IEEE Reviews in Biomedical Engineering最新文献_第8页

The Application of Nanotechnology for Quantification of Circulating Tumour DNA in Liquid Biopsies: A Systematic Review 纳米技术在液体活检中定量检测循环肿瘤DNA的应用：系统综述

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-03-18 DOI: 10.1109/RBME.2022.3159389

Nathan J. W. Wu;Matthew Aquilina;Bin-Zhi Qian;Remco Loos;Ines Gonzalez-Garcia;Cristina C. Santini;Katherine E. Dunn

{"title":"The Application of Nanotechnology for Quantification of Circulating Tumour DNA in Liquid Biopsies: A Systematic Review","authors":"Nathan J. W. Wu;Matthew Aquilina;Bin-Zhi Qian;Remco Loos;Ines Gonzalez-Garcia;Cristina C. Santini;Katherine E. Dunn","doi":"10.1109/RBME.2022.3159389","DOIUrl":"10.1109/RBME.2022.3159389","url":null,"abstract":"Technologies for quantifying circulating tumour DNA (ctDNA) in liquid biopsies could enable real-time measurements of cancer progression, profoundly impacting patient care. Sequencing methods can be too complex and time-consuming for regular point-of-care monitoring, but nanotechnology offers an alternative, harnessing the unique properties of objects tens to hundreds of nanometres in size. This systematic review was performed to identify all examples of nanotechnology-based ctDNA detection and assess their potential for clinical use. Google Scholar, PubMed, Web of Science, Google Patents, Espacenet and Embase/MEDLINE were searched up to 23rd March 2021. The review identified nanotechnology-based methods for ctDNA detection for which quantitative measures (e.g., limit of detection, LOD) were reported and biologically relevant samples were used. The pre-defined inclusion criteria were met by 66 records. LODs ranged from 10 zM to 50nM. 25 records presented an LOD of 10fM or below. Nanotechnology-based approaches could provide the basis for the next wave of advances in ctDNA diagnostics, enabling analysis at the point-of-care, but none are currently used clinically. Further work is needed in development and validation; trade-offs are expected between different performance measures e.g., number of sequences detected and time to result.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"499-513"},"PeriodicalIF":17.6,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09737698.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9371134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Contactless WiFi Sensing and Monitoring for Future Healthcare - Emerging Trends, Challenges, and Opportunities 面向未来医疗保健的非接触式WiFi传感和监测-新兴趋势、挑战和机遇

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-03-07 DOI: 10.1109/RBME.2022.3156810

Yao Ge;Ahmad Taha;Syed Aziz Shah;Kia Dashtipour;Shuyuan Zhu;Jonathan Cooper;Qammer H. Abbasi;Muhammad Ali Imran

{"title":"Contactless WiFi Sensing and Monitoring for Future Healthcare - Emerging Trends, Challenges, and Opportunities","authors":"Yao Ge;Ahmad Taha;Syed Aziz Shah;Kia Dashtipour;Shuyuan Zhu;Jonathan Cooper;Qammer H. Abbasi;Muhammad Ali Imran","doi":"10.1109/RBME.2022.3156810","DOIUrl":"10.1109/RBME.2022.3156810","url":null,"abstract":"WiFi sensing has received recent and significant interest from academia, industry, healthcare professionals, and other caregivers (including family members) as a potential mechanism to monitor our aging population at a distance without deploying devices on users’ bodies. In particular, these methods have the potential to detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems arises from practical advantages including its ease of operation indoors as well as ready compliance from monitored individuals. Unlike other sensing methods, such as wearables, camera-based imaging, and acoustic-based solutions, WiFi technology is easy to implement and unobtrusive. This paper reviews the current state-of-the-art research on collecting and analyzing channel state information extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, including untapped areas of research and related trends. This work aims to provide an overarching view in understanding the technology and discusses its use-cases from a perspective that considers hardware, advanced signal processing, and data acquisition.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"171-191"},"PeriodicalIF":17.6,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09729463.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9713747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Unsupervised ECG Analysis: A Review 无监督心电图分析：综述

