IEEE Reviews in Biomedical Engineering最新文献

{"title":"Control Algorithms for Adaptive Deep Brain Stimulation in Parkinson's Disease.","authors":"Jakub Orlowski, Madeleine M Lowery","doi":"10.1109/RBME.2026.3723716","DOIUrl":"10.1109/RBME.2026.3723716","url":null,"abstract":"<p><p>Thirty years on from the introduction of deep brain stimulation as a therapy for Parkinson's disease, adaptive deep brain stimulation (aDBS) is poised to transform neural stimulation for the treatment of motor disorders. Implementation of aDBS has been facilitated by the identification of biomarkers that reflect patients' clinical states and the introduction of hardware allowing simultaneous sensing and stimulation. However, the most appropriate algorithms for aDBS remain unclear. This review provides an overview of control algorithms used in computational, animal and human studies of aDBS in Parkinson's disease to date. Although shown to be effective and well-tolerated, only relatively simple aDBS algorithms have been used clinically. Computational studies have explored a wider range of more advanced algorithms which promise superior performance but need to be rigorously tested and compared against clinically-tested techniques before translating to patients. The need for comparative studies is further driven by advances in machine learning, which promise patient-specific programming solutions but require large datasets and have high computational requirements. Understanding the advantages and limitations of these different algorithms is critical for aDBS to reach its potential and enable personalized treatment to provide maximum patient benefit.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148888935","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":"The Next Paradigm in Medical AI: A Survey of Agentic AI in Biomedicine.","authors":"Ali Abdollahi, Mohammad Amin Rezaei, Xi Wang, Dejia Cai, Sunan He, Seyed Moein Ayyoubzadeh, Yuxiang Nie, Hao Chen","doi":"10.1109/RBME.2026.3704162","DOIUrl":"10.1109/RBME.2026.3704162","url":null,"abstract":"<p><p>Biomedical AI is increasingly shaped by policy-bound, multi-step clinical workflows and non-stationary, multimodal data and tools. In this setting, the field is moving beyond static predictors toward agentic systems, enabled by foundation models that maintain task-relevant state and operate through a closed perceive$rightarrow$plan$rightarrow$act$rightarrow$observe loop under explicit oversight. However, the field lacks a coherent account that defines biomedical agency, relates foundational model capabilities to agent behaviors, and traces the pathway from pretraining to domain-adapted, deployable systems. This survey offers such an account by synthesizing operational boundaries of agency and framing six core components (memory, planning, reflection, tool use, dialogue, and collaboration) as foundational agent-enabling capabilities that drive the transition from isolated pipelines to fully realized agents. This survey situates these perspectives along the model-building pathway, from pretraining through post-training adaptation to the orchestration mechanisms that operationalize agents. We highlight safety and governance considerations for high-stakes settings, emphasizing the fidelity of process and reasoning, uncertainty and abstention, privacy and provenance, and human oversight. Taken together, this survey provides a structured synthesis of how recent work connects foundation models to governable biomedical agentic systems and distills the recurring challenges and directions identified in the literature for reliable, accountable deployment.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148437416","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":"Bridging the Gap - Advancing Microfluidics From Laboratory to Point-of-Care.","authors":"Baobao Lin, Zhijie Li, Yogesh Movendane, Xingjian Jin, Xianyou Sun, Bao Li, Wu Zeng, Peng Liu, Chwee Teck Lim","doi":"10.1109/RBME.2026.3688651","DOIUrl":"10.1109/RBME.2026.3688651","url":null,"abstract":"<p><p>Microfluidic technology offers a transformative approach for biomedical diagnostics by enabling miniaturization and automation of analytical procedures. Its integration into Point-of-Care Testing (POCT) holds promise for rapid, decentralized, and accessible diagnostics. However, translating laboratory microfluidics into practical POCT devices faces key challenges, including the handling of complex clinical samples, integration of multiple functions on a single chip, ensuring reliable analytical performance in clinical deployment scenarios, and meeting regulatory requirements. This review explores the evolution of microfluidic technology and the unique requirements for POCT, while highlighting the main challenges in translating laboratory systems into practical applications. Representative case studies and recent technological advances are presented to illustrate progress and solutions, and future directions are discussed with a focus on strategies to bridge the gap between laboratory research and effective, real-world POCT deployment.