IEEE Transactions on Neural Systems and Rehabilitation Engineering最新文献

{"title":"Effects of 3D Stimuli With Frequency Ranges, Patterns, and Shapes on SSVEP-BCI Performance in Virtual Reality","authors":"Zihao Wei;Yanfei Lin;Jiayi Chen;Shuo Pan;Xiaorong Gao","doi":"10.1109/TNSRE.2025.3544308","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3544308","url":null,"abstract":"Traditional steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) systems offer stability and simplicity in evoking brain responses, but their practical utility is limited by immovable screens for visual stimuli. Virtual Reality (VR) technology provides a more natural and immersive environment to evoke SSVEP signals. However, the design methods for visual stimuli in VR environments remain to be explored, especially under the stereoscopic vision conditions. This study investigated the effects of 3D stimuli with frequency ranges, patterns, and shapes on the performance and user experiences of VR-SSVEP. There were four patterns including three-dimensional (3D) flicker, two-dimensional (2D) flicker, 3D checkerboard, and 3D quick response (QR) code with four shapes comprising cube, sphere, cylinder, and cone at low (9-15Hz), medium (18-24Hz), and high frequencies (30-36Hz). Both offline and online experiments were conducted to analyze the effects of different parameter combinations on SSVEP-BCI performance, and a questionnaire was exploited to evaluate user experiences. Compared to high frequency range, the low and medium frequency ranges had better performance and lower user experiences. 3D checkerboard and 3D QR code patterns showed significantly better user experiences than 3D and 2D flickers for all frequency ranges. With a high level of classification performance, 3D checkerboard and 3D QR code patterns in medium frequency range could synthetically enhance the system performance and user experiences. These results could provide significant value for SSVEP-BCI application in VR environments.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"890-899"},"PeriodicalIF":4.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10898078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous and Proportional Control Based on an Enhanced Musculoskeletal Model","authors":"Lizhi Pan;Diyi Liu;Ruyi Wang;Jinhua Li","doi":"10.1109/TNSRE.2025.3543912","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543912","url":null,"abstract":"Recently, the musculoskeletal model (MM) has been widely studied for decoding movement intent from electromyography (EMG) signals. However, the decoding performance of the MM is impaired for the coordinated movements of multiple degrees of freedom (DoFs) due to the crosstalk between signals of multiple muscles. To address this problem, this study proposed an enhanced MM for 3-DoF motion prediction by taking the “divide and conquer” (DC) strategy and integrating the non-negative matrix factorization (NMF) algorithm, which is named as DC-NMF-MM. The control signals of wrist flexion/extension and MCP flexion/extension were obtained from four independent muscles, and the control signals of wrist pronation/supination were obtained from eight-channel surface EMG signals. Eight non-disabled subjects were recruited for offline and online experiment. For offline experiment, another two MMs were established and taken as the control groups for validation of the proposed DC-NMF-MM, including the MM totally taking the NMF algorithm (T-NMF-MM) and that partly taking the NMF algorithm (P-NMF-MM) for predicting the wrist pronation/supination only. The Pearson’s correlation coefficient and the normalized root mean square error were employed to compare the prediction performance of three models. The results showed that the proposed method performs better than the other two models. Moreover, artificial neural network and linear regression model were established to compare with the proposed model and the results showed that DC-NMF-MM is more accurate in predicting joint Angle. For online experiment, a general 3-DOF musculoskeletal model based on DC-NMF-MM was established and the completion time, the number of overshoots, and the path efficiency were taken as evaluation indexes. The results further demonstrated the feasibility of the proposed method to achieve 3-DoF motion control. The proposed enhanced MM provides a prerequisite for the realization of clinical hand myoelectric control.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"847-857"},"PeriodicalIF":4.