical Engineering Letters Pub Date : 2024-07-26 DOI: 10.1007/s13534-024-00409-9

Geunho Jung, Jonghan Lee, Semin Kim

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

Biomedical Engineering Letters 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

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

Biomedical Engineering Letters Pub Date : 2024-07-11 DOI: 10.1007/s13534-024-00406-y

S. Baek, Jaewon Lee

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

Biomedical Engineering Letters 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

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

Biomedical Engineering Letters Pub Date : 2024-07-07 DOI: 10.1007/s13534-024-00407-x

Kideok Kim, Kunhee Lee, Jiyoung Hwang, Ui-Lyong Lee, Joong Yull Park

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

Biomedical Engineering Letters Pub Date : 2024-07-05 DOI: 10.1007/s13534-024-00405-z

Sang Ho Choi

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

Biomedical Engineering Letters Pub Date : 2024-06-25 eCollection Date: 2024-09-01 DOI: 10.1007/s13534-024-00404-0

Sung Soo Park, Young-Seok Choi

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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

Biomedical Engineering Letters Pub Date : 2024-06-20 eCollection Date: 2024-09-01 DOI: 10.1007/s13534-024-00403-1

Eunsu Kim, Youngmin Kim

{"title":"Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives.","authors":"Eunsu Kim, Youngmin Kim","doi":"10.1007/s13534-024-00403-1","DOIUrl":"10.1007/s13534-024-00403-1","url":null,"abstract":"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.","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0