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147976155","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":"Review of Current Advances in Ultrasound Computed Tomography for Medical Imaging.","authors":"Weicheng Yan, Lei He, Hui Zhang, Zesong Wang, Xiaolu Zeng, Hongrui Tan, Xiang Zhou, Yun Wu, Zhaohui Liu, Liren Fan, Pengcheng Zhang, Zhaoyuan Guo, Gaoxiang Xie, Chao Cai, Mingyue Ding, Ming Yuchi, Wu Qiu","doi":"10.1109/RBME.2026.3686264","DOIUrl":"10.1109/RBME.2026.3686264","url":null,"abstract":"<p><p>Ultrasound Computed Tomography (USCT) represents a paradigm shift in medical imaging, offering quantitative, high-resolution tissue characterization for diverse anatomical regions including breast, musculoskeletal system, brain, and lungs. By capturing the full ultrasonic wavefield through dedicated transducer arrays, USCT enables reconstruction of intrinsic tissue properties such as sound speed, attenuation, and acoustic impedance. Unlike conventional ultrasound, USCT provides three fundamental advantages: full-angle tomographic reconstruction, quantitative multi-parameter imaging capabilities, and operator-independent standardized acquisition-all while maintaining ultrasound's inherent safety and cost-effectiveness. While clinical adoption is still evolving, the technology has achieved significant milestones with several commercially available systems receiving regulatory approval for breast imaging. This review synthesizes recent advances across five critical domains: system hardware design, reflection imaging, quantitative multi-parameter reconstruction (particularly through full-waveform inversion), precision calibration methodologies, and expanding clinical applications. Additionally, we have offered a comprehensive review of the application of deep learning-related technologies in USCT. By comprehensively analyzing current challenges and emerging trends, this work provides researchers and clinicians with an essential reference for understanding the state of the art and identifying pivotal pathways toward widespread clinical implementation of USCT technology.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943198","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":"Gas Embolism: Fundamentals, Diagnosis, and Treatment.","authors":"Mohammad Mahdi Mardanpour, Dan V Nicolau, Richard E Moon, Neal W Pollock, David M Eckmann, Dan V Nicolau","doi":"10.1109/RBME.2026.3677292","DOIUrl":"10.1109/RBME.2026.3677292","url":null,"abstract":"<p><p>Invasive medical interventions or abrupt reductions in ambient pressure can result in intravascular gas embolism. The accumulation of gas bubbles initiates a cascade of pathophysiological phenomena progressing from platelet activation to ischemia and neurological dysfunction. This review integrates current knowledge of the biophysical mechanisms of bubble nucleation, progression, and vascular occlusion into a framework aligned with the adverse physiological consequences on circulation. The discussion further addresses the present state of clinical practice, diagnostic approaches, and therapeutic interventions. Initial studies on gas embolism utilized in vivo models, and recent in vitro and in silico platforms have provided reproducible and cost-efficient experimental approaches. The initial symptoms of gas embolism often overlap with stroke, myocardial infarction, or sepsis. Reliable detection of intravascular gas bubbles is constrained by the sensitivity, resolution, and accessibility of existing imaging modalities, particularly in systemic cases. Current treatment frameworks emphasize hyperbaric oxygen therapy, while adjunct pharmacological strategies to improve clinical outcomes are under investigation. The challenges responsible for the persistent neglect of gas embolism in both clinical and academic contexts are discussed, and a forward-looking perspective on strategies to overcome these barriers is presented.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784392","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":"Sonogenetics for Precision Medicine: A Focus on Immunoengineering and Genome Engineering.","authors":"Chi Woo Yoon, Linshan Zhu, Xue Dong, Zhou Yuan, Yunjia Qu, Peixiang He, Longwei Liu, Yingxiao Wang","doi":"10.1109/RBME.2026.3675985","DOIUrl":"10.1109/RBME.2026.3675985","url":null,"abstract":"<p><p>Ultrasound can penetrate centimetres of soft tissue, focus energy with millimetre precision, and operate safely under real-time image guidance. Leveraging these advantages, sonogenetics combines therapeutic ultrasound with genetic, cellular, and molecular engineering to create remotely programmable living systems. While widely applied in neuronal modulation, this review highlights recent progress in precision medicine, focusing on immunoengineering and genome engineering, illustrating how sonogenetics is moving beyond neuromodulation to enable precise control of immune responses and targeted genetic modifications. We introduce the fundamental principles of sonogenetics and key ultrasound-responsive biological actuators, including heat-shock promoters, thermosensitive and mechanosensitive ion channels, gas vesicles, microbubbles, and acoustically responsive nanoparticles. These convert acoustic signals into biological responses and are integrated into synthetic genetic circuits to control cell behaviour with high spatial and temporal precision. We then overview immunoengineering and genome engineering, covering cellular therapies such as CAR-T and engineered bacteria, synthetic materials, and CRISPR-based genome and transcriptome editors. This context supports recent applications, including ultrasound-guided immune modulation, remote control of CAR-T cells, tumour microenvironment reprogramming, targeted genome editing, and epigenetic regulation in vivo. We also discuss the emerging role of artificial intelligence in optimizing sonogenetic designs and outline translational challenges, including actuator safety and immunogenicity, ultrasound penetration limits, targeting accuracy, and regulatory pathways for device-biologic combinations. Key priorities include closed-loop dosimetry, scalable vector delivery, and actuator optimization. In summary, sonogenetics provides a programmable, non-invasive toolkit for controlling cellular functions, opening opportunities in basic research, diagnostics, and next-generation therapeutics.