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-02-28 DOI: 10.1109/RBME.2022.3154893

Kasra Nezamabadi;Neda Sardaripour;Benyamin Haghi;Mohamad Forouzanfar

{"title":"Unsupervised ECG Analysis: A Review","authors":"Kasra Nezamabadi;Neda Sardaripour;Benyamin Haghi;Mohamad Forouzanfar","doi":"10.1109/RBME.2022.3154893","DOIUrl":"10.1109/RBME.2022.3154893","url":null,"abstract":"Electrocardiography is the gold standard technique for detecting abnormal heart conditions. Automatic detection of electrocardiogram (ECG) abnormalities helps clinicians analyze the large amount of data produced daily by cardiac monitors. As thenumber of abnormal ECG samples with cardiologist-supplied labels required to train supervised machine learning models is limited, there is a growing need for unsupervised learning methods for ECG analysis. Unsupervised learning aims to partition ECG samples into distinct abnormality classes without cardiologist-supplied labels–a process referred to as ECG clustering. In addition to abnormality detection, ECG clustering has recently discovered inter and intra-individual patterns that reveal valuable information about the whole body and mind, such as emotions, mental disorders, and metabolic levels. ECG clustering can also resolve specific challenges facing supervised learning systems, such as the imbalanced data problem, and can enhance biometric systems. While several reviews exist on supervised ECG systems, a comprehensive review of unsupervised ECG analysis techniques is still lacking. This study reviews ECG clustering techniques developed mainly in the last decade. The focus will be on recent machine learning and deep learning algorithms and their practical applications. We critically review and compare these techniques, discuss their applications and limitations, and provide future research directions. This review provides further insights into ECG clustering and presents the necessary information required to adopt the appropriate algorithm for a specific application.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"208-224"},"PeriodicalIF":17.6,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9728418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents 神经元信号处理中的数据转换：照亮信息内容的强大工具

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-02-14 DOI: 10.1109/RBME.2022.3151340

MohammadAli Shaeri;Amir M. Sodagar

{"title":"Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents","authors":"MohammadAli Shaeri;Amir M. Sodagar","doi":"10.1109/RBME.2022.3151340","DOIUrl":"10.1109/RBME.2022.3151340","url":null,"abstract":"Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today’s technological advancements, the physical development of high-density and high-resolution neural interfaces has been made possible. This is where the critical bottleneck in receiving the expected functionality from such devices shifts to transferring, processing, and subsequently analyzing the massive neurophysiological extra-cellular data recorded. To respond to this inevitable concern, a spectrum of neuronal signal processing techniques have been proposed to extract task-related informative content of the signals conveying neuronal activities, and eliminate the irrelevant contents. Such techniques provide powerful tools for a wide range of neuroscience research, from low-level perception to high-level cognition. Data transformations are among the most efficient processing techniques that serve this purpose by properly changing the data representation. Mapping the data from its original domain (i.e., the time-space domain) to a new representational domain, data transformations change the viewing angle of observing the informative content of the data. This paper reviews the employment of data transformations in order to process neuronal signals and their three key applications, including spike detection, spike sorting, and data compression.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"611-626"},"PeriodicalIF":17.6,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9358694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bioprinting: A Strategy to Build Informative Models of Exposure and Disease 生物打印：建立暴露和疾病信息模型的策略

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-27 DOI: 10.1109/RBME.2022.3146293

