IEEE Open Journal of Engineering in Medicine and Biology最新文献

{"title":"Reverse Correlation Characterizes More Complete Tinnitus Spectra in Patients","authors":"Nelson V. Barnett;Alec Hoyland;Divya A. Chari;Benjamin Parrell;Adam C. Lammert","doi":"10.1109/OJEMB.2024.3427318","DOIUrl":"10.1109/OJEMB.2024.3427318","url":null,"abstract":"<italic>Goal:</i>\u0000 We validate a recent reverse correlation approach to tinnitus characterization by applying it to individuals with clinically-diagnosed tinnitus. \u0000<italic>Methods:</i>\u0000 Two tinnitus patients assessed the subjective similarity of their non-tonal tinnitus percepts and random auditory stimuli. Regression of the responses onto the stimuli yielded reconstructions which were evaluated qualitatively by playing back resynthesized waveforms to the subjects and quantitatively by response prediction analysis. \u0000<italic>Results:</i>\u0000 Subject 1 preferred their resynthesis to white noise; subject 2 did not. Response prediction balanced accuracies were significantly higher than chance across subjects: subject 1: 0.5963, subject 2: 0.6922. \u0000<italic>Conclusion:</i>\u0000 Reverse correlation can provide the foundation for reconstructing accurate representations of complex, non-tonal tinnitus in clinically diagnosed subjects. Further refinements may yield highly similar waveforms to individualized tinnitus percepts.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"589-592"},"PeriodicalIF":2.7,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10602769","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complex Hemodynamic Responses to Trans-Vascular Electrical Stimulation of the Renal Nerve in Anesthetized Pigs","authors":"Filippo Agnesi;Lucia Carlucci;Gia Burjanadze;Fabio Bernini;Khatia Gabisonia;John W Osborn;Silvestro Micera;Fabio A. Recchia","doi":"10.1109/OJEMB.2024.3429294","DOIUrl":"10.1109/OJEMB.2024.3429294","url":null,"abstract":"The objective of this study was to characterize hemodynamic changes during trans-vascular stimulation of the renal nerve and their dependence on stimulation parameters. We employed a stimulation catheter inserted in the right renal artery under fluoroscopic guidance, in pigs. Systolic, diastolic and pulse blood pressure and heart rate were recorded during stimulations delivered at different intravascular sites along the renal artery or while varying stimulation parameters (amplitude, frequency, and pulse width). Blood pressure changes during stimulation displayed a pattern more complex than previously described in literature, with a series of negative and positive peaks over the first two minutes, followed by a steady state elevation during the remainder of the stimulation. Pulse pressure and heart rate only showed transient responses, then they returned to baseline values despite constant stimulation. The amplitude of the evoked hemodynamic response was roughly linearly correlated with stimulation amplitude, frequency, and pulse width.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"750-758"},"PeriodicalIF":2.7,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10601543","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Twins of Biological Systems: A Narrative Review","authors":"Ghufran A. Alsalloum;Nour M. Al Sawaftah;Kelly M. Percival;Ghaleb A. Husseini","doi":"10.1109/OJEMB.2024.3426916","DOIUrl":"10.1109/OJEMB.2024.3426916","url":null,"abstract":"The concept of Digital Twins (DTs), software models that mimic the behavior and interactions of physical or conceptual objects within their environments, has gained traction in recent years, particularly in medicine and healthcare research. DTs technology emerges as a pivotal tool in disease modeling, integrating diverse data sources to computationally model dynamic biological systems. This narrative review explores potential DT applications in medicine, from defining DTs and their history to constructing DTs, modeling biologically relevant systems, as well as discussing the benefits, risks, and challenges in their application. The influence of DTs extends beyond healthcare and can revolutionize healthcare management, drug development, clinical trials, and various biomedical research fields","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"670-677"},"PeriodicalIF":2.7,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596666","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing SPINE: A Holistic Approach to Synthetic Pulmonary Imaging Evaluation Through End-to-End Data and Model Management","authors":"Nikolaos Ntampakis;Vasileios Argyriou;Konstantinos Diamantaras;Konstantinos Goulianas;Panagiotis Sarigiannidis;Ilias Siniosoglou","doi":"10.1109/OJEMB.2024.3426910","DOIUrl":"10.1109/OJEMB.2024.3426910","url":null,"abstract":"In the evolving field of medical imaging and machine learning (ML), this paper introduces a novel framework for evaluating synthetic pulmonary imaging aiming to assess synthetic data quality and applicability. Our study concentrates on synthetic X-ray chest images, crucial for diagnosing respiratory diseases. We employ SPINE (Synthetic Pulmonary Imaging Evaluation) framework, a threefold synthetic images evaluation method including expert domain assessment, statistical data analysis and adversarial evaluation. In order to replicate and validate our methodology, we followed an End-to-End data and model management process which begins with a dataset of Normal and Pneumonia chest X-rays, generating synthetic images using Generative Adversarial Networks (GANs) and training a baseline classifier, essential in the adversarial evaluation axis, testing synthetic images against real data assessing their predictive value. The critical outcome of our approach is the post-market analysis of synthetic images. This innovative method evaluates synthetic images using clinical, statistical, and scientific criteria independently from traditional generation performance metrics. This independent evaluation provides deep insights into the clinical and research effectiveness of the synthetic data. By ensuring these images mirror real data's statistical properties and maintain clinical accuracy, our framework establishes a new standard for the ethical and reliable use of synthetic data in medical imaging and research.