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10896736","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of Transcranial Magnetic Stimulation in Post-Stroke Motor Recovery: Impact of Impairment Severity","authors":"Guiyuan Cai;Cailing Zhang;Jiayue Xu;Junbo Jiang;Gengbin Chen;Jialin Chen;Quan Liu;Guangqing Xu;Yue Lan","doi":"10.1109/TNSRE.2025.3543859","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543859","url":null,"abstract":"Stroke is a leading cause of impairment, with 70% of survivors experiencing upper limb motor deficits. While transcranial magnetic stimulation (TMS) is widely used in rehabilitation, the impact of impairment severity on treatment outcomes remains unclear. This study evaluated TMS effectiveness in post-stroke motor impairment and explored its neural mechanisms. Fifty-five stroke patients were divided into TMS (n =27) and control (n =28) groups. The TMS group received two weeks of intermittent theta-burst stimulation (iTBS), while controls received sham stimulation. Patients were stratified into mild/moderate (Fugl-Meyer Assessment [FMA] <inline-formula> <tex-math>$ge 30$ </tex-math></inline-formula>) and severe (FMA <30) impairment subgroups. Motor function and electroencephalography (EEG) metrics were assessed before and after treatment. Overall FMA improvement showed no difference between groups, but the TMS-mild/moderate impairment group demonstrated significantly greater improvement compared to others. This group exhibited higher global and local alpha band power and global alpha efficiency. FMA improvement positively correlated with local alpha power changes. TMS of ipsilesional M1 improves motor function in mild/moderate impairments but shows limited efficacy in severe cases. EEG suggests TMS promotes recovery by modulating alpha activity and enhancing network efficiency. These findings support stratified treatment approaches and highlight the need for alternative interventions in severe impairment.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"881-889"},"PeriodicalIF":4.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10896702","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"mGNN-bw: Multi-Scale Graph Neural Network Based on Biased Random Walk Path Aggregation for ASD Diagnosis","authors":"Wenqiu Pan;Guang Ling;Feng Liu","doi":"10.1109/TNSRE.2025.3543177","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543177","url":null,"abstract":"In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) and typically developing (TD) individuals based on neuroimaging data, such as functional magnetic resonance imaging (fMRI), has garnered significant attention. Studies have shown that long-range functional connectivity patterns in ASD patients exhibit significant abnormalities, and individual brain networks display considerable heterogeneity. However, current graph neural networks (GNNs) used in ASD research have failed to adequately capture long-range connectivity and have overlooked individual differences. To address these limitations, this study proposes a novel multi-scale graph neural network based on biased random walks (mGNN-bw). The model introduces a co-optimization strategy between sub-models and the main model, leveraging node pooling scores from sub-models to guide biased random walks, effectively capturing long-range connectivity. By constructing high-order brain networks through path encoding and aggregation, and integrating them with low-order brain networks based on Pearson correlation, the model achieves a robust multi-scale feature representation. Experimental results on the publicly available ABIDE I dataset demonstrate the superior performance of our approach, achieving accuracy rates of 74.8% and 73.2% using CC200 and AAL atlases, respectively, outperforming existing methods. Additionally, the model identifies key ASD-associated brain regions, including the frontal lobe, insula, cingulate, and calcarine, supported by existing research. The proposed method significantly contributes to the clinical diagnosis of ASD.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"900-910"},"PeriodicalIF":4.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10896757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in Kinematic and Spatiotemporal Gait Parameters With a Biarticular Lower Limb Exosuit for Adolescents With Crouch Gait During Level Walking and Stair Climbing","authors":"Chiara Basla;Philippe Dürrenberger;Peter Wolf;Robert Riener;Hubertus J. A. van Hedel","doi":"10.1109/TNSRE.2025.3543606","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543606","url":null,"abstract":"Crouch gait is a prevalent walking abnormality among children with cerebral palsy, characterized by excessive knee and hip flexion during walking. This condition often limits children’s engagement in physical activities and daily life. Current exoskeleton solutions targeting the knee joint in this population are either tethered or bulky, hindering practical integration into daily routines. In this cross-sectional study, we evaluated the impact of a biarticular cable-driven exosuit, originally designed for adults, on the gait pattern of adolescents with crouch gait. Participants completed level walking and stair climbing trials under three conditions: without the exosuit (noMyo), with the exosuit inactive (MyoOff), and with the exosuit active (MyoOn). Kinematic and spatiotemporal gait metrics were analyzed using 3D motion capture. Five male adolescents with mild to moderate crouch participated. Results revealed significant improvements in mean knee and hip extension during the assisted phase (5 to 50% of the gait) with MyoOn compared to noMyo, increasing by 6 (range: 0 - 12) and 12 (range: 4 - 24) degrees, respectively, during level walking. During stair climbing, knee and hip extension improved in the stance phase of the trailing leg in the MyoOn condition compared to MyoOff. Only the hip angles improved in the MyoOn condition compared to noMyo. Spatiotemporal metrics showed no improvement. Stride length shortened significantly in both MyoOn and MyoOff. These findings demonstrate the exosuit’s potential to address extension deficits in crouch gait, although its weight may limit improvements in spatiotemporal gait characteristics. Developing a lighter, child-specific version could expand accessibility to a broader pediatric population.