Yu-Rong Mao

Although pharmacological treatments for insomnia remain widely prescribed, their long-term use is constrained by risks of tolerance, dependence, and residual daytime effects. This has prompted growing interest in non-pharmacological interventions that target insomnia’s underlying mechanisms. This narrative review examines five physical factor therapies for insomnia: auditory stimulation, phototherapy, thermotherapy, electrical stimulation, and magnetic stimulation. They are classified according to their primary sites of action into peripheral sensory modulation, central neuromodulation, or systemic autonomic regulation. In each context, research findings about circadian entrainment, thermoregulatory promotion of falling asleep, attenuation of cortical hyperarousal, and restoration of autonomic balance are discussed. Clinical evidence from randomized controlled trials and meta-analyses is critically appraised, with emphasis on therapeutic efficacy, safety, and limitations. Overall, physical factor therapies may constitute promising adjunctive options for selected insomnia phenotypes, but current evidence remains heterogeneous and preliminary for several modalities. Recent advances in portable and home-based technologies support their feasibility, although long-term effectiveness, adherence, and cost-effectiveness remain to be established. Future research should prioritize larger sham-controlled trials, objective sleep and circadian outcomes, standardized protocols, biomarker-guided stratification, and closed-loop intervention systems.

Robotic-assisted rehabilitation has been used to release the labor burden in manual practice for early stroke rehabilitation. However, its broader applicat

Intelligent rehabilitation is the application of technology-driven methods, transforming clinical settings by automating personalized routine processes. Its components include artificial intelligence, robotics, wearable devices, and virtual reality. Sensor integration, digital twins, telemedicine, and wearable devices improve diagnostic accuracy and enable more personalized rehabilitation plans. By leveraging real-time data, these technologies create highly adaptable and personalized treatment plans that adjust as therapy progresses. Intelligent rehabilitation technologies have revolutionized various clinical domains, particularly neurological rehabilitation, musculoskeletal rehabilitation, pediatric rehabilitation, and cardiopulmonary rehabilitation. Implementing smart rehabilitation technologies and developing the healthcare metaverse promise significant advancements in patient care and rehabilitation outcomes. However, several challenges must be addressed to realize the potential of these innovations fully. As innovations in artificial intelligence, virtual environments, and telehealth continue to advance, we can anticipate significant changes in how rehabilitation services are delivered and experienced.

Purpose: This study aimed to translate the English version of the Short Orientation-Memory-Concentration (SOMC) test into a Chinese version, denoted the C-SOMC test, and to investigate the concurrent validity, sensitivity, and specificity of the C-SOMC test against a longer and widely used screening instrument in people with a first cerebral infarction.Methods: An expert group translated the SOMC test into Chinese using a forward–backward procedure. Eighty-six participants (67 men and 19 women, mean age = 59.31 ± 11.57 years) with a first cerebral infarction were enrolled in this study. The validity of the C-SOMC test was determined using the Chinese version of Mini Mental State Examination (C-MMSE) as the comparator. Concurrent validity was determined using Spearman’s rank correlation coefficients. Univariate linear regression was used to analyze items’ abilities to predict the total score on the C-SOMC test and the C-MMSE score. The area under the receiver operating characteristic curve (AUC) was used to demonstrate the sensitivity and specificity of the C-SOMC test at various cut-off values distinguishing cognitive impairment from normal cognition.Results: The total score for the C-SOMC test and the score for item 1 on this test exhibited moderate-to-good correlations with the C-MMSE score, with respective ρ-values of 0.636 and 0.565 (P < 0.001). The scores for each of items 2, 4, 5, 6, and 7 yielded fair correlations with C-MMSE score, with ρ-value from 0.272 to 0.495 (P < 0.05). The total score on the C-SOMC test and the item score were good predictors (adjusted R² = 0.049 to 0.615) of the C-MMSE score, and six items were good predictors (adjusted R² = 0.134 to 0.795) of the total score. The AUC was 0.92 for the C-SOMC test. A cut-off of 17/18 on the C-SOMC test gave optimal performance: correct classification of 75% of participants, with 75% sensitivity and 87.9% specificity.Conclusion: The C-SOMC test demonstrated good concurrent validity, sensitivity and specificity in a sample of people with a first cerebral infarction, demonstrating that it could be used to screen for cognitive impairment in stroke patients.

