IEEE Reviews in Biomedical Engineering最新文献_第6页

A Review of Recent Advances and Future Developments in Fetal Phonocardiography 胎儿心音描记术的最新进展和未来发展

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-06-02 DOI: 10.1109/RBME.2022.3179633

Radana Kahankova;Martina Mikolasova;Rene Jaros;Katerina Barnova;Martina Ladrova;Radek Martinek

引用次数: 6

Saline-Infused Radiofrequency Ablation: A Review on the Key Factors for a Safe and Reliable Tumour Treatment 盐注射频消融术：安全可靠的肿瘤治疗关键因素综述

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-06-02 DOI: 10.1109/RBME.2022.3179742

Antony S. K. Kho;Ean H. Ooi;Ji J. Foo;Ean T. Ooi

引用次数: 1

Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback 基于多模态感觉反馈的组织检查训练机器人模拟器

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-04-19 DOI: 10.1109/RBME.2022.3168422

Liang He;Perla Maiolino;Florence Leong;Thilina Dulantha Lalitharatne;Simon de Lusignan;Mazdak Ghajari;Fumiya Iida;Thrishantha Nanayakkara

{"title":"Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback","authors":"Liang He;Perla Maiolino;Florence Leong;Thilina Dulantha Lalitharatne;Simon de Lusignan;Mazdak Ghajari;Fumiya Iida;Thrishantha Nanayakkara","doi":"10.1109/RBME.2022.3168422","DOIUrl":"10.1109/RBME.2022.3168422","url":null,"abstract":"Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":17.6,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9720072","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: 5

A Review of Techniques for Surface Electromyography Signal Quality Analysis 表面肌电信号质量分析技术综述

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-04-05 DOI: 10.1109/RBME.2022.3164797

Emma Farago;Dawn MacIsaac;Michelle Suk;Adrian D. C. Chan

{"title":"A Review of Techniques for Surface Electromyography Signal Quality Analysis","authors":"Emma Farago;Dawn MacIsaac;Michelle Suk;Adrian D. C. Chan","doi":"10.1109/RBME.2022.3164797","DOIUrl":"10.1109/RBME.2022.3164797","url":null,"abstract":"Electromyography (EMG) signals are instrumental in a variety of applications including prosthetic control, muscle health assessment, rehabilitation, and workplace monitoring. Signal contaminants including noise, interference, and artifacts can degrade the quality of the EMG signal, leading to misinterpretation; therefore it is important to ensure that collected EMG signals are of sufficient quality prior to further analysis. A literature search was conducted to identify current approaches for detecting, identifying, and quantifying contaminants within surface EMG signals. We identified two main strategies: 1) bottom-up approaches for identifying specific and well-characterized contaminants and 2) top-down approaches for detecting anomalous EMG signals or outlier channels in high-density EMG arrays. The best type(s) of approach are dependent on the circumstances of data collection including the environment, the susceptibility of the application to contaminants, and the resilience of the application to contaminants. Further research is needed for assessing EMG with multiple simultaneous contaminants, identifying ground-truths for clean EMG data, and developing user-friendly and autonomous methods for EMG signal quality analysis.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":17.6,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9365457","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: 12

Virtual Reality Assisted Motor Imagery for Early Post-Stroke Recovery: A Review 虚拟现实辅助运动图像用于脑卒中后早期恢复：综述

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-04-05 DOI: 10.1109/RBME.2022.3165062

Chi Sang Choy;Shaun L. Cloherty;Elena Pirogova;Qiang Fang

引用次数: 5

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury 综述：新兴的基于眼睛的创伤性脑损伤诊断技术

IF 17.6 1区工程技术

IEEE Reviews in Biomedical Engineering Pub Date : 2022-03-23 DOI: 10.1109/RBME.2022.3161352

Georgia Harris;Jonathan James Stanley Rickard;Gibran Butt;Liam Kelleher;Richard James Blanch;Jonathan Cooper;Pola Goldberg Oppenheimer

{"title":"Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury","authors":"Georgia Harris;Jonathan James Stanley Rickard;Gibran Butt;Liam Kelleher;Richard James Blanch;Jonathan Cooper;Pola Goldberg Oppenheimer","doi":"10.1109/RBME.2022.3161352","DOIUrl":"10.1109/RBME.2022.3161352","url":null,"abstract":"The study of ocular manifestations of neurodegenerative disorders, \u0000<italic>Oculomics,</i>\u0000 is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the “silent epidemic” is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":17.6,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9740402","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9365613","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

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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