The present study examined whether a culture-based virtual reality (VR) training program is feasible and tolerable for patients with amnestic mild cognitive impairment (aMCI), and whether it could improve cognitive function in these patients. Twenty-one outpatients with aMCI were randomized to either the VR-based training group or the control group in a 1:1 ratio. The VR-based training group participated in training for 30 min/day, two days/week, for three months (24 times). The VR-based program was designed based on Korean traditional culture and used attention, processing speed, executive function and memory conditions to stimulate cognitive function. The adherence to the culture-based VR training program was 91.55% ± 6.41% in the VR group. The only adverse events observed in the VR group were dizziness (4.2%) and fatigue (8.3%). Analysis revealed that the VR-based training group exhibited no significant differences following the three-month VR program in Korean Mini-Mental State Examination (K-MMSE) scores, working memory functions such as performance on the digit span test, or in Stroop test performance and word fluency. We conclude that although the 12-week culture-based VR training program did not improve cognitive function, our findings revealed that the culture-based VR training program was feasible and tolerable for participants with aMCI.

We investigated the effectiveness of virtual-reality-based cognitive training (VRCT) and exercise on the brain, cognitive, physical and activity of older adults with mild cognitive impairment (MCI). Methods: This study included 99 participants (70.8 ± 5.4) with MCI in the VRCT, exercise, and control groups. The VRCT consisted of a series of games targeting different brain functions such as executive function, memory, and attention. Twenty-four sessions of VRCT (three days/week) were performed, and each session was 100 min long. Exercise intervention consisted of aerobic and resistance trainings performed in 24 sessions for 60 min (2 times/week for 12 weeks). Global cognitive function was measured using the Mini-Mental State Examination (MMSE) test. Resting-state electroencephalography (EEG) of the neural oscillatory activity in different frequency bands was performed. Physical function was measured using handgrip strength (HGS) and gait speed. Results: After the intervention period, VRCT significantly improved the MMSE scores (p < 0.05), and the exercise group had significantly improved HGS and MMSE scores (p < 0.05) compared to baseline. One-way analysis of variance (ANOVA) of resting-state EEG showed a decreased theta/beta power ratio (TBR) (p < 0.05) in the central region of the brain in the exercise group compared to the control group. Although not statistically significant, the VRCT group also showed a decreased TBR compared to the control group. The analysis of covariance (ANCOVA) test showed a significant decrease in theta band power in the VRCT group compared to the exercise group and a decrease in delta/alpha ratio in the exercise group compared to the VRCT group. Conclusion: Our findings suggest that VRCT and exercise training enhances brain, cognitive, and physical health in older adults with MCI. Further studies with a larger population sample to identify the effect of VRCT in combination with exercise training are required to yield peak benefits for patients with MCI.

A limited number of studies have used objective measures to examine the associations between the built environment and physical activity (PA) among older adults. This study aimed to examine geographic information systems-derived neighborhood walkability attributes and accelerometer measured PA in older adults. Data were collected from 124 older Taiwanese adults aged over 60 years (mean age: 69.9). Adjusted multiple linear regression was performed to explore the associations between five neighborhood walkability factors (population density, street connectivity, sidewalk availability, access to destinations, and public transportation) and five metrics of accelerometer-measured physical activity (total PA, moderate-to-vigorous PA, light PA, long moderate-to-vigorous PA bouts, and daily step counts). After adjusting for potential confounders, we found that greater sidewalk availability was positively associated with daily step counts in older adults (β = 0.165; 95% confidence interval: 0.006, 0.412; P = 0.043). No associations between other neighborhood environment attributes and PA metrics were observed. In conclusion, high sidewalk availability in the neighborhood may be supportive for older adults’ daily step counts. Further longitudinal research is needed to establish the causality between the built environment and objectively measured PA in older adults.

Background: Lifestyle behaviors are modifiable factors that can provide information for designing intervention strategies for sarcopenia. The present study aimed to identify the relationships between a range of daily lifestyle behaviors and sarcopenia risks among older adults.Methods: A nationwide telephone-based survey targeting older adults (≥65 years) was performed in Taiwan. Data based on self-reported daily lifestyle behaviors (food selection, physical activity, sitting time, and sleep duration), the presence or absence of sarcopenia (measured by SARC-F), and personal characteristics were obtained. Binary logistic regression models were applied.Results: A total of 1068 older adults participated in this survey. In the adjusted model, older adults who selected unbalanced foods (odds ratio [OR] = 1.93, 95% confidence interval [CI] = 1.12–3.34), engaged in insufficient physical activity (OR = 5.14, 95% CI = 3.04–8.70), and sat for longer periods of time (OR = 1.98, 95% CI = 1.09–3.59) were more likely to have higher risks of sarcopenia. No significant association was observed for sleep duration.Conclusions: The results of this study highlight that, among health behaviors, an unbalanced food selection (six nutrients), not meeting physical activity recommendations (150 min/week), and a higher sitting time (≥7 h/day) were risk factors for sarcopenia among older adults. Intervention programs for sarcopenia prevention in older adults should focus on promoting balanced food selection, sufficient physical activity, and reduced sitting time.

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists.

Background: For effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient’s functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations. Objective: Gait analysis using smart insole technology can be applied continuously, objectively, and quantitatively, thereby overcoming the shortcomings of other assessment tools. Methods: To confirm the reliability of gait analysis using smart insole technology, normal healthy controls wore insoles in their shoes during the Timed Up and Go (TUG) test. The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test; gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients’ clinical condition, we analyzed the relationships of 22 gait parameters on 4 stroke severity scales. Results: The smart insole gait parameter data were similar to those calculated manually. Among the 18 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The smart insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the sound side in patients showed a markedly longer stance duration. Regarding swing duration, that of the sound side was shorter in patients than controls, whereas that of the hemiplegic side was longer. We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the sound and hemiplegic sides was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score. Conclusions: This study confirmed the feasibility and applicability of the smart insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the smart insole data. Providing an environment where stroke patients can easily measure walking ability helps to maintain chronic functions as well as acute rehabilitation. Trial Registration: UMIN Clinical Trials Registry UMIN000041646, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538