The rate of obesity in adolescents has increased due to social distancing measures and school closures caused by the COVID-19 pandemic. These issues have caused adolescents to change their lifestyles and eating habits. Furthermore, the growth in inactive behavior and computer screen or watching TV time, as well as the reduction in physical activity, could similarly be related with obesity. To overcome this problem, we recently developed an artificial intelligence (AI)-based gesture recognition game application called Super Kids Adventure (SUKIA, Funrehab, Daejeon, Korea), which provides inexpensive and motivational game applications. This research is designed to assess the effects of SUKIA and Nintendo Switch (NINS) on calorie consumption, VO2 max, 6-minute walking test (6MWT) as well as body mass index (BMI), and the Borg rating of perceived exertion scale (RPE) in adolescents with obesity. A convenience sample of 24 adolescents with obesity were randomized into either the NINS or SUKIA groups 5 days/week for 3 weeks. Analysis of variance (ANOVA) and independent t-tests were presented with significant level at p < 0.05, and the analysis indicated that SUKIA showed superior effects on calorie consumption, VO2 max, and RPE compared to NINS. Our results provide evidence that SUKIA can more effectively improve cardiopulmonary function and calorie consumption than NINS in adolescents with obesity during COVID-19.

We aimed to compare the effects of robotic-assisted gait training (RAGT) in patients with FAC < 2 (low initial functional ambulation category [LFAC]) and FAC ≥ 2 (high initial functional ambulation category [HFAC]) on sensorimotor and spasticity, balance and trunk stability, the number of steps and walking distance in subacute hemiparetic stroke. Fifty-seven patients with subacute hemiparetic stroke (mean age, 63.86 ± 12.72 years; 23 women) were assigned to two groups. All patients received a 30-min Walkbot-assisted gait training session, 3 times/week, for 6 weeks. Clinical outcomes included scores obtained on the Fugl–Meyer Assessment (FMA) scale, Modified Ashworth Scale (MAS), Berg Balance Scale (BBS), trunk impairment scale (TIS), and the number of walking steps and walking distance. Analysis of covariance and analysis of variance were conducted at p < 0.05. Significant main effects of time in both groups on number of walking steps and distance (p < 0.05) were observed, but not in MAS (p> 0.05). Significant changes in FMA, BBS, and TIS scores between groups (p < 0.05) were observed. Significant main effects of time on BBS and TIS were demonstrated (p < 0.05). Our study shows that RAGT can maximize improvement in the functional score of FMA, BBS, TIS, steps, and distance during neurorehabilitation of subacute stroke patients regardless of their FAC level.

The present study aimed to determine a multimodal brain empowerment (MBE) program to mitigate the modifiable risk factors in mild cognitive impairment (MCI), and its therapeutic effects are unknown. MBE encompassing (1) tDCS, light therapy, computerized cognitive therapy (TLC) and (2) robot-assisted gait training, music therapy, and core exercise (REM) interventions were randomly assigned to 20 healthy young adults and 20 older adults with MCI. The electroencephalography (EEG) power spectrum and topographic event-related synchronization (ERS) analysis were used to assess intervention-related changes in neural activity during the MBE program. Outcome: The EEG results demonstrated that both multimodal TLC and REM decreased delta waves and increased theta, alpha, and beta waves (p < 0.001). ERS showed increased neural activation in the frontal, temporal, and parietal lobes during TLC and REM. Such enhanced neural activity in the region of interest supports potential clinical benefits in empowering cognitive function in both young adults and older adults with MCI.