Neural stem cells (NSCs) play a crucial role in neural regeneration following spinal cord injury (SCI) owing to their self-proliferative and multidirectional differentiation capabilities. This study examined the biological properties of adult spinal cord-derived NSCs (sp-NSCs) and the role of Notch receptors in regulating their activation. NSCs were isolated from the spinal cords of 8-week-old C57/BL6 mice, and their biological properties, including the gene expression profile of Notch receptors, were subsequently analyzed using single-cell RNA sequencing (scRNA-Seq) and bioinformatics. The NSCs were subsequently infected with lentiviral vectors encoding Notch1 shRNA, Notch2 shRNA, and a combination of Notch1 and Notch2 shRNA sequences, and evaluated using Sphere assays and EdU staining to determine their activation effects. The expression levels of downstream genes, NICD and Rbpj, in the Notch signaling pathway, as well as the related target genes, Hes1 and Hey1, were subsequently quantified using Western blot analysis. Intact adult mouse sp-NSCs predominantly existed in a quiescent state, with their population increasing significantly with age. Notch receptors served as critical regulators of adult sp-NSC activation. Notably, Notch1 expression was significantly elevated compared to Notch2 and Notch3, demonstrating its predominant role in sustaining NSC activation. In contrast, Notch2 and Notch3 were primarily responsible for maintaining NSCs in a quiescent state. Overall, both Notch1 and Notch2 signals are involved in different regulatory roles that facilitate the activation and fate determination of NSCs via NICD-Rbpj.

Background:Repetitive transcranial magnetic stimulation (rTMS) of the left primary motor cortex (M1) shows promise for treating neuropathic pain (NP) after spinal cord injury (SCI), but its efficacy remains limited. This study investigated whether combining rTMS on M1 with premotor cortex (PMC) could improve pain relief in SCI patients with NP. Materials and Methods:Thirty-nine subjects with NP post-SCI were randomly assigned to three groups: M1 + PMC (10-Hz rTMS on left M1 and PMC), M1 (10-Hz rTMS on left M1), and sham. They underwent daily rTMS sessions for 4 weeks with 2 days off each week. Pain was assessed using the numerical rating scale (NRS) and the Short-Form McGill Pain Questionnaire-2 (SF-MPQ2). Functional near-infrared spectroscopy (fNIRS) measured activations in bilateral M1, PMC, and primary somatosensory cortex (S1) during a handgrip task. Results:Pain intensity gradually declined in the M1 + PMC, M1, and sham groups over time. Both the M1 and M1 + PMC groups experienced greater reductions in NRS scores compared to the sham group (p < 0.05), with the M1 + PMC group showing the most significant reduction (p < 0.05). The M1 + PMC group showed pain relief from Weeks 1 to 6, along with notable inhibition of left M1 and the left PMC activation. The decrease in the oxyhemoglobin (HbO) concentration in the left PMC is significantly positively correlated with the improvement of the NRS score (r = 0.607, p = 0.028) and SF-MPQ2 (r = 0.595, p = 0.032), respectively. Conclusions:High-frequency rTMS targeting both left M1 and the left PMC is more effective for NP after SCI than targeting left M1 alone, indicating a synergistic benefit. Trial Registration: Chinese Clinical Trials Registry: ChiCTR2000029024.

Spatial transcriptomics (ST) profiles gene expression with spatial context, but most platforms capture multicellular spots containing mixed cell types, making accurate deconvolution essential. Existing reference-based methods using scRNA-seq often ignore spatial dependency and gene-level contribution, yielding fragmented maps and limited insight into domain-specific programs. Here, we propose a gene-aware heterogeneous graph attention network called STGnet for spatial transcriptomics deconvolution and functional annotation. Leveraging a hybrid pseudo-spot generation strategy that captures realistic spatially enriched cell-type patterns, STGnet accurately integrates spatial adjacency, transcriptional similarity, and gene-spot associations within a unified heterogeneous network. Attention weights highlight domain-specific genes for interpretable domain annotation. Importantly, STGnet can characterize spatially ordered functional programs across domains that may be associated with disease progression. These insights may facilitate the discovery of spatial disease mechanisms and improve understanding of pathological tissue organization. Experiments on simulated and real datasets show that STGnet achieves the best overall performance compared with state-of-the-art methods.