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147595145","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":"Current Trends in Ultrasound Wearables: Spotlight on System Architecture.","authors":"David Weik, Richard Nauber, Erik Kaiser, Nele Kirsch, Robert Kunz, Lennart Schierling, Christoph Leitner, Luca Benini, Hsiao-Chuan Liu, Qifa Zhou, Jochen Hampe, Gerhard Fettweis, Moritz Herzog, Christian Kupsch","doi":"10.1109/RBME.2026.3664011","DOIUrl":"10.1109/RBME.2026.3664011","url":null,"abstract":"<p><p>Wearable ultrasound sensing systems are rapidly emerging for precise, continuous, and intuitive biomedical monitoring and human-in-the-loop interaction in healthcare, industry, and rehabilitation. These systems must operate under stringent constraints on size, weight, and power while delivering actionable physiological and functional information. Advances in micromachined transducers, conformable electronics, low-power signal processing, and edge artificial intelligence (AI) have enabled the first generation of wearable prototypes, yet integration of hardware and software at the system-level remains a major barrier to mass deployment. This review maps the technology readiness and architectures of wearable ultrasound systems, and examines critical design trade-offs, including edge versus cloud-based processing and pulse-echo versus coded signal approaches. We identify recurring design principles and argue that modular, scalable, and reusable platforms are key to lowering development barriers and accelerating translation from prototypes to commercial deployment across healthcare, industrial, and consumer domains.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147349217","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 Perspective on Non-Invasive Blood Pressure Monitoring: Bridging Emerging Principles, Enabling Technologies and Extended Applications.","authors":"Chentao Du, Ting Xiang, Guangyao Zhao, Mengkang Deng, Zijun Liu, Zexu Yang, Jiayuan Fang, Ningxu Yuan, Siyuan Zhou, Jian Li, Nan Ji, Jing-Song Ou, Alberto Avolio, Xinge Yu, Yuan-Ting Zhang, Tingrui Pan","doi":"10.1109/RBME.2025.3646327","DOIUrl":"10.1109/RBME.2025.3646327","url":null,"abstract":"<p><p>Cardiovascular disease (CVD), the leading global cause of death, highlights the critical need for effective blood pressure management. Non-invasive blood pressure (NIBP) monitoring, compared with invasive methods, enables home-based and long-term use, supporting early detection and continuous care. Despite significant progress, challenges remain, including accuracy issues, insufficient validation in real-world settings, limited application-specific sensor designs, and inadequate calibration standards and validation platforms. These gaps call for a systematic review to clarify the unmet needs and future research directions. This article reviews current advances in four key areas: (1) novel NIBP estimation principles designed to minimize user intervention; (2) flexible and wearable electronics that improve accuracy and comfort; (3) integration with theranostic applications and broader healthcare scenarios enabled by NIBP technologies; (4) calibration and validation strategies that enhance reliability and accuracy. With the rapid growth of home healthcare and AI-enabled wearable systems, addressing these challenges is essential to advance personalized, precise and stable cardiovascular medicine.</p>","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":16.0,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146114279","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":"IEEE Reviews in Biomedical Engineering (R-BME) Publication Information","authors":"","doi":"10.1109/RBME.2026.3652438","DOIUrl":"https://doi.org/10.1109/RBME.2026.3652438","url":null,"abstract":"","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"19 ","pages":"C3-C3"},"PeriodicalIF":12.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11368641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071189","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":"IEEE Engineering in Medicine and Biology Society","authors":"","doi":"10.1109/RBME.2026.3652442","DOIUrl":"https://doi.org/10.1109/RBME.2026.3652442","url":null,"abstract":"","PeriodicalId":39235,"journal":{"name":"IEEE Reviews in Biomedical Engineering","volume":"19 ","pages":"C2-C2"},"PeriodicalIF":12.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11368668","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071183","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}