Pub Date : 2024-08-08DOI: 10.1007/s13534-024-00414-y
Sanjay Mane, Paul Jacob, Vadiraj Hemadri, Prasenjit Dey, Sunil Bhand, S. Tripathi
{"title":"Characterization of the phagocytic ability of white blood cells separated using a single curvature spiral microfluidic device","authors":"Sanjay Mane, Paul Jacob, Vadiraj Hemadri, Prasenjit Dey, Sunil Bhand, S. Tripathi","doi":"10.1007/s13534-024-00414-y","DOIUrl":"https://doi.org/10.1007/s13534-024-00414-y","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929346","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}
Pub Date : 2024-07-27DOI: 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
{"title":"Quantitative biomechanical analysis in validating a video-based model to remotely assess physical frailty: a potential solution to telehealth and globalized remote-patient monitoring","authors":"Mohammad Dehghan Rouzi, Myeounggon Lee, Jaewon Beom, Sanam Bidadi, Abderrahman Ouattas, Gozde Cay, A. Momin, Michele K. York, M. Kunik, Bijan Najafi","doi":"10.1007/s13534-024-00410-2","DOIUrl":"https://doi.org/10.1007/s13534-024-00410-2","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141797625","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}
Pub Date : 2024-07-11DOI: 10.1007/s13534-024-00406-y
S. Baek, Jaewon Lee
{"title":"Snn and sound: a comprehensive review of spiking neural networks in sound","authors":"S. Baek, Jaewon Lee","doi":"10.1007/s13534-024-00406-y","DOIUrl":"https://doi.org/10.1007/s13534-024-00406-y","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656812","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}
Pub Date : 2024-07-09DOI: 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}
Pub Date : 2024-07-07DOI: 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}
Pub Date : 2024-07-05DOI: 10.1007/s13534-024-00405-z
Sang Ho Choi
{"title":"Spiking neural networks for biomedical signal analysis","authors":"Sang Ho Choi","doi":"10.1007/s13534-024-00405-z","DOIUrl":"https://doi.org/10.1007/s13534-024-00405-z","url":null,"abstract":"","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676709","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}
Pub Date : 2024-06-25eCollection Date: 2024-09-01DOI: 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.
{"title":"Spiking neural networks for physiological and speech signals: a review.","authors":"Sung Soo Park, Young-Seok Choi","doi":"10.1007/s13534-024-00404-0","DOIUrl":"10.1007/s13534-024-00404-0","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362433/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113344","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}
Pub Date : 2024-06-20eCollection Date: 2024-09-01DOI: 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.
{"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":"<p><p>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.</p>","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}
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