INTRODUCTION:The rising incidence of chronic nonspecific low back pain (CNLBP) is placing an ever-growing burden on healthcare systems. This study aims to investigate the multidimensional impairment characteristics of core muscle structure and function, neuromuscular control, and psychological status in patients with CNLBP and to analyze the correlations among key indicators, thereby providing a basis for individualized clinical assessment and targeted intervention. METHODS:A total of 56 CNLBP patients from the outpatient department of Rehabilitation Medicine at Xijing Hospital of Fourth Military Medical University were enrolled between June 2024 and January 2025. Additionally, 30 healthy volunteers were recruited as controls. Demographic data were collected. Assessments were conducted across four dimensions: pain and function, muscle morphology, neuromuscular control, and sleep and psychological status. Differences in indicators between groups were compared, and correlation analyses among indicators were performed within the CNLBP group. RESULTS:In the CNLBP group, the pressure pain threshold (p = 0.012), maximum voluntary extension of back extensors (p < 0.001), cross-sectional area (CSA) of the multifidus muscle (p < 0.001), thickness change rate of the multifidus muscle (p < 0.001), and flexion-relaxation ratio (FRR) (p < 0.001) were significantly lower than those in the healthy control group. In contrast, the finger-to-floor distance (p = 0.040), Pittsburgh Sleep Quality Index score (p = 0.004), Generalized Anxiety Disorder-7 score (p = 0.005), and Patient Health Questionnaire-9 score (p = 0.021) were significantly higher. Correlation analysis within the CNLBP group revealed that the FRR was negatively correlated with the NRS score (r = -0.283, p = 0.038) and the Oswestry Disability Index (ODI) score (r = -0.345, p = 0.011). The thickness change rate of the multifidus muscle was negatively correlated with the ODI score (r = -0.285, p = 0.037), but its correlation with the Numeric Rating Scale (NRS) score was not significant (r = -0.172, p = 0.214). The CSA of the multifidus muscle showed no significant correlation with the FRR (r = 0.061, p = 0.655). In contrast, a significant positive correlation was identified between the FRR and the rate of thickness change in the multifidus (r = 0.301, p = 0.024). CONCLUSION:This study confirms that CNLBP involves multidimensional impairments, including pain perception and function, multifidus muscle morphology and activation function, neuromuscular regulation of the erector spinae, and sleep quality and psychological status. The identified correlations between FRR and both NRS and ODI scores provide a crucial basis for formulating individualized rehabilitation plans and for subsequent longitudinal research. TRIAL REGISTRATION:Chinese Registry of Clinical Trials: ChiCTR2400093968.

Spatial transcriptomics (STs) has emerged as a transformative approach to elucidate cellular heterogeneity and spatial organization within complex tissue microenvironments. However, the analysis of ST data is challenged by limited spatial resolution, resulting in mixed expression profiles at each spatial location. Moreover, the precious spatial information is rarely exploited, and noise issues in spatial transcriptomes (STs) are often overlooked by computational deconvolution methods. In this study, a novel computational framework for STs deconvolution (DeCoST), called DeCoST, is presented. DeCoST capitalizes on the valuable spatial context information by integrating a Gaussian kernel-based conditional autoregressive model. Additionally, the method employs domain adaptation techniques to address platform effects between single-cell and ST data, enabling robust cell type identification. Evaluations on simulated datasets under diverse spatial configurations, as well as real-world case studies on human pancreatic ductal adenocarcinoma, mouse olfactory bulb, and mouse brain samples, demonstrate the superior performance of DeCoST compared to existing deconvolution approaches. The method's ability to accurately map region-specific cell types and uncover spatial interactions advances our understanding of complex tissue organization and function, with broad applications in disease research and developmental biology.

