Hai Li

Introduction: To investigate whether there is an association between nocturnal-daytime sleep patterns as well as social participation and memory-related categories of diseases in the middle-aged and elderly population in China. Material and methods: This study was based on data from the Peking University China Health and Aging Tracking Survey (CHARLS), and a total of 19,023 study participants were analyzed in the year 2018 according to the inclusion and exclusion criteria. Logistic regression models were used to explore the relationship between different night-time-daytime sleep patterns, social participation, and memory-related categories of disorders step by step with adjustments for different covariates, and the odds ratios (ORs) and 95% confidence intervals (95% Cl) were obtained. Results: Logistic regression models gradually adjusted for confounding with nighttime sleep duration >5 h and daytime sleep duration ≤30 min group, Going to a sport, social, or other club activity and social participation as the protective factors of memory-related class of diseases. Stratified analyses found that among males, people living in rural areas, and married people, the group with >5 h of nighttime sleep and ≤30 min of daytime sleep was a protective factor for memory-related classes of diseases. Among women, people living in urban areas, and married people, social participation was a protective factor for memory-related diseases. Conclusions: Nighttime sleep time >5 h, daytime sleep time ≤30 min group, and social participation are independent protective factors for memory-related class disorders in older adults. Keywords: sleep patterns, social participation, memory-related disorders, CHARLS, middle‐aged and older adults

Motor intent (MI)-based muscle computer interfaces (MCIs) have been widely explored for prosthetic control as a means of restoring functionality to the lost limb in amputees. However, persistent issues remain, such as insufficient robustness of the current features, the presence of coherent noise, and the low spatial resolution of electromyography (EMG) sensors. Subsequently, these results in decreased movement characterization performance. Therefore, this study introduces a novel feature extraction technique that utilizes a Sliding Mode Differentiator (SMD) to extract unique patterns from EMG signals, followed by the deployment of symmetric positive definite matrices (SPD) to efficiently leverage the spatial-temporal properties of the EMG signal. The average classification results of 98.7±3.0% and 97.9±5.2% for 21 able-bodied subjects and 15 amputees respectively, suggests an improvement in accuracy for characterizing 13 hand gestures, thereby outperforming other state-of-the-art feature methods. Further, the channel optimization analysis shows that the number of channels can be reduced by 75% (from 24 channels to 6 channels) without compromising the performance of the proposed technique. This justifies the potential of the proposed technique in both high-density and sparse-density EMG electrode configurations. Additional analysis of the performance of the techniques in the presence of noise indicates that the proposed method can significantly outperform other methods. Therefore, the findings of this study have the potential to significantly improve the control performance of prostheses, rehabilitation assistive robots, and hand gesture-related games.

Accurate decoding of motor intent in electromyogram (EMG)-based pattern recognition systems heavily depends on effective feature extraction. Although numerous techniques have been introduced, their performance remains suboptimal. Many fail to utilize spatial dependencies across EMG channels and overlook the distributional shift between training and test data. To overcome these challenges, this study introduces an unsupervised feature extraction method. It employs Dynamic Mode Decomposition (DMD) to isolate meaningful spatiotemporal patterns associated with hand gestures, followed by enhanced spatial representation through the Sample Covariance Matrix (SCM). To address dataset drift, the method aligns test data within the same non-Euclidean space as the training data. Experimental results show a significant improvement (p < 0.05) in decoding 13 distinct hand and finger gestures, with average accuracies of 99.89 ± 0.28% for amputees and 99.90 ± 0.31% for non-disabled subjects. Importantly, the method retains over 97% accuracy even when the number of EMG channels is reduced from 24 to just 3, suggesting its potential across both dense and sparse sensor configurations. This may be useful for low-cost prosthetic designs, where reducing the number of electrodes can decrease hardware complexity and cost. Thus, the proposed technique shows promise for improving the performance, reliability, and adaptability of EMG-based control systems, with potential relevance to clinical and commercial applications after further real-time and clinical validation.

Background: Stroke often results in significant motor impairments, particularly in the upper limbs, which can severely impact functional independence and quality of life. Conventional rehabilitation methods provide limited recovery, necessitating the exploration of adjunctive therapies to enhance motor function. Intermittent theta burst stimulation (iTBS) is a brain stimulation technique that has shown promise in improving motor function after stroke. This study was conducted to investigate whether iTBS targeting ipsilesional primary motor cortex can induce improvements of the paretic upper limb and physiological changes in cortical excitability in subacute stroke patients.Methods: 50 patients were randomized assigned to either iTBS or sham stimulation across 10 sessions. Motor function, symptom severity, muscle tone, and functional independence were evaluated. Additional measures included rest motor threshold (RMT), oxygenated hemoglobin concentration.Results: Both the iTBS and sham groups showed significant improvements in National Institutes of Health Stroke Scale (NIHSS) (iTBS: p = 0.002; sham: p = 0.039), Fugl-Meyer Assessment (FMA) (iTBS: p < 0.001; sham: p = 0.005), and Modified Barthel Index (MBI) (iTBS: p < 0.001; sham: p = 0.002) scores post-intervention. Only the iTBS group demonstrated significant improvements in Modified Ashworth Scale (MAS) (p < 0.001), Wolf Motor Function Test (WMFT) (p < 0.001), and RMT (p = 0.016). The iTBS group exhibited a trend toward greater improvements in MAS (p = 0.001), WMFT (p = 0.002), and MBI (p < 0.001). RMT in contralateral Primary motor cortex (M1) was significantly lower in the iTBS group (p = 0.016), and functional connectivity between each M1 regions was notably enhanced (p = 0.049).Conclusion: These findings suggest that iTBS may offer additional benefits in improving functional task performance and cortical connectivity in subacute stroke patients.Clinical trial registration: https://www.chictr.org.cn/showproj.html?proj=193454, Identifier ChiCTR2300072415.