Introduction: This study was conducted to evaluate whether a non-immersive virtual reality (VR)-based intervention can enhance lower extremity movement in patients with cerebral infarction and whether it has greater short-term and long-term effectiveness than conventional therapies (CTs).Materials and methods: This was a single-blinded, randomized clinical controlled trial. Forty-four patients with subacute cerebral infarction were randomly allocated to the VR or CT group. All intervention sessions were delivered in the inpatient unit for 3 weeks. Outcomes were measured before (baseline) and after the interventions and at 3-month, 6-month and 1-year follow-ups. The outcomes included clinical assessments of movement and balance function using the Fugl–Meyer Assessment of Lower Extremity (FMA-LE) and Berg Balance Scale (BBS), and gait parameters in the sagittal plane.Results: In the VR group, the walking speed after intervention, at 3-month, 6-month, and 1-year follow-ups were significantly greater than baseline (p= 0.01, p= 0.006, 0.002, p= p= 0.03, p= 0.02, 0.004 and p= 0.04).Conclusion: The effectiveness of the non-immersive VR-based intervention in our study was observed after the intervention and at the follow-ups, but it was not significantly different from that of CTs. In sum, our results suggest that non-immersive VR-based interventions may thus be a valuable addition to conventional physical therapies to enhance treatment efficacy.Clinical trial registration: http://www.chictr.org.cn/showproj.aspx?proj=10541, ChiCTR-IOC-15006064.

Background: Stroke is among the leading causes of long-term disability worldwide. Motor impairments after stroke not only impact the individuals quality of life but also lay substantial burdens on the society. Motor planning is a key component of cognitive function that impacts motor control. Hand movements such as grasping or reaching to grasp require the application of correct force and the coordination of multiple limb segments. Successful completion of hand motor task requires a certain degree of cognitive function to anticipate the requirement of the task. Cognitive function may thus be a confounding factor to rehabilitation outcomes. Objective: This study aims to explore the impact of cognitive function on functional outcomes in people with subacute stroke after VR intervention. Methods: Patients with stroke were first stratified into cognitively normal (CN) and cognitively impaired (CI), followed by allocation to the VR or control group (CG). Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Barthel Index (BI), and Instrumental Activities of Daily Living (IADL) were recorded at baseline, 3 weeks after the intervention, and 3 and 6 months after the intervention. The between-group and within-group differences were assessed by repeated-measures analysis of variance (ANOVA). Results: The between-group comparison indicated that FMA-UE, BI, and IADL (time effect P<.001 for all) scores improved significantly in both groups after the intervention. Repeated-measures ANOVA indicated that FMA-UE, BI, and IADL (time effect P<.001 for all) were significantly different in each subgroup after the intervention. For BI score, the ANOVA results showed obvious interaction effects (treatment × time × cognitive effect, P=.04). Conclusions: VR intervention was as effective as traditional conventional therapy in improving upper limb function regardless of the cognitive functional level. Patients with stroke with impaired cognitive function may gain more improvement in upper limb function and independency in performing activities of daily living after a VR-based intervention. Trial Registration: Chinese Clinical Trial Registry ChiCTR-IOC-15006064; https://tinyurl.com/4c9vkrrn