OBJECTIVE:This study aims to improve the performance of auditory brain-computer interfaces (BCIs) by developing two-target and three-target paradigms based on steady-state motion auditory evoked potential (SSMAEP) using low-frequency stimuli in a spatial audio environment. SSMAEP is elicited by auditory stimuli exhibited by periodic and discrete changes in auditory spatial position. METHODS:We designed a periodic auditory motion stimulation paradigm to evoke SSMAEP. Two-target and three-target SSMAEP-BCIs were developed. For the two-target SSMAEP-BCI, two periodic auditory motion stimuli with different motion frequencies were located on the left (2 Hz) and right (1.6 Hz) sides of the head, respectively. For the three-target SSMAEP-BCI, three periodic auditory motion stimuli with different motion frequencies were located on the front (2 Hz), left (2.4 Hz) and right (1.6 Hz) sides of the head, respectively. RESULTS:SSMAEP amplitudes were modulated by auditory selective attention. In the two-target BCI, the offline experiments showed a peak average information transfer rate (ITR) of 7.70 bits/min, while the online experiments had a mean accuracy of 82.83% and an ITR of 4.41 bits/min. The three-target BCI achieved a peak ITR of 12.04 bits/min offline, with an online mean accuracy of 80.45% and an ITR of 7.05 bits/min. CONCLUSION:The study confirms the feasibility and enhanced performance of spatial low-frequency SSMAEP-BCIs. SIGNIFICANCE:This novel approach to SSMAEP-BCI offers a promising direction for enhancing auditory BCI performance, potentially improving user experience and application in complex environments.

Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactions within cells. Thanks to the advancements in spatial transcriptomics technology, we are now able to better decipher the process of cellular communication within the cellular microenvironment. Nevertheless, the majority of existing spatial cell–cell communication algorithms fail to take into account the downstream signals within cells. In this study, we put forward SpaCcLink, a cell–cell communication analysis method that takes into account the downstream influence of individual receptors within cells and systematically investigates the spatial patterns of communication as well as downstream signal networks. Analyses conducted on real datasets derived from humans and mice have demonstrated that SpaCcLink can help in identifying more relevant ligands and receptors, thereby enabling us to systematically decode the downstream genes and signaling pathways that are influenced by cell–cell communication. Comparisons with other methods suggest that SpaCcLink can identify downstream genes that are more closely associated with biological processes and can also discover reliable ligand-receptor relationships. By means of SpaCcLink, a more profound and all-encompassing comprehension of the mechanisms underlying cellular communication can be achieved, which in turn promotes and deepens our understanding of the intricate complexity within organisms.

Modern video games are increasingly aiming for more natural interactions and healthier gaming experiences. Haptic devices, in particular, can enhance these experiences by providing multimodal feedback and simulating a variety of body postures. However, limited attention has been paid to utilizing upper limb wearable haptic devices in video games. In. this study, we developed a flight video game that incorporates a wearable pneumatic haptic device. Our designed haptic feedback sleeve can deliver changes in both haptic forces and applied areas on the forearm. The proposed device consists of 40 airbag units made from two layers of TPU film, sealed by heat. To verify its performance, we conducted finite element simulations and experiments to assess the output force, area, and linearity of the airbag units. Two haptic perception experiments were conducted to verify the distribution of this haptic feedback device. Finally, experimental validation combining the flight video game was conducted. The results showed that the distributed upper limb haptic feedback sleeve reduced the user's following angle error by 12.99% when the aircraft roll speed was 16 deg/s. This finding indicates an enhancement in limb motor control ability using the proposed haptic feedback sleeve.

