IEEE Transactions on Biomedical Engineering最新文献

{"title":"In Vivo Characterization of Central Arterial Properties Using a Miniaturized pMUT Array Compared to a Clinical Transducer: A Feasibility Study Towards Wearable Pulse Wave Imaging.","authors":"Parth Gami, Tuhin Roy, Pengcheng Liang, Paul Kemper, Marco Travagliati, Leonardo Baldasarre, Stephen Bart, Elisa E Konofagou","doi":"10.1109/TBME.2025.3551281","DOIUrl":"10.1109/TBME.2025.3551281","url":null,"abstract":"<p><strong>Objective: </strong>Piezoelectric micromachined ultrasound transducer (pMUT) technology shows promise for wearable ultrasound applications, although with limitations in acquisition performance compared to standard transducers. To translate Pulse Wave Imaging (PWI)-an ultrasound imaging technique that evaluates local arterial mechanics-into wearable applications, this study investigated the performance of integrating a miniaturized pMUT array into the PWI pipeline.</p><p><strong>Methods: </strong>Nine (n = 9) carotid arteries were scanned with a miniaturized pMUT array and an L7-4 linear transducer. Metrics like pulse wave velocity at end-diastole (PWVED) and end-systole (PWVES), compliance (CED, CES), and carotid pulse pressure (PPC) were compared between imaging arrays.</p><p><strong>Results: </strong>Lower SNR of axial wall velocities (SNRvPWI) at end-diastole (L7-4: 47.9 ± 6.8 dB, pMUT: 43.3 ± 7.4 dB) and end-systole (L7-4: 45.4 ± 6.4 dB, pMUT: 38.1 ± 6.5 dB), and trends of higher coefficient of variation (CV) were found for PWI performed with the pMUT array compared to the L7-4. Bland-Altman analysis identified good agreement between the L7-4 and pMUT array for average PWVED (bias = -0.02 ± 0.42 m/s), PWVES (bias = -0.38 ± 1.3 m/s), CED (bias = 0.04 x 10-9 ± 0.24 x 10-9 m2/Pa), CES (bias = 0.11 x 10-9 ± 0.38 x 10-9 m2/Pa) and PPC (bias = 1.06 ± 5.08 mmHg).</p><p><strong>Conclusion: </strong>The findings revealed comparable performance between the miniaturized pMUT array and L7-4 for PWI, highlighting the versatility of the PWI technique.</p><p><strong>Significance: </strong>This feasibility study illustrates the potential for translating PWI into wearable configurations, opening new avenues for cardiovascular health monitoring.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a Low-Cost Amplifier With System Optimization in Thermoacoustic Tomography: Characterization and Imaging of Ex-Vivo and In-Vivo Samples.","authors":"Md Tarikul Islam, Mohsin Zafar, Ravi Prakash, Deepika Aggrawal, Danilo Erricolo, James Lin, Kamran Avanaki","doi":"10.1109/TBME.2025.3551260","DOIUrl":"10.1109/TBME.2025.3551260","url":null,"abstract":"<p><p>Microwave-induced thermoacoustic tomography (TAT) is a hybrid imaging technique that combines microwave excitation with ultrasound detection to create detailed images of biological tissue. Most TAT systems require a costly amplification system (or a sophisticated high-power microwave source), which limits the wide adoption of this imaging modality. We have developed a rotating single-element thermoacoustic tomography (RTAT) system using a low-cost amplifier that has been optimized in terms of microwave signal pulse width and antenna placement. The optimized system, enhanced with signal averaging, advanced signal processing, and a deep learning computational core, successfully produced adequate-quality images. The system has been characterized in terms of spatial resolution, imaging depth, acquisition speed, and multispectral capabilities utilizing tissue-like phantoms, ex-vivo specimens and in-vivo imaging. We believe our low-cost, portable system expands accessibility for the research community, empowering more groups to explore thermoacoustic imaging. It supports the development of advanced signal processing algorithms to optimize both low-power and even high-power TAT systems, accelerating the clinical adoption of this promising imaging modality.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-Autonomous Laparoscopic Robot Docking with Learned Hand-Eye Information Fusion.","authors":"Huanyu Tian, Martin Huber, Christopher E Mower, Zhe Han, Changsheng Li, Xingguang Duan, Christos Bergeles","doi":"10.1109/TBME.2025.3550974","DOIUrl":"10.1109/TBME.2025.3550974","url":null,"abstract":"<p><p>In this study, we introduce a novel shared-control system for key-hole docking operations, combining a commercial camera with occlusion-robust pose estimation and a hand-eye information fusion technique. This system is used to enhance docking precision and force-compliance safety. To train a hand-eye information fusion network model, we generated a self-supervised dataset using this docking system. After training, our pose estimation method showed improved accuracy compared to traditional methods, including observation-only approaches, hand-eye calibration, and conventional state estimation filters. In real-world phantom experiments, our approach demonstrated its effectiveness with reduced position dispersion (1.230.81 mm vs. 2.47 1.22 mm) and force dispersion (0.780.57 N vs. 1.150.97 N) compared to the control group. These advancements in semi-autonomy co-manipulation scenarios enhance interaction and stability. The study presents an anti-interference, steady, and precise solution with potential applications extending beyond laparoscopic surgery to other minimally invasive procedures.