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"576-588"},"PeriodicalIF":2.7,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596687","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Heating and Cooling Stage With Fast Temporal Control for Biological Applications","authors":"Manon Valet;Juan M. Iglesias-Artola;Falk Elsner;Anatol W. Fritsch;Otger Campàs","doi":"10.1109/OJEMB.2024.3426912","DOIUrl":"10.1109/OJEMB.2024.3426912","url":null,"abstract":"The study of biological processes involving live microscopy techniques requires adequate temperature control to respect the physiology of the organism under study. We present here a design strategy for a microscope temperature stage based on thermoelectric elements. The design allows the user to access a range of temperatures below and above room temperature and can accommodate samples of different geometries. In addition, by cooling simultaneously the sample insert and the objective, we minimize the temperature gradients along the sample for large magnification objectives requiring immersion oil. We illustrate how this design can be used to study the physiology of the zebrafish embryo over the temperature tolerance of this species. We envision that this device could benefit the communities using model and non-model organisms with physiological temperatures different from typical mammalian cell culture incubation in biomedical research.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"573-575"},"PeriodicalIF":2.7,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596548","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fetal-BET: Brain Extraction Tool for Fetal MRI","authors":"Razieh Faghihpirayesh;Davood Karimi;Deniz Erdoğmuş;Ali Gholipour","doi":"10.1109/OJEMB.2024.3426969","DOIUrl":"10.1109/OJEMB.2024.3426969","url":null,"abstract":"<italic>Goal:</i>\u0000 In this study, we address the critical challenge of fetal brain extraction from MRI sequences. Fetal MRI has played a crucial role in prenatal neurodevelopmental studies and in advancing our knowledge of fetal brain development \u0000<italic>in-utero</i>\u0000. Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it poses significant challenges due to 1) non-standard fetal head positioning, 2) fetal movements during examination, and 3) vastly heterogeneous appearance of the developing fetal brain and the neighboring fetal and maternal anatomy across gestation, and with various sequences and scanning conditions. Development of a machine learning method to effectively address this task requires a large and rich labeled dataset that has not been previously available. Currently, there is no method for accurate fetal brain extraction on various fetal MRI sequences. \u0000<italic>Methods:</i>\u0000 In this work, we first built a large annotated dataset of approximately 72,000 2D fetal brain MRI images. Our dataset covers the three common MRI sequences including T2-weighted, diffusion-weighted, and functional MRI acquired with different scanners. These data include images of normal and pathological brains. Using this dataset, we developed and validated deep learning methods, by exploiting the power of the U-Net style architectures, the attention mechanism, feature learning across multiple MRI modalities, and data augmentation for fast, accurate, and generalizable automatic fetal brain extraction. \u0000<italic>Results:</i>\u0000 Evaluations on independent test data, including data available from other centers, show that our method achieves accurate brain extraction on heterogeneous test data acquired with different scanners, on pathological brains, and at various gestational stages. \u0000<italic>Conclusions:</i>\u0000By leveraging rich information from diverse multi-modality fetal MRI data, our proposed deep learning solution enables precise delineation of the fetal brain on various fetal MRI sequences. The robustness of our deep learning model underscores its potential utility for fetal brain imaging.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"551-562"},"PeriodicalIF":2.7,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596549","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Preadolescents’ Obesity on Inhibitory Control During Stop-Signal Task: A Functional EEG Network Study","authors":"Yuqin Li;Qian Yang;Yuxin Liu;Yutong Zheng;Jianfu Li;Chunli Chen;Baodan Chen;Dezhong Yao;Liang Yu;Peng Xu;Fali Li;Yi Liang","doi":"10.1109/OJEMB.2024.3425855","DOIUrl":"10.1109/OJEMB.2024.3425855","url":null,"abstract":"<italic>Objectives</i>\u0000. Until now, limited knowledge remains regarding the association among childhood obesity, cognitive behavior, and brain networks. Utilizing a publicly available dataset, we aimed to investigate the relationships between childhood obesity and functional networks during the stop-signal task. \u0000<italic>Results</i>\u0000. Given the huge conflict-monitoring and inhibitory control demands of the task, both enhanced network connectivity and properties were observed under the “No-go” compared to the “Go” condition for both obese and non-obese preadolescents. Obese preadolescents exhibited significantly increased frontal-parietal, frontal-occipital, and frontal-temporal linkages, as well as heightened network efficiency under both “Go” and “No-go” conditions compared to non-obese counterparts. Additionally, significant correlations were found between network connectivity and properties and preadolescents’ body mass index (BMI), with their combination predicting BMI scores successfully. \u0000<italic>Conclusions</i>\u0000. These findings support that childhood obesity is not simply a deviant habit with restricted physical health consequences, but rather associated with the atypical development of frontal-based networks involved in inhibitory control and cognitive performance.