CAAT/Enhancer Binding Protein β (C/EBPβ) is associated with inflammatory responses in neurodegenerative pathologies, particularly in the brain. However, the regulatory role of C/EBPβ in spinal cord injury and its impact on neurological recovery remain unknown. In this study, we observed significant upregulation of C/EBPβ in microglia after spinal cord injury in mice and was associated with neuroinflammation. Knocking down C/EBPβ in the spinal cord attenuated microglia pyroptosis, reduced the production of proinflammatory cytokines, and inhibited neuronal apoptosis. Mechanistically, C/EBPβ promoted the transcription of Fcgr1, which was involved in activating microglia pyroptosis. In both in-vivo and in-vitro experiments, knocking down Cebpb or Fcgr1, or the pyroptosis inhibitor VX765 inhibited neuronal apoptosis and improved neurological recovery in mice. These findings indicate that C/EBPβ functions as a key regulator that participates in the microglia pyroptosis-mediated neuroinflammation by activating Fcgr1 transcription.

Recent advancements in methodologies and technologies have enabled the simultaneous measurement of multiple omics data, which provides a comprehensive understanding of cellular heterogeneity. However, existing methods have limitations in accurately identifying cell types while maintaining model interpretability, especially in the presence of noise. We propose a novel method called scMFG, which leverages feature grouping and group integration techniques for the integration of single-cell multi-omics data. By organizing features with similar characteristics within each omics layer through feature grouping. Furthermore, scMFG ensures a consistent feature grouping approach across different omics layers, promoting comparability of diverse data types. Additionally, scMFG incorporates a matrix factorization-based approach to enable the integrated results remain interpretable. We comprehensively evaluated scMFG’s performance on four complex real-world datasets generated using diverse sequencing technologies, highlighting its robustness in accurately identifying cell types. Notably, scMFG exhibited superior performance in deciphering cellular heterogeneity at a finer resolution compared to existing methods when applied to simulated datasets. Furthermore, our method proved highly effective in identifying rare cell types, showcasing its robust performance and suitability for detecting low-abundance cellular populations. The interpretability of scMFG was successfully validated through its specific association of outputs with specific cell types or states observed in the neonatal mouse cerebral cortices dataset. Moreover, we demonstrated that scMFG is capable of identifying cell developmental trajectories even in datasets with batch effects. Our work presents a robust framework for the analysis of single-cell multi-omics data, advancing our understanding of cellular heterogeneity in a comprehensive and interpretable manner.

Spinal cord injury (SCI) is a highly debilitating condition. Following SCI, the number of M1 microglia in the spinal cord increases, secreting numerous inflammatory factors that exacerbate the inflammatory response and activate resting astrocytes to form the neurotoxic A1 astrocytes. Hydrogels have good biocompatibility and their mechanical properties and bioactivity can be optimized by adjusting the ratios of their composition, whereby spinal cord repair can be promoted. This study aimed to compare the characteristics and bioefficacy of two hydrogels with different proportions of methacryloylated gelatin (GelMA) and pluronic F127 diacrylate, namely G5F and G10F hydrogels, prepared with 0.05 and 0.1 g/mL GelMA, respectively. Both the G5F and G10F hydrogels exhibited favorable properties, including plasticity, mechanical stability, and shear-thinning behavior. However, compared with the G5F hydrogel, the G10F hydrogel demonstrated a larger compressive modulus, tensile modulus and toughness, as well as a greater pore size. C3 expression was lower in cultured astrocytes treated with the conditioned medium from microglia cultured within G10F than in lipopolysaccharide-treated astrocytes, indicating that the G10F hydrogel inhibited microglial activation. G10F transplantation promoted motor recovery post-SCI better than G5F transplantation, as indicated by higher Basso Mouse Scale scores, footprint analysis results, and reduced scar areas observed through hematoxylin-eosin and GFAP staining. Additionally, immunostaining for Iba1, Ki67, iNOS, NeuN, and cleaved Caspase-3 revealed that G10F suppressed inflammatory responses and neuronal death more effectively than G5F via multiple inflammatory signaling pathways. Therefore, optimizing the proportions of hydrogel components offers new prospects for SCI treatment.

