Objective: To examine the effectiveness of virtual reality (VR)-based rehabilitation training in improving cognition, motor function, and daily functioning in patients with mild cognitive impairment and dementia. Data sources: A systematic review of published literature was conducted using PubMed, Web of Science, Elsevier, Embase, Cochrane, CNKI, Networked Digital Library of Theses and Dissertations. Methods: The search period was from inception to 7 October 2023. Eligible studies were randomized controlled trials evaluating the efficacy of VR-based rehabilitation training in patients with mild cognitive impairment or dementia versus control subjects. Methodologic quality was assessed with the Cochrane risk of bias tool, and outcomes were calculated as the standard mean difference between participant groups with 95% confidence interval. Results: A total of 21 randomized controlled trials with 1138 patients were included. The meta-analysis showed that VR-based rehabilitation training had significant effects on Montreal Cognitive Assessment (SMD: 0.50; 95%CI: 0.05 to 0.95; P = 0.030), Trail-making test A (SMD: −0.38; 95%CI: −0.61 to −0.14; P = 0.002), and Berg Balance Scale scores (SMD: 0.79; 95%CI: 0.13 to 1.45; P = 0.020). A subgroup analysis revealed that the type of VR, and duration and frequency of interventions had statistically significant effects on cognition and motor function. Conclusion: VR-based rehabilitation training is a beneficial nonpharmacologic approach for managing mild cognitive impairment or dementia. Immersive VR-based training had greater effects on cognition and motor function than non-immersive VR-based training, but non-immersive VR-based training was more convenient for patients with limitations imposed by their disease. Also, an intervention lasting 5–8 weeks and for >30 min at a frequency of ≥3 times/week achieved the best results. It indicated that a longer intervention cycle may not achieve the best intervention effect and training duration and schedule should be carefully considered when managing patients.

Introduction: Running is one of the most popular sports in the world, but it also increases the risk of injury. The purpose of this study was to establish a modeling approach for IMU-based subdivided action pattern evaluation and to investigate the classification performance of different deep models for predicting running fatigue.Methods: Nineteen healthy male runners were recruited for this study, and the raw time series data were recorded during the pre-fatigue, mid-fatigue, and post-fatigue states during running to construct a running fatigue dataset based on multiple IMUs. In addition to the IMU time series data, each participant’s training level was monitored as an indicator of their level of physical fatigue.Results: The dataset was examined using single-layer LSTM (S_LSTM), CNN, dual-layer LSTM (D_LSTM), single-layer LSTM plus attention model (LSTM + Attention), CNN, and LSTM hybrid model (LSTM + CNN) to classify running fatigue and fatigue levels.Discussion: Based on this dataset, this study proposes a deep learning model with constant length interception of the raw IMU data as input. The use of deep learning models can achieve good classification results for runner fatigue recognition. Both CNN and LSTM can effectively complete the classification of fatigue IMU data, the attention mechanism can effectively improve the processing efficiency of LSTM on the raw IMU data, and the hybrid model of CNN and LSTM is superior to the independent model, which can better extract the features of raw IMU data for fatigue classification. This study will provide some reference for many future action pattern studies based on deep learning.

Background: The related functions of skeletal muscle and brain decrease significantly with age, and muscle-brain-related diseases are primarily associated with each other. Exercise can promote the secretion of myokines in skeletal muscle, showing a beneficial effect on the function of both, reflecting muscle-brain crosstalk. However, the key mechanism of action of exercise-regulated myokines in muscle-brain diseases remains unclear. Summary: This review is intended to sort out and explore the key mechanism of the effect of exercise regulatory myokines on muscle-brain diseases through summarizing the relevant literature on the level of motor regulatory myokines in recent years and pay special attention to the impact of exercise type, intensity, and duration on myokine expression levels. Key Messages: The mechanism by which exercise regulates myokine levels in muscle-brain diseases is explained, and an effective exercise prescription for myokine expression that is more suitable for the elderly based on relevant literature is proposed. This work may hold certain value for subsequent exercise treatment of chronic diseases in the elderly and for further research on muscle-brain crosstalk.

Visual cognition plays a pivotal role in sports. It is widely recognized that there is an intriguing coupling that they could affect each other through interaction between visual cognition and motor control, but few studies linked the effects of visual cognitive tasks on landing stability to postural control and injury risk. Whether visual cognitive tasks affect the landing stability and lower limb injury risk of professional soccer players? The current study used a three-dimensional Multiple Object Tracking (MOT) task to simulate visual cognitive difficulties experienced in soccer matches. Fifteen male high-level soccer athletes (height: 181.43 ± 7.36 cm, weight: 75.37 ± 10.67 kg, training years: 10.07 ± 2.98 yr) from our school team were recruited and completed a landing action from a high platform with and without MOT tasks. Vicon infrared high-speed motion capture system and three-dimensional force measuring platform were used to collect various outcomes simultaneously. The Time to Stabilization (TTS) during landing was significantly prolonged, while the Medial-Lateral Stability Index (MLSI), Anterior-Posterior Stability (APSI), Dynamic Postural Index Stability Index (DPSI), the trajectory lengths, and envelope area of COP during landing were also increased during MOT dual-task. The decline of these indicators reflected the deterioration in postural stability and greater requirements for maintaining balance which could increase the risk of injury in soccer athletes. We advocate that adequate visual attention and visual information processing might play critical roles in maintaining dynamic balance through the supraspinal neural network.