The objective of this study was to translate the Family Quality of Life (FQOL) Scale into simplified Chinese and assess its reliability and validity in mainland China for families of children with autism. The FQOL Scale was professionally translated from English into simplified Chinese using a forward-backward process. We conducted a survey in which families with autistic kids were asked to participate, it comprised of a general condition questionnaire and the FQOL Scale translated to Chinese. A total of 402 families took part in the study, out of which 333 data sets were complete and available for analysis. The FQOL Scale model was subject to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to probe its scale dimensional design and structure, as well as its adaptability to autistic children and their families using SPSS AMOS 24.0. The internal consistency and reliability was examined using Cronbach’s α (SPSS 22.0). And stepwise regression analysis was conducted to predict parents’ attitudes towards prognosis based on the five dimensions of the modified Chinese version of the FQOL Scale (SPSS 22.0). The data analysis yielded a revised Chinese version of the FQOL Scale. The analysis revealed that the overall reliability coefficient of the scale, as indicated by Cronbach’s α, was 0.918. The results of the CFA provided support for the best fit of a five-factor model (χ2 = 285.237, CFI = 0.930, TLI = 0.916, SRMR = 0.061, RMSEA = 0.062). The predictive equation for parents’ attitudes towards prognosis based on the five-dimensional model of the modified Chinese version of the FQOL Scale was as follows: Parent prognostic attitude = -0.863 + 0.456* Parenting + 0.2* Physical/Material Well-being. The modified Chinese version of the FQOL Scale is suitable in mainland China for families of children with autism and has good reliability and model fit. The two dimensions of Parenting and Physical/Material Well-being can significantly predict parents’ prognostic attitude, indicating that the better the status of Parenting and Physical/Material Well-being, the better the parents’ prognosis attitude.

Patients with chronic low back pain (CLBP) usually demonstrate poor postural control due to impaired core muscle function. Dynamic neuromuscular stabilization (DNS) is based on developmental kinesiology principles, utilizing infant motor patterns to treat motor disorders. DNS has been shown to improve postural control in cerebral palsy patients by activating core muscle. However, whether the DNS approach is superior for enhancing core muscle contractility and postural control in CLBP patients still remains unclear. This study aimed to compare the effects of DNS training and conventional core exercises on core muscle contractility and standing postural control in CLBP patients. Sixty CLBP patients were randomly assigned to a DNS group or a control group. Participants in the DNS group received DNS training, while those in the control group completed conventional core exercises. Both groups completed 12 sessions over 4 weeks (3 sessions/week, 50 min/session). Pre- and post-intervention evaluations included diagnostic musculoskeletal ultrasound to assess the change rate of core muscles (transversus abdominis (TrA), lumbar multifidus, and diaphragm), a balance assessment system to evaluate postural control performance (center of pressure displacement (COP)), and clinical questionnaires (Visual Analog Scale (VAS), Oswestry Disability Index (ODI), and Roland-Morris Disability Questionnaire (RDQ)) for pain intensity and disability. After 4 weeks, comparisons between both groups revealed significant statistical differences in the interaction effects of time*group. These differences were observed in the change rates of the left and right TrA (F1,58=4.820 and 3.964, p = 0.032 and 0.041), diaphragm change rate (F1,58=11.945, p = 0.001), as well as COP velocity (F1,58=5.283, p = 0.025), variability (F1,58=13.189, p = 0.001) in the anterior-posterior (AP) direction, COP path length (F1,58=6.395, p = 0.014), and COP area (F1,58=5.038, p = 0.029) in the eye-closed condition. DNS participants showed significantly greater muscle change rates and reduced COP (p < 0.05). The scores of VAS (F1,58=173.929, p = 0.001), ODI (F1,58=60.871, p = 0.001), and RDQ (F1,58=60.015, p = 0.001) decreased significantly over time, although no group differences were found between both groups (p > 0.05). DNS is superior to conventional core exercises in enhancing core muscle contractility and standing postural control in CLBP patients, showing potential to reduce pain and improve disability. Its mechanism may involve the enhancement of proprioceptive feedback, particularly when visual feedback is blocked. This study was registered in the Chinese Clinical Trial Registry (ChiCTR) with the registration number ChiCTR2300074595 on 10 August 2023.

Understanding the coordination between the pelvis and lower limbs in individuals with hemiplegic gait is crucial for deciphering their walking patterns. While studies have focused on lower limb kinematics in stroke patients, research on pelvis-lower limb coordination remains limited. This study aims to assess pelvis-lower limb coordination and kinematics in stroke patients using statistical parametric mapping (SPM) and smartphone-based markerless motion capture. Seventeen stroke patients and twenty healthy individuals were recruited to collect locomotion data using dual smartphone videos. For comparison, the time-series coordination of the pelvis-thigh, thigh-shank, and shank-foot among the control, paretic, and nonparetic limbs were analyzed using SPM and continuous relative phase (CRP). The results showed that there were significant differences (p < 0.05) in the CRP curves of the pelvis-thigh in the sagittal plane (50–62% of the gait cycle), pelvis-thigh in the coronal plane (0–100% of the gait cycle), thigh-shank (65–92% of the gait cycle), and shank-foot (13–29% and 57–68% of the gait cycle) across the different segments. Assessing the coordination and kinematics of the pelvis and lower limbs using a feasible and portable motion capture technique could assist clinicians in identifying potential muscle dysfunction while uncovering the compensatory strategies that individuals with hemiplegic gait may use to maintain balance, stability, and propulsion during walking. These results could guide clinicians in targeting interventions to reduce spasticity and strengthen muscles, ultimately enhancing coordination, optimizing gait mechanics, and improving functional outcomes.