RNA velocity, as an extension of trajectory inference, is an effective method for understanding cell development using single-cell RNA sequencing (scRNA-seq) experiments. However, existing RNA velocity methods are limited by the batch effect because they cannot directly correct for batch effects in the input data, which comprises spliced and unspliced matrices in a proportional relationship. This limitation can lead to an incorrect velocity stream. This paper introduces VeloVGI, which addresses this issue innovatively in two key ways. Firstly, it employs an optimal transport (OT) and mutual nearest neighbor (MNN) approach to construct neighbors in batch data. This strategy overcomes the limitations of existing methods that are affected by the batch effect. Secondly, VeloVGI improves upon VeloVI’s velocity estimation by incorporating the graph structure into the encoder for more effective feature extraction. The effectiveness of VeloVGI is demonstrated in various scenarios, including the mouse spinal cord and olfactory bulb tissue, as well as on several public datasets. The results show that VeloVGI outperformed other methods in terms of metric performance.

BACKGROUND:Fatigue is one of the most common neurological symptoms reported post coronavirus disease 2019 (COVID-19) infection. In order to establish effective early intervention strategies, more emphasis should be placed on the correlation between fatigue and cortical neurophysiological changes, especially in healthcare workers, who are at a heightened risk of COVID-19 infection. METHODS:A prospective cohort study was conducted involving 29 COVID-19 medical workers and 24 healthy controls. The assessment included fatigue, sleep and health quality, psychological status, and physical capacity. Functional near-infrared spectroscopy (fNIRS) was employed to detect activation of brain regions. Bilateral primary motor cortex (M1) excitabilities were measured using single- and paired-pulse transcranial magnetic stimulation. Outcomes were assessed at 1, 3, and 6 months into the disease course. RESULTS:At 1-month post-COVID-19 infection, 37.9% of patients experienced severe fatigue symptoms, dropping to 10.3% at 3 months. Interestingly, the remarkable decreased activation/excitability of bilateral prefrontal lobe (PFC) and M1 were closely linked to fatigue symptoms after COVID-19. Notably, greater increase in M1 region excitability correlated with more significant fatigue improvement. Re-infected patients exhibited lower levels of brain activation and excitability compared to single-infection patients. CONCLUSIONS:Both single infection and reinfection of COVID-19 lead to decreased activation and excitability of the PFC and M1. The degree of excitability improvement in the M1 region correlates with a greater recovery in fatigue. Based on these findings, targeted interventions to enhance and regulate the excitability of M1 may represent a novel strategy for COVID-19 early rehabilitation. TRIAL REGISTRATION:The Ethics Review Committee of Xijing Hospital, No. KY20232051-F-1; www.chictr.org.cn , ChiCTR2300068444.

BackgroundPatients with low back pain (LBP) often suffer from sleep disorder, and insufficient sleep duration was recognized as a potential risk factor for LBP. Our aim was to explore the exact effect of sleep duration on LBP and the optimal sleep duration to reduce the risk of LBP.MethodsAnalyzing data from the Korean National Health and Nutrition Examination Survey (KNHANES), we investigated the association between sleep duration and LBP in individuals aged 50 years and older. We used logistic regression models, interaction stratification analysis, and threshold effect assessment to analyze the relationship between sleep duration and LBP.ResultsA total of 6,285 participants, comprising 3,056 males and 3,229 females with a median age of 63.1 years, were enrolled in the study. The association between sleep duration and LBP risk exhibited an L-shaped curve (p < 0.015) in RCS analysis. In the threshold analysis, the OR of developing risk of LBP was 0.864 (95% CI:0.78–0.957, p = 0.005) in participants with sleep duration <6.55 h. Each additional hour of sleep was associated with a 13.6% decrease in the risk of LBP. No significant association was observed between sleep duration ≥6.55 h and the risk of LBP. The risk of LBP did not decrease further with increasing sleep duration. Results remain robust across subgroups.ConclusionOur findings indicate that shorter sleep duration is a risk factor for LBP in adults aged over 50 years. We revealed an L-shaped association between sleep duration and LBP, with an inflection point at approximately 6.55 h per day. These results underscore the significance of sleep duration as a factor in the risk assessment for LBP.

