{"title":"Artificial Intelligence for Emerging Technology in Surgery: Systematic Review and Validation","authors":"Ephraim Nwoye;Wai Lok Woo;Bin Gao;Tobenna Anyanwu","doi":"10.1109/RBME.2022.3183852","DOIUrl":"10.1109/RBME.2022.3183852","url":null,"abstract":"Surgery is a high-risk procedure of therapy and is associated to post trauma complications of longer hospital stay, estimated blood loss and long duration of surgeries. Reports have suggested that over 2.5% patients die during and post operation. This paper is aimed at systematic review of previous research on artificial intelligence (AI) in surgery, analyzing their results with suitable software to validate their research by obtaining same or contrary results. Six published research articles have been reviewed across three continents. These articles have been re-validated using software including SPSS and MedCalc to obtain the statistical features such as the mean, standard deviation, significant level, and standard error. From the significant values, the experiments are then classified according to the null (p < 0.05) or alternative (p>0.05) hypotheses. The results obtained from the analysis have suggested significant difference in operating time, docking time, staging time, and estimated blood loss but show no significant difference in length of hospital stay, recovery time and lymph nodes harvested between robotic assisted surgery using AI and normal conventional surgery. From the evaluations, this research suggests that AI-assisted surgery improves over the conventional surgery as safer and more efficient system of surgery with minimal or no complications.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"241-259"},"PeriodicalIF":17.6,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9359911","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}
Arif Mohd. Kamal;Tushar Sakorikar;Uttam M. Pal;Hardik J. Pandya
{"title":"Engineering Approaches for Breast Cancer Diagnosis: A Review","authors":"Arif Mohd. Kamal;Tushar Sakorikar;Uttam M. Pal;Hardik J. Pandya","doi":"10.1109/RBME.2022.3181700","DOIUrl":"10.1109/RBME.2022.3181700","url":null,"abstract":"Breast cancer is a leading cause of mortality among women. The patient's survival rate is uncertain due to the limitations in the accuracy of diagnosis and effective monitoring during cancer treatment. The key to efficaciously controlling cancer on a larger scale is effective diagnosis at an early stage of cancer by distinguishing the vital signatures of the diseased from the normal breast tissue. The breast tissue is a heterogeneous turbid media that exhibits multifaceted bulk tissue properties. Various sensing modalities can yield distinct tissue behavior for cancer and adjacent normal tissues, serving as a basis for cancer diagnosis. A novel multimodal diagnostic tool that can concurrently assess the optical, electrical, and mechanical bulk tissue properties can substantially augment the clinical findings such as histopathology, potentially aiding the clinician to establish an accurate and rapid diagnosis of cancer. This review aims to discuss the clinical and engineering aspects along with the unmet challenges of these physical sensing modalities, primarily in the field of optical, electrical, and mechanical. The challenges of combining two or more of these sensing modalities that can significantly enhance the effectiveness of the clinical diagnostic tools are further investigated.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"687-705"},"PeriodicalIF":17.6,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9720538","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}
{"title":"Dynamical Models in Neuroscience From a Closed-Loop Control Perspective","authors":"Sebastián Martínez;Demián García-Violini;Mariano Belluscio;Joaquín Piriz;Ricardo Sánchez-Peña","doi":"10.1109/RBME.2022.3180559","DOIUrl":"10.1109/RBME.2022.3180559","url":null,"abstract":"Modifying neural activity is a substantial goal in neuroscience that facilitates the understanding of brain functions and the development of medical therapies. Neurobiological models play an essential role, contributing to the understanding of the underlying brain dynamics. In this context, control systems represent a fundamental tool to provide a correct articulation between model stimulus (system inputs) and outcomes (system outputs). However, throughout the literature there is a lack of discussions on neurobiological models, from the formal control perspective. In general, existing control proposals applied to this family of systems, are developed empirically, without theoretical and rigorous framework. Thus, the existing control solutions, present clear and significant limitations. The focus of this work is to survey dynamical neurobiological models that could serve for closed-loop control schemes or for simulation analysis. Consequently, this paper provides a comprehensive guide to discuss and analyze control-oriented neurobiological models. It also provides a potential framework to adequately tackle control problems that could modify the behavior of single neurons or networks. Thus, this study constitutes a key element in the upcoming discussions and studies regarding control methodologies applied to neurobiological systems, to extend the present research and understanding horizon for this field.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"706-721"},"PeriodicalIF":17.6,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9720537","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}