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time of Flight Transmission Mode Ultrasound Computed Tomography with Expected Gradient and Boundary Optimization.","authors":"Roberto C Ceccato, Andre V Pigatto, Richard C Aster, Chi-Nan Pai, Jennifer L Mueller, Sergio S Furuie","doi":"10.1109/TBME.2025.3550823","DOIUrl":"https://doi.org/10.1109/TBME.2025.3550823","url":null,"abstract":"<p><strong>Objective: </strong>Quantitative time of flight in transmission mode ultrasound computed tomography (TFTM USCT) is a promising, cost-effective, and non-invasive modality, particularly suited for functional imaging. However, TFTM USCT encounters resolution challenges due to path information concentration in specific medium regions and uncertainty in transducer positioning. This study proposes a method to enhance resolution and robustness, focusing on low-frequency TFTM USCT for pulmonary imaging.</p><p><strong>Methods: </strong>The proposed technique improves the orientation of steepest descent algorithm steps, preventing resolution degradation due to path information concentration, while allowing for a posteriori sensor positioning retrieval. Total variation regularization is employed to stabilize the inverse problem, and a modified Barzilai-Borwein method determined the step size in the steepest descent algorithm. The proposed method was validated through simulations of data on healthy and abnormal cross-sections of a human chest using MATLAB's k-Wave toolbox. Additionally, experimental data were collected using a Verasonics Vantage 64 low-frequency system and a ballistic gel torso-mimicking phantom to assess robustness under a more realistic environment, closer to that of a clinical situation.</p><p><strong>Results: </strong>The results showed that the proposed method significantly improved image quality and successfully retrieved sensor locations from imprecise positioning.</p><p><strong>Significance: </strong>This study is the first to address transducer location uncertainty on a transducer belt in TFTM USCT and to apply an estimated gradient approach. Additionally, low-frequency USCT for lung imaging is quite novel, and this work addresses practical questions that will be important for translational development.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast and Stable Neonatal Brain MR Imaging Using Integrated Learned Subspace Model and Deep Learning.","authors":"Ziwen Ke, Yue Guan, Tianyao Wang, Huixiang Zhuang, Zijun Cheng, Yunpeng Zhang, Jing-Ya Ren, Su-Zhen Dong, Yao Li","doi":"10.1109/TBME.2025.3541643","DOIUrl":"https://doi.org/10.1109/TBME.2025.3541643","url":null,"abstract":"<p><strong>Objective: </strong>To enable fast and stable neonatal brain MR imaging by integrating learned neonate-specific subspace model and model-driven deep learning.</p><p><strong>Methods: </strong>Fast data acquisition is critical for neonatal brain MRI, and deep learning has emerged as an effective tool to accelerate existing fast MRI methods by leveraging prior image information. However, deep learning often requires large amounts of training data to ensure stable image reconstruction, which is not currently available for neonatal MRI applications. In this work, we addressed this problem by utilizing a subspace model-assisted deep learning approach. Specifically, we used a subspace model to capture the spatial features of neonatal brain images. The learned neonate-specific subspace was then integrated with a deep network to reconstruct high-quality neonatal brain images from very sparse k-space data.</p><p><strong>Results: </strong>The effectiveness and robustness of the proposed method were validated using both the dHCP dataset and testing data from four independent medical centers, yielding very encouraging results. The stability of the proposed method has been confirmed with different perturbations, all showing remarkably stable reconstruction performance. The flexibility of the learned subspace was also shown when combined with other deep neural networks, yielding improved image reconstruction performance.</p><p><strong>Conclusion: </strong>Fast and stable neonatal brain MR imaging can be achieved using subspace-assisted deep learning with sparse sampling. With further development, the proposed method may improve the practical utility of MRI in neonatal imaging applications.