Background: Mild cognitive impairment (MCI) is a critical stage of dementia. Previous reviews have suggested that physical exercise combined with non-invasive brain stimulation is more beneficial for improving cognitive function. However, no targeted studies have confirmed the effect of Tai Chi combined with transcranial direct current stimulation (tDCS) on the improvement of cognitive function in patients with MCI. Thus, this randomized trial was conducted to assess the effect of Tai Chi combined with tDCS on the cognitive performance of patients with MCI.Methods: From April 2018 to February 2020, a randomized, single-blind clinical trial was conducted, involving 180 participants with MCI who were divided into four intervention groups: Tai Chi combined with tDCS (TCT), Tai Chi combined with sham tDCS (TCS), walking combined with tDCS (WAT), and walking combined with sham tDCS (WAS). All participants were assessed at baseline and 12 weeks for global cognitive function, memory, attention, and executive function.Results: At baseline, there were no significant differences in age, gender, education duration, body mass index, or the Baker Depression Inventory among the four groups (P ≥ 0.05). After 12 weeks of intervention, the TCT group showed greater improvements in MOCA scores, memory quotient scores, and digit-symbol coding task reaction time compared to the TCS, WAS, and WAT groups (P < 0.05). The TCT group also had a shorter Stroop test color reaction time compared to the WAS and WAT groups (P < 0.05), a higher increase in Auditory Verbal Learning Test-immediate recall than the TCS and WAT groups (P < 0.05), a shorter visual reaction time than the TCS group (P < 0.05), and a shorter sustained attention time compared to the WAT group (P < 0.05).Conclusion: Tai Chi combined with tDCS effectively improves global cognitive performance, memory, execution function, and attention in patients with MCI. These findings suggest the potential clinical use of Tai Chi combined with tDCS as a physical exercise combined with a non-invasive brain stimulation intervention to improve cognitive function in older adults with MCI.Clinical trial registration: ChiCTR1800015629.

Background: Mind–body exercise (MBE) has shown promise in mitigating the effects of sarcopenia and frailty in older adults. Nevertheless, its effectiveness in enhancing muscle function and physical performance in this population has not been well established. This study aimed to investigate the effects of MBE on older adults with sarcopenia and frailty, to offer evidence‐based exercise recommendations. Methods: A comprehensive search for randomized controlled trials (RCTs) was conducted through multiple databases, including PubMed, Embase, Cochrane Library, Web of Science, PsycINFO, CINAHL, China National Knowledge Infrastructure (CNKI), WanFang, and Chinese Scientific Journals Full‐Text Database (VIP), supplemented by manual reference searches from inception until February 2024. The eligible RCTs compared MBE with passive or active exercise controls, focusing on muscle function and physical performance in older adults aged 60 years or above. Subgroup analyses were conducted to evaluate the types, duration, and frequency of MBE. Results: Nine eligible RCTs with 1838 participants were included in this study. MBE demonstrated significant improvements compared with passive control, particularly in grip strength (WMD [weighted mean difference] = 0.99; 95% CI [95% confidence interval] = 0.06, 1.92; I ² = 3%, p = 0.04), Timed Up and Go Test (TUGT) (WMD = −4.04; 95% CI = −5.54, −2.53; I ² = 12%, p < 0.01), and Berg Balance Scale (BBS) scores (WMD = 3.63; 95% CI = 0.38, 6.87; I ² = 0%, p = 0.03). Even when compared to active exercise training, improvements were still observed in TUGT and BBS ( p < 0.001), with a trend toward improved grip strength (WMD = −2.20; 95% CI = −4.35, −0.04; p = 0.05). No positive effect on muscle mass was observed. Subgroup analysis indicated that MBE performed more than 5 times a week for a short or medium duration (4–24 weeks) could improve grip strength ( p < 0.05). Moderate‐frequency intervention over a short period in this population yielded greater improvements in gait speed and Chair Rise Test completion time ( p < 0.05). Conclusions: MBE can enhance muscle function and physical performance to some extent in older adults with sarcopenia and frailty, whether they are compared with passive or active exercise training. However, positive effects on muscle mass have not been observed. Future studies are warranted to compare it with well‐designed active exercise training programs that match the exercise volume, to draw more definitive conclusions to support the notion that MBE yields comparable effects.

Objective: The aim of this systematic review was to evaluate the effects of tai chi on metabolic con...

Introduction: Using wrist-wearable sensors to ecological transient assessment may provide a more valid assessment of physical activity, sedentary time, sleep and circadian rhythm than self-reported questionnaires, but has not been used widely to study the association with mild cognitive impairment and their characteristics.Methods: 31 normal cognitive ability participants and 68 MCI participants were monitored with tri-axial accelerometer and nocturnal photo volumetric pulse wave signals for 14 days. Two machine learning algorithms: gradient boosting decision tree and eXtreme gradient boosting were constructed using data on daytime physical activity, sedentary time and nighttime physiological functions, including heart rate, heart rate variability, respiratory rate and oxygen saturation, combined with subjective scale features. The accuracy, precision, recall, F1 value, and AUC of the different models are compared, and the training and model effectiveness are validated by the subject-based leave-one-out method.Results: The low physical activity state was higher in the MCI group than in the cognitively normal group between 8:00 and 11:00 (P < 0.05), the daily rhythm trend of the high physical activity state was generally lower in the MCI group than in the cognitively normal group (P < 0.05). The peak rhythms in the sedentary state appeared at 12:00–15:00 and 20:00. The peak rhythms of rMSSD, HRV high frequency output power, and HRV low frequency output power in the 6h HRV parameters at night in the MCI group disappeared at 3:00 a.m., and the amplitude of fluctuations decreased; the amplitude of fluctuations of LHratio nocturnal rhythm increased and the phase was disturbed; the oxygen saturation was between 90 and 95% and less than 90% were increased in all time periods (P < 0.05). The F1 value of the two machine learning algorithms for MCI classification of multi-feature data combined with subjective scales were XGBoost (78.02) and GBDT (84.04).Conclusion: By collecting PSQI Scale data combined with circadian rhythm characteristics monitored by wrist-wearable sensors, we are able to construct XGBoost and GBDT machine learning models with good discrimination, thus providing an early warning solution for identifying family and community members with high risk of MCI.