{"title":"A Review of Recent Advances and Future Developments in Fetal Phonocardiography","authors":"Radana Kahankova;Martina Mikolasova;Rene Jaros;Katerina Barnova;Martina Ladrova;Radek Martinek","doi":"10.1109/RBME.2022.3179633","DOIUrl":"10.1109/RBME.2022.3179633","url":null,"abstract":"Fetal phonocardiography (fPCG) is receiving attention as it is a promising method for continuous fetal monitoring due to its non-invasive and passive nature. However, it suffers from the interference from various sources, overlapping the desired signal in the time and frequency domains. This paper introduces the state-of-the-art methods used for fPCG signal extraction and processing, as well as means of detection and classification of various features defining fetal health state. It also provides an extensive summary of remaining challenges, along with the practical insights and suggestions for the future research directions.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"653-671"},"PeriodicalIF":17.6,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09786823.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9358720","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}
{"title":"Saline-Infused Radiofrequency Ablation: A Review on the Key Factors for a Safe and Reliable Tumour Treatment","authors":"Antony S. K. Kho;Ean H. Ooi;Ji J. Foo;Ean T. Ooi","doi":"10.1109/RBME.2022.3179742","DOIUrl":"10.1109/RBME.2022.3179742","url":null,"abstract":"Radiofrequency ablation (RFA) combined with saline infusion into tissue is a promising technique to ablate larger tumours. Nevertheless, the application of saline-infused RFA remains at clinical trials due to the contradictory findings as a result of the inconsistencies in experimental procedures. These inconsistencies not only magnify the number of factors to consider during the treatment, but also obscure the understanding of the role of saline in enlarging the coagulation zone. Consequently, this can result in major complications, which includes unwanted thermal damages to adjacent tissues and also incomplete ablation of the tumour. This review aims to identify the key factors of saline responsible for enlarging the coagulation zone during saline-infused RFA, and provide a proper understanding on their effects that is supported with findings from computational studies to ensure a safe and reliable cancer treatment.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"17 ","pages":"310-321"},"PeriodicalIF":17.6,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130536826","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}
{"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":"16 ","pages":"514-529"},"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}
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":"16 ","pages":"472-486"},"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}
Chi Sang Choy;Shaun L. Cloherty;Elena Pirogova;Qiang Fang
{"title":"Virtual Reality Assisted Motor Imagery for Early Post-Stroke Recovery: A Review","authors":"Chi Sang Choy;Shaun L. Cloherty;Elena Pirogova;Qiang Fang","doi":"10.1109/RBME.2022.3165062","DOIUrl":"10.1109/RBME.2022.3165062","url":null,"abstract":"Stroke is a serious neurological disease that may lead to long-term disabilities and even death for stroke patients worldwide. The acute period, (\u0000<inline-formula><tex-math>$le$</tex-math></inline-formula>\u00001 mo post-stroke), is crucial for rehabilitation but the current standard clinical practice may be ineffective for patients with severe motor impairment, since most rehabilitation programs involve physical movement. Imagined movement – the so-called motor imagery (MI) – has been shown to activate motor areas of the brain without physical movement. MI therefore offers an opportunity for early rehabilitation of stroke patients. MI, however, is not widely employed in clinical practice due to a lack of evidence-based research. Here, we review MI-based approaches to rehabilitation of stroke patients and immersive virtual reality (VR) technologies to potentially assist MI and thus, promote recovery of motor function.","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"16 ","pages":"487-498"},"PeriodicalIF":17.6,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/4664312/10007429/09749920.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9735257","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}
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":"16 ","pages":"530-559"},"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}
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}