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143614778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel NICU Sleep State Stratification: Multiperspective Features, Adaptive Feature Selection and Ensemble Model.","authors":"Muhammad Irfan, Abdulhamit Subasi, Zhenning Tang, Laishuan Wang, Yan Xu, Chen Chen, Tomi Westurlund, Wei Chen","doi":"10.1109/TBME.2025.3549584","DOIUrl":"https://doi.org/10.1109/TBME.2025.3549584","url":null,"abstract":"<p><p>The examination of sleep patterns in newborns, particularly premature infants, is crucial for understanding neonatal development. This study presents an automated multi-sleep state classification approach for infants in neonatal intensive care units (NICU) using multiperspective feature extraction methodologies and machine learning to assess their neurological and physical development. The datasets for this study were collected from Children's Hospital Fudan University, Shanghai and consist of electroencephalography (EEG) recordings from two datasets, one comprising 64 neonates and the other 19 neonates. The proposed study involves six major phases: data collection, data annotation, preprocessing, multi-perspective feature extraction, adaptive feature selection, and classification. During the preprocessing phase, noise reduction is achieved using the multi-scale principal component analysis (MSPCA) method. From each epoch of eight EEG channels, a diverse ensemble of 1,976 features is extracted. This extraction employs a combination of stationary wavelet transform (SWT), flexible analytical wavelet transform (FAWT), spectral features based on α, β, θ, and δ brain waves, and temporal features refined through adaptive feature algorithm. In terms of performance, the proposed approach demonstrates significant improvements over existing studies. Using a single EEG channel, the model achieves accuracy of 81.45% and a Kappa score of 71.75%. With four channels, these metrics increase to 83.71% accuracy and a 74.04% Kappa score. Furthermore, utilizing all eight channels, the mean accuracy reaches to 85.62%, and the Kappa score rises to 76.30%. To evaluate the model's effectiveness, a leave-one-subject-out cross-validation method is employed. This thorough analysis validates the reliability of the classification approach. This makes it a promising method for monitoring and assessing sleep patterns in neonates.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of Magnetic Actuated Capsule Robot for Liquid Sampling.","authors":"Shuo Zhang, Shaohui Song, Xinkai Yu, Shuang Song, Lihai Zhang","doi":"10.1109/TBME.2025.3550179","DOIUrl":"10.1109/TBME.2025.3550179","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to introduce a biopsy capsule robot based on the negative pressure suction principle to achieve liquid sampling in the digestive tract.</p><p><strong>Methods: </strong>The proposed capsule robot is designed with a magnetic spring configuration. By controlling the direction of an external magnetic field, the suction port can be aligned with the target sampling area. The sampling operation can then be achieved by increasing the external field to start the magnetic spring and a negative pressure can be generated to achieve the liquid sampling. Moreover, a locking mechanism is designed to prevent the magnetic spring from retracting, ensuring that the collected liquid is not squeezed out.</p><p><strong>Results: </strong>The capsule robot prototype has dimensions of 16.3mm × 24.4mm. Both phantom and in-vitro experiments have been carried out. Results showed that it can sample liquids with viscosities ranging from 0.7mPa s to 200mPa s and absorb up to 0.24ml liquid. Additionally, the sealing of the capsule also meets clinical requirements.</p><p><strong>Conclusion: </strong>The experimental results indicate that the designed capsule robot can satisfy the clinical requirements for liquid sampling within the digestive tract.</p><p><strong>Significance: </strong>This study has designed and developed a micro capsule robot in the digestive tract, which can achieve safe and efficient liquid sampling operations. The proposed robot can benefit the clinical diagnosis of digestive diseases, especially in the small intestine.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-Robot Shared Control for Osteotomy Procedure.","authors":"Elisa Iovene, Lorenzo Casadio, Junling Fu, Francesco Costa, Giancarlo Ferrigno, Elena De Momi","doi":"10.1109/TBME.2025.3549867","DOIUrl":"10.1109/TBME.2025.3549867","url":null,"abstract":"<p><p>Spinal intervention can benefit from advancements in robotic systems, particularly in the field of Human-Robot Interaction (HRI). Despite the promising potential of these technologies, their integration into spine surgeries remains relatively limited, comprising mainly only selected procedures. Meanwhile, complex and time-consuming procedures, such as osteotomy, continue to be performed manually, significantly impacting surgeon workload and stress. This paper introduces a robotic system to assist surgeons during the drilling of the vertebral body. The system aims to reduce surgeon workload, enhance surgical precision, and ultimately contribute to improved patient outcomes in spinal surgeries. The system integrates a pre-planning tool for establishing the desired angle of correction, a virtual fixture-based impedance control algorithm enabling the robot to assist the user in following pre-defined cutting trajectories while safeguarding surrounding structures, and a navigation tool for enhanced guidance during the procedure. The proposed system is composed by a 7 Degree-of-Freedom robotic manipulator equipped with a drilling system attached to its end-effector. System accuracy was validated on 5 vertebral