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"966-974"},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10892316","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons","authors":"Gabriel da Silva Lima;Vinícius Rosa Cota;Wallace Moreira Bessa","doi":"10.1109/TNSRE.2025.3543756","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543756","url":null,"abstract":"Closed-loop electricalstimulation of brain structures is one of the most promising techniques to suppress epileptic seizures in drug-resistant refractory patients who are also ineligible to ablative neurosurgery. In this work, an intelligent controller is presented to block the aberrant activity of a network of Izhikevich neurons of three different types, used here to model the electrical activity of the basolateral amygdala during ictogenesis, i.e. its transition from asynchronous to hypersynchronous state. A Lyapunov-based nonlinear scheme is used as the main framework for the proposed controller. To avoid the issue of accessing each neuron individually, local field potentials are used to gain insight into the overall state of the Izhikevich network. Artificial neural networks are integrated into the control scheme to manage unknown dynamics and disturbances caused by brain electrical activity that are not accounted for in the model. Four different cases of ictogenesis induction were tested. The results show the efficacy of the proposed control strategy to suppress epileptic seizures and suggest its capability to address both patient-specific and patient-to-patient variability.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"868-880"},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10892294","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Benefit of FMG and EMG Sensor Fusion for Gesture Recognition Using Cross-Subject Validation","authors":"Maurice Rohr;Jad Haidamous;Niklas Schäfer;Stephan Schaumann;Bastian Latsch;Mario Kupnik;Christoph Hoog Antink","doi":"10.1109/TNSRE.2025.3543649","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543649","url":null,"abstract":"Hand gestures are a natural form of human communication, making gesture recognition a sensible approach for intuitive human-computer interaction. Wearable sensors on the forearm can be used to detect the muscle contractions that generate these gestures, but classification approaches relying on a single measured modality lack accuracy and robustness. In this work, we analyze sensor fusion of force myography (FMG) and electromyography (EMG) for gesture recognition. We employ piezoelectric FMG sensors based on ferroelectrets and a commercial EMG system in a user study with 13 participants to measure 66 distinct hand movements with 10ms labelling precision. Three classification tasks, namely flexion and extension, single finger, and all finger movement classification, are performed using common handcrafted features as input to machine learning classifiers. Subsequently, the evaluation covers the effectiveness of the sensor fusion using correlation analysis, classification performance based on leave-one-subject-out-cross-validation and 5x2cv-t-tests, and its effects of involuntary movements on classification. We find that sensor fusion leads to significant improvement (42% higher average recognition accuracy) on all three tasks and that both sensor modalities contain complementary information. Furthermore, we confirm this finding using reduced FMG and EMG sensor sets. This study reinforces the results of prior research about the effectiveness of sensor fusion by performing meticulous statistical analyses, thereby paving the way for multi-sensor gesture recognition in assistance systems.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"935-944"},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10892285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Throw and Catch: Analyzing the Synchronized Movements of Eyes and Joints in Children","authors":"Ziyu He;Hong Fu;Ruimin Li;Zhen Liang;Chetwyn C. H. Chan;Yanwen Xu;Yang Zheng","doi":"10.1109/TNSRE.2025.3543730","DOIUrl":"10.1109/TNSRE.2025.3543730","url":null,"abstract":"Throw and catch are fundamental motor skills that are closely related to eye-hand coordination, reaction speed, and spatial awareness in children. Current research on throw and catch mainly focuses on the impact of attentional focus, anticipatory knowledge, and training on visuomotor control. Little work has been done