Purpose: To explore the relationship between the systemic immune-inflammation index (SII) and deep venous thrombosis (DVT) in patients with spinal cord injury (SCI). Methods: This cross-sectional study included data from 382 participants with SCI. The SII was calculated for all participants. Logistic regression, smooth curve fitting, interaction effects were used to substantiate the research objectives. Results: The overall prevalence of DVT was 23.1% (22.4% among males, 25.6% among females). A positive association between SII and the risk for DVT was observed (odds ratio 1.39 [95% CI 1.03-1.87]; P=0.032), independent of confounders. Similar patterns of association were observed in the subgroup analysis (P values for interaction, all >0.05). Further sensitivity analyses provided confidence that the results were reliable and unlikely to be substantially altered by unmeasured confounding factors. Conclusion: Results of the present suggest that higher SII may be associated with DVT in patients with SCI, highlighting a potential link between SII and DVT. These findings underscore the potential of SII as a valuable predictive biomarker for DVT, thus offering a promising avenue for early detection and intervention strategies in patients with SCI. Plain Language Summary: The aim of this study was to investigate the relationship between the systemic immune-inflammation index (SII) and deep vein thrombosis (DVT) in patients with spinal cord injury (SCI). We analyzed data from 382 SCI patients and found that 23.1% of them had DVT. The risk of DVT was significantly increased by 39% with each 1-point increase in SII (OR = 1.39, 95% CI: 1.03-1.87, p = 0.031). Our results showed that higher SII values were associated with an increased risk of DVT, independent of other factors. This suggests that SII may be used as a potential biomarker to predict DVT in SCI patients, highlighting the importance of early detection and intervention. This finding could greatly contribute to the early detection and management of DVT in SCI patients using SII.

AIMS:Neurogenic bladder (NB) is a prevalent and debilitating consequence of spinal cord injury (SCI). Indeed, the accurate prognostication of early bladder outcomes is crucial for patient counseling, rehabilitation goal setting, and personalized intervention planning. METHODS:A retrospective exploratory analysis was conducted on a cohort of consecutive SCI patients admitted to a rehabilitation facility in China from May 2016 to December 2022. Demographic, clinical, and electrophysiological data were collected within 40 days post-SCI, with bladder outcomes assessed at 3 months following SCI onset. RESULTS:The present study enrolled 202 SCI patients with a mean age of 40.3 ± 12.3 years. At 3 months post-SCI, 79 participants exhibited complete bladder emptying. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analyses identified the H-reflex of the soleus muscle, the American Spinal Injury Association Lower Extremity Motor Score (ASIA-LEMS), and the time from lesion to rehabilitation facility (TLRF) as significant independent predictors for bladder emptying. A scoring system named HALT was developed, yielding a strong discriminatory performance with an area under the receiver operating characteristics curve (aROC) of 0.878 (95% CI: 0.823-0.933). A simplified model utilizing only the H-reflex exhibited excellent discriminatory ability with an aROC of 0.824 (95% CI: 0.766-0.881). Both models demonstrated good calibration via the Hosmer-Lemeshow test and favorable clinical net benefits through decision curve analysis (DCA). In comparison to ASIA-LEMS, both the HALT score and H-reflex showed superior predictive accuracy for bladder outcome. Notably, in individuals with incomplete injuries, the HALT score (aROC = 0.973, 95% CI: 0.940-1.000) and the H-reflex (aROC = 0.888, 95% CI: 0.807-0.970) displayed enhanced performance. CONCLUSION:Two reliable models, the HALT score and the H-reflex, were developed to predict bladder outcomes as early as 3 months after SCI onset. Importantly, this study provides hitherto undocumented evidence regarding the predictive significance of the soleus H-reflex in relation to bladder outcomes in SCI patients.