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"783-791"},"PeriodicalIF":2.7,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10595447","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Propulsion Neuroprosthesis Improves Overground Walking in Community-Dwelling Individuals After Stroke","authors":"Dabin K. Choe;Ashlyn J. Aiello;Johanna E. Spangler;Conor J. Walsh;Louis N. Awad","doi":"10.1109/OJEMB.2024.3416028","DOIUrl":"10.1109/OJEMB.2024.3416028","url":null,"abstract":"Functional electrical stimulation (FES) is a common neuromotor intervention whereby electrically evoked dorsiflexor muscle contractions assist foot clearance during walking. Plantarflexor neurostimulation has recently emerged to assist and retrain gait propulsion; however, safe and effective coordination of dorsiflexor and plantarflexor neurostimulation during overground walking has been elusive, restricting propulsion neuroprostheses to harnessed treadmill walking. We present an overground propulsion neuroprosthesis that adaptively coordinates, on a step-by-step basis, neurostimulation to the dorsiflexors and plantarflexors. In 10 individuals post-stroke, we evaluate the immediate effects of plantarflexor neurostimulation delivered with different onset timings, and retention to unassisted walking (NCT06459401). Preferred onset timing differed across individuals. Individualized tuning resulted in a significant 10% increase in paretic propulsion peak (Δ: 1.41 ± 1.52%BW) and an 8% increase in paretic plantarflexor power (Δ: 0.27 ± 0.23 W/kg), compared to unassisted walking. Post-session unassisted walking speed, paretic propulsion peak, and propulsion symmetry all significantly improved by 9% (0.14 ± 0.09 m/s), 28% (2.24 ± 3.00%BW), and 12% (4.5 ± 6.0%), respectively, compared to pre-session measurements. Here we show that an overground propulsion neuroprosthesis can improve overground walking speed and propulsion symmetry in the chronic phase of stroke recovery. Future studies should include a control group to examine the efficacy of gait training augmented by the propulsion neuroprosthesis compared to gait training alone.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"563-572"},"PeriodicalIF":2.7,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10586842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Modified Quadrature Birdcage Coil Incorporated With a Curved Feature for In Ovo MR Imaging","authors":"Chang-Hoon Choi;Maximilian Bruch;Suk-Min Hong;Sandra Krause;Carina Stegmayr;Stefan Schwan;Wieland A. Worthoff;Jörg Felder;N. Jon Shah","doi":"10.1109/OJEMB.2024.3420231","DOIUrl":"10.1109/OJEMB.2024.3420231","url":null,"abstract":"<italic>Goal:</i>\u0000 This study presents a novel MRI coil design approach explicitly tailored for chick embryo measurements, with the primary objective of improving sensitivity and coverage. \u0000<italic>Methods:</i>\u0000 The limitations posed by conventional birdcage coils were addressed by introducing a curvature feature into a standard coil. The performance of the modified coil was assessed using EM simulations and experimental evaluations, which were subsequently validated using a 7 T MRI scanner. A comparative analysis was conducted against a standard quadrature low-pass birdcage coil to evaluate key factors. \u0000<italic>Results:</i>\u0000 The proposed coil demonstrated improved SNR and uniformity, particularly in the proximity of the end-rings. These results were consistent with the findings obtained from the simulations. \u0000<italic>Conclusions:</i>\u0000 The use of our innovative birdcage coil design holds promise and offers practical potential for \u0000<italic>in ovo</i>\u0000 studies.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"534-541"},"PeriodicalIF":2.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10577130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141503317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable Neuroanatomical and Behavioral Phenotyping of Radio Frequency Radiation on Young Zebrafish","authors":"Xiaoli Wu;Yu Suen Chan;Bingjie Xiang;Wenhui Zhang;Kwai-Man Luk;Shuk Han Cheng;Yuk Fai Leung;Rosa H. M. Chan","doi":"10.1109/OJEMB.2024.3420247","DOIUrl":"10.1109/OJEMB.2024.3420247","url":null,"abstract":"<italic>Objective:</i>\u0000 In our wireless-centric world, evaluating the health effects of radio frequency electromagnetic radiation (RF-EMR) is crucial. An existing research gap pertains to the replication of real-world specific absorption rates (SAR) for RF-EMR, especially within aquatic environments. We aimed to bridge this gap using an innovative TEM cell platform to replicate realistic SAR conditions in water and assess RF-EMR's impact on neuroanatomical and behavioral changes. \u0000<italic>Results:</i>\u0000 We examined RF-EMR effects on zebrafish embryos exposed to RF-EMR during the 4-58 hours post-fertilization phase. Temporary neuroanatomical enlargements and minor behavioral shifts were observed, diminishing by day 8 post-fertilization. \u0000<italic>Conclusion:</i>\u0000 Short-term RF-EMR exposure at tested levels did not yield significant long-term effects. Nevertheless, investigating prolonged exposure remains imperative. Our study serves as a pioneering model for future investigations into the biological consequences of RF-EMR exposure, highlighting the importance of assessing its health implications in our wireless-centric world","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"89-99"},"PeriodicalIF":2.7,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10577592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141526715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}