on the synchronized movements of eyes and joints during the throw and catch. To understand how these synchronized movements contribute to the success rate of throwing and catching, we proposed a video-based framework named Synchronized Eye and Joint Analysis (SEJA). This framework locates, extracts, and analyzes the essential eye and joint movements from untrimmed first-person and third-person view videos. Using the proposed framework, throw and catch events in long untrimmed videos were successfully identified, and whether each catch was successful was accurately assessed. Additionally, detailed metrics related to predictive gaze behaviors and predictive hand movements for each catch event were obtained. On a dataset consisting of videos from 56 children aged 7 to 10, the proposed framework delivered an average precision (AP) ranging from 0.5 to 0.95 at 0.881 for task localization and achieved an accuracy of 0.985 in predicting whether a catch was successful. Our research indicated that children with higher catch success rates showed shorter delays in predicting the ball’s trajectory, smaller amplitudes of body movement, and more pronounced predictive saccades (rapid eye movements to anticipate the ball’s position). These findings are crucial for comprehending and improving the development of motor skills in children.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"994-1003"},"PeriodicalIF":4.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10892245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143556759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Visual Clutter in VR on Visuomotor Integration in Autistic Individuals","authors":"Minxin Cheng;Leanne Chukoskie","doi":"10.1109/TNSRE.2025.3543131","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3543131","url":null,"abstract":"Autistic individuals often exhibit superior local visual sensitivity but may struggle with global visual processing, affecting their visuomotor integration (VMI). Goal-directed overhand throwing is common in both the physical environment (PE) and virtual reality (VR) games, demanding spatial and temporal accuracy to perceive position and motion, and precise VMI. Understanding VMI in autistic individuals and exploring supportive designs in VR are crucial for rehabilitation and improving accessibility. We assessed static visuospatial accuracy and VMI with autistic (<inline-formula> <tex-math>${n} = 16$ </tex-math></inline-formula>) and non-autistic (<inline-formula> <tex-math>${n} = 16$ </tex-math></inline-formula>) adults using spatial estimation and overhand throwing tasks with eye and hand tracking, comparing VR to PE. In VR, all participants exhibited reduced visual accuracy, increased visual scanning, and shortened quiet eye duration and eye following duration after the ball release, which led to decreased throwing performance. However, simplifying visual information in VR throwing improved these measures, and resulted in autistic individuals outperforming non-autistic peers.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"829-840"},"PeriodicalIF":4.8,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Multiscore Functional Atlas Creation for Image-Guided Deep Brain Stimulation","authors":"Xiongbiao Luo;Zhuo Zeng;Song Zheng;Jianhui Chen;Pierre Jannin","doi":"10.1109/TNSRE.2025.3542395","DOIUrl":"https://doi.org/10.1109/TNSRE.2025.3542395","url":null,"abstract":"Deep brain stimulation is increasingly performed for patients who suffer from drug-resistant movement disorders. It still remains challenging to determine the optimal electrode contact location to obtain the optimal surgical outcome and simultaneously minimize adverse effects. This paper proposes to construct a new statistical functional atlas to guide electrode contact targeting during deep brain stimulation. The construction of the atlas consists of four main steps: 1) multimodal image segmentation and registration, 2) activation volume modeling, 3) computing and combining multiple functional scores, and 4) generation of multiscore functional atlas. Based on these steps, the statistical functional atlas is created by integrating anatomical information analysis with multiple clinical scores that postoperatively characterize stimulation efficacy (e.g., motor symptom) and adverse effect. We evaluated the created atlas on 40 subthalamic nucleus stimulated parkinsonian patient datasets. The experimental results show that the reproducibility of the created statistical functional atlas was more than 75% in the cross validation. In addition, the motor, neuropsychological, and health scores can be reproduced up to 77%, 82%, and 78%. Compared to the actually implanted electrode position, the atlas predicted and the manually planned electrode position errors were 2.89 mm and 2.38 mm, respectively. The constructed multiscore atlas provides an automatic and accurate electrode targeting strategy that potentially outperforms manually planned approaches.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"818-828"},"PeriodicalIF":4.8,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}