Crack failures frequently occur in aero-engine blades which can trigger a cascade of accidents. Previous studies have primarily focused on crack-induced nonlinear vibration, and the contact state of the crack surfaces during crack breathing is often neglected. However, it is important to consider the contact behavior of the crack surfaces as it is responsible for generating nonlinear vibrations. To further investigate the mechanism behind crack-induced nonlinear vibrations, a novel dynamic contact breathing crack model (DCBCM) for rotating blades is proposed based on the self-programmed incompatible hexahedral element (SNCHE). The breathing effect is simulated using spring elements. The proposed DCBCM is validated by the contact finite element model. Moreover, the effects of crack parameters (depth and location) and load parameters (aerodynamic amplitude and aerodynamic frequency) on the dynamic contact characteristics are investigated. Furthermore, a breathing crack quantification indicator (BCQI) is proposed to represent the nonlinear level of breathing crack. The results indicate that the crack may close from the sides of the blade toward the center of the crack front during crack breathing. Besides, the BCQI increases with the increase of crack depth, aerodynamic amplitude, and rotational speed; while decreases as the crack moves closer to the blade tip.

Introduction:Providing stimulation enhancements to existing hand rehabilitation training methods may help stroke survivors achieve better treatment outcomes. This paper presents a comparison study to explore the stimulation enhancement effects of the combination of exoskeleton-assisted hand rehabilitation and fingertip haptic stimulation by analyzing behavioral data and event-related potentials.Methods:The stimulation effects of the touch sensations created by a water bottle and that created by cutaneous fingertip stimulation with pneumatic actuators are also investigated. Fingertip haptic stimulation was combined with exoskeleton-assisted hand rehabilitation while the haptic stimulation was synchronized with the motion of our hand exoskeleton. In the experiments, three experimental modes, including exoskeleton-assisted grasping motion without haptic stimulation (Mode 1), exoskeleton-assisted grasping motion with haptic stimulation (Mode 2), and exoskeleton-assisted grasping motion with a water bottle (Mode 3), were compared.Results:The behavioral analysis results showed that the change of experimental modes had no significant effect on the recognition accuracy of stimulation levels (p = 0.658), while regarding the response time, exoskeleton-assisted grasping motion with haptic stimulation was the same as grasping a water bottle (p = 0.441) but significantly different from that without haptic stimulation (p = 0.006). The analysis of event-related potentials showed that the primary motor cortex, premotor cortex, and primary somatosensory areas of the brain were more activated when both the hand motion assistance and fingertip haptic feedback were provided using our proposed method (P300 amplitude 9.46 μV). Compared to only applying exoskeleton-assisted hand motion, the P300 amplitude was significantly improved by providing both exoskeleton-assisted hand motion and fingertip haptic stimulation (p = 0.006), but no significant differences were found between any other two modes (Mode 2 vs. Mode 3: p = 0.227, Mode 1 vs. Mode 3: p = 0.918). Different modes did not significantly affect the P300 latency (p = 0.102). Stimulation intensity had no effect on the P300 amplitude (p = 0.295, 0.414, 0.867) and latency (p = 0.417, 0.197, 0.607).Discussion:Thus, we conclude that combining exoskeleton-assisted hand motion and fingertip haptic stimulation provided stronger stimulation on the motor cortex and somatosensory cortex of the brain simultaneously; the stimulation effects of the touch sensations created by a water bottle and that created by cutaneous fingertip stimulation with pneumatic actuators are similar.

步行功能的恢复是脑卒中后康复治疗最重要的目标之一[1].既往的研究表明,约38％的脑卒中患者在发病后6个月仍不能行走[2],而那些出院时可以步行的患者,回归家庭后的步行能力也大幅下降[3].因此,恢复步行功能对脑卒中患者至关重要.我们前期的研究已经证实,末端驱动型机器人(GEO system)比常规减重平板步行训练更能改善脑卒中患者的步行功能[4-5],但是具体的机制还不清楚.