phantoms, achieving a tracking error of mm and mm, a margin error of mm and mm, and an angular alignment error of and for the sagittal and coronal planes, respectively.Additionally, the system's performance was evaluated with real porcine bone, with results demonstrating similar precision and robustness under realistic mechanical properties. A user Study was conducted to evaluate whether the proposed system effectively enhanced user performance and alleviated the users' workload compared to a manual control strategy. The results demonstrated reduced deviation from the desired path (Trajectory Error) and fewer instances of the system exceeding predetermined restricted areas (Boundary Violation) when using the proposed system. Additionally, participants rated the proposed system as less mentally and physically demanding in comparison to the traditional control strategy.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robot-mediated asymmetric connection between humans can improve performance without increasing effort.","authors":"Alessia Noccaro, Silvia Buscaglione, Jonathan Eden, Xiaoxiao Cheng, Nicola Di Stefano, Gio-Vanni Di Pino, Etienne Burdet, Domenico Formica","doi":"10.1109/TBME.2025.3548884","DOIUrl":"10.1109/TBME.2025.3548884","url":null,"abstract":"<p><p>Whether working together to move a table or supporting a child learning to ride a bike, physically connected individuals exchange haptic information to improve motor performance. However, this improvement occurs at the cost of additional effort for the more skilled partner.</p><p><strong>Objective: </strong>Here, we hypothesize that an asymmetric connection, consisting of a stiffer link to the less skilled partner and a more compliant link to the more skilled partner, could improve task performance without additional effort in collaborative tasks.</p><p><strong>Methods: </strong>Through computational modelling, we first tested this hypothesis on simulated human dyads tracking a common target. Then we experimentally validated the approach on a three degree-offreedom tracking task using two commercial robots as individual interfaces.</p><p><strong>Results: </strong>The simulation and experimental results confirm that using an asymmetric connection stiffness can improve joint performance without requiring additional effort from either partner compared to their solo effort.</p><p><strong>Conclusion: </strong>This suggests that the training of motor skills with a proficient partner may be enhanced through the use of robot-mediated asymmetric haptic connections.</p><p><strong>Significance: </strong>This approach may benefit joint tasks between individuals with clearly different motor abilities, such as a violin teacher demonstrating bowing techniques or a physical therapist assisting a patient during rehabilitation.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Resolution Whole-Brain Diffusion Tensor Imaging Exploiting Rapid Single-Slab 3D EPI Strategy.","authors":"Hyunkyung Maeng, HyungGoo R Kim, Roh Eul Yoo, Jaeseok Park","doi":"10.1109/TBME.2025.3541686","DOIUrl":"10.1109/TBME.2025.3541686","url":null,"abstract":"<p><strong>Objective: </strong>The purpose of this work is to investigate the feasibility of high-resolution whole-brain diffusion tensor imaging (DTI) using a rapid single-slab 3D pseudo-random EPI encoding strategy with physical constraints.</p><p><strong>Methods: </strong>A spin-echo-based diffusion-weighted imaging was modified to incorporate both single-slab 3D segmented EPI for high-resolution diffusion imaging and unsegmented EPI with short readouts for segment-specific motion-induced phase navigation. A physically constrained, segment-wise grouped phase encoding strategy is introduced, yielding a rapid, pseudo-random traversal of $k$ -space with smooth signal transition in local neighborhood even in the presence of magnetic field inhomogeneities. Numerical simulations and in vivo studies were performed to validate the feasibility of the proposed method for high-resolution whole-brain DTI.</p><p><strong>Results: </strong>The proposed method exhibits a robust point spread function (PSF) even in the presence of magnetic field inhomogeneities and produces a clear depiction of DTI parameter maps from highly incomplete measurements (reduction factor = 5.5). Furthermore, the proposed method outperforms the conventional 2D single-shot EPI and the conventional simultaneous multislice EPI due to its robust PSF, high encoding efficiency, and high signal gain.</p><p><strong>Conclusion: </strong>We successfully demonstrated the rapid single-slab 3D pseudo-random EPI encoding strategy with physical constraints, which makes it possible to achieve high-resolution (1.0mm$^{3}$) single-slab 3D DTI roughly in 14 minutes without apparent artifacts and noise.</p><p><strong>Significance: </strong>This is the first work that prospectively demonstrates a rapid, physically constrained pseudo-random EPI strategy for high-resolution single-slab whole-brain DTI.</p>","PeriodicalId":13245,"journal":{"name":"IEEE Transactions on Biomedical Engineering","volume":"PP ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}