Jose Caceres-Alban;Midori Sanchez;Fanny L. Casado

{"title":"Bioprinting: A Strategy to Build Informative Models of Exposure and Disease","authors":"Jose Caceres-Alban;Midori Sanchez;Fanny L. Casado","doi":"10.1109/RBME.2022.3146293","DOIUrl":"10.1109/RBME.2022.3146293","url":null,"abstract":"Novel additive manufacturing techniques are revolutionizing fields of industry providing more dimensions to control and the versatility of fabricating multi-material products. Medical applications hold great promise to manufacture constructs of mixed biologically compatible materials together with functional cells and tissues. We reviewed technologies and promising developments nurturing innovation of physiologically relevant models to study safety of chemicals that are hard to reproduce in current models, or diseases for which there are no models available. Extrusion-, inkjet- and laser-assisted bioprinting are the most used techniques. Hydrogels as constituents of bioinks and biomaterial inks are the most versatile materials to recreate physiological and pathophysiological microenvironments. The highlighted bioprinted models were chosen because they guarantee post-printing cellular viability while maintaining desirable mechanical properties of their constitutive bioinks or biomaterial inks to ensure their printability. Bioprinting is being readily adopted to overcome ethical concerns of in vivo models and improve the automation, reproducibility, geometry stability of traditional \u0000<italic>in vitro</i>\u0000 models. The challenges for advancing the technological level readiness of bioprinting require overcoming heterogeneity, microstructural complexity, dynamism and integration with other models, to generate multi-organ platforms that can inform about biological responses to chemical exposure, disease development and efficacy of novel therapies.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"594-610"},"PeriodicalIF":17.6,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09695320.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9371124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial: A Message From the Outgoing Editor-in-Chief 社论：即将离任的主编寄语

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-20 DOI: 10.1109/RBME.2021.3130485

Yuan-Ting Zhang

引用次数: 0

IEEE Engineering in Medicine and Biology Society IEEE医学与生物工程学会

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-20 DOI: 10.1109/RBME.2021.3130508

引用次数: 0

Frontcover 封面

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-20 DOI: 10.1109/RBME.2021.3130482

引用次数: 0

IEEE Reviews in Biomedical Engineering (R-BME) IEEE生物医学工程评论（R-BME）

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-20 DOI: 10.1109/RBME.2021.3130484

引用次数: 0

Hemodynamic Modeling, Medical Imaging, and Machine Learning and Their Applications to Cardiovascular Interventions 血液动力学建模、医学成像和机器学习及其在心血管干预中的应用

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-01-11 DOI: 10.1109/RBME.2022.3142058

Mason Kadem;Louis Garber;Mohamed Abdelkhalek;Baraa K. Al-Khazraji;Zahra Keshavarz-Motamed

{"title":"Hemodynamic Modeling, Medical Imaging, and Machine Learning and Their Applications to Cardiovascular Interventions","authors":"Mason Kadem;Louis Garber;Mohamed Abdelkhalek;Baraa K. Al-Khazraji;Zahra Keshavarz-Motamed","doi":"10.1109/RBME.2022.3142058","DOIUrl":"10.1109/RBME.2022.3142058","url":null,"abstract":"Cardiovascular disease is a deadly global health crisis that carries a substantial financial burden. Innovative treatment and management of cardiovascular disease straddles medicine, personalized hemodynamic modeling, machine learning, and modern imaging to help improve patient outcomes and reduce the economic impact. Hemodynamic modeling offers a non-invasive method to provide clinicians with new pre- and post- procedural metrics and aid in the selection of treatment options. Medical imaging is an integral part in clinical workflows for understanding and managing cardiac disease and interventions. Coupling machine learning with modeling, and cardiovascular imaging, provides faster modeling, improved data fidelity, and an enhanced understanding and earlier detection of cardiovascular anomalies, leading to the development of patient-specific diagnostic and predictive tools for characterizing and assessing cardiovascular outcomes. Herein, we provide a scoping review of translational hemodynamic modeling, medical imaging, and machine learning and their applications to cardiovascular interventions. We particularly focus on providing an intuitive understanding of each of these approaches and their ability to support decision making during important clinical milestones.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"403-423"},"PeriodicalIF":17.6,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9364000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13