Background Measures of knee stability by symptoms, physical examination, and imaging do not accurately reflect the condition of knee movement. Therefore, this study aimed to introduce a model for assessing knee stability during walking in patients with knee osteoarthritis (OA). Aims Three dimensional(3D) gait analysis system was used to quantify the gait of patients and display the clinical diagnosis model of knee instability with nomogram to guide clinical diagnosis and treatment. Methods This cross-sectional study performed a 3D gait analysis in 93 participants with knee OA and 40 healthy control subjects. Multiple linear regression analysis investigated the correlation between gait parameters and knee extension/flexion stability. The predicting models were built applied multinomial logistic regression analysis and calibration plot, C-index, decision curve analysis, bootstrapping validation were used to assess the predicting nomograms' clinical usefulness and internal validation. Results Multiple linear regression analysis indicated knee extension stability was correlated with walking speed (β = 0.256, P = 0.006), knee extensor strength (β = −0.196, P = 0.03), static HKA (β = 0.218, P = 0.016), width of the femoral diaphysis (β = −0.282, P = 0.002) and WOMAC score (β = 0.281, P = 0.002); however, knee flexion stability was correlated with walking speed (β = 0.340, P < 0.001), knee flexor strength (β = −0.327, P < 0.001), posterior tibial slope (PTS) (β = 0.291, P < 0.001), knee flexion/extension range of motion (ROM) (β = 0.177, P = 0.018) and HSS score (β = −0.173, P = 0.028). We developed and internally validated a knee instability risk nomogram in patients with knee OA. Conclusions These results indicated that using the 3D motion analysis system is feasible to quantify knee instability. The current prediction models could serve as a reliable tool to quantify the possibility of knee instability in OA patients. Trial registration number (TRN) ChiCTR2100051302; Date of registration: Sep 18, 2021; retrospectively registered.

Background: Total knee arthroplasty (TKA) is the only effective treatment of end-stage knee osteoarthritis (OA). Lower limb neutral alignment has been a criterion to predict prosthesis life; however, there has been recent controversy over this. Some researchers believe that lower limb static alignment does not significantly affect prosthesis life and some researchers have found that dynamic mechanical alignment may affect prosthesis life, which needs to be further studied. Methods: Eighty-seven patients with knee OA were evaluated by a three-dimensional (3D) gait analysis system before TKA and six months after TKA, dynamic mechanical alignment and basic gait parameters were then calculated. Based on the static alignment of the lower limb on the postoperative X-radiographs, they were divided into a neutral alignment group (58 cases), varus alignment group (20 cases), and valgus alignment group (9 cases). Simple linear regression was used to assess the correlation between static and dynamic alignment. One-way analysis of variance (ANOVA) was used to compare the differences in gait parameters between and within groups. Results: Eighty-seven patients were followed up for an average of six months after the operation. There was no significant difference in all gait parameters among the three groups after TKA. There was no correlation found between static alignment and dynamic alignment/knee adduction moment (KAM) after TKA, although patients showed a significant linear correlation before operation. There was a significant linear correlation between dynamic alignment and KAM before and after the operation. Conclusions: Static alignment has no significant effect on postoperative gait function. Static alignment is no longer an effective predictor of the dynamic alignment or KAM six months after TKA, although they are correlated before TKA. The dynamic alignment allows for better prediction of KAM, which may be a risk factor for the life of the prosthesis.

Background: The efficacy of interlimb-coordinated training on gait and upper limb functional improvement remains unclear. The latest published randomized controlled trials have supported the potential benefits of interlimb-coordinated training to enhance gait function. Upper limb functional recovery may also benefit from interlimb-coordinated training since most everyday activities require the coordinated use of both hands to complete a task. This study investigates the efficacy of interlimb-coordinated training on gait and upper limb functional recovery over a short-medium term period. Methods: A total of 226 acute stroke patients will be recruited from four centres over four years. Patients will be randomly allocated to either conventional therapy or conventional therapy plus interlimb-coordinated training. Outcomes will be recorded at baseline, after 2 weeks of intervention, and at 3- and 6-months post-intervention. Gait speed is the primary outcome measure. Secondary outcome measures include Fugl–Meyer Assessment of Motor Recovery, Berg Balance Scale, Timed Up and Go test, Action Research Arm Test, electroencephalography, and magnetic resonance imaging. Conclusion: The results of this trial will provide an in-depth understanding of the efficacy of early interlimb-coordinated intervention on gait and upper functional rehabilitation and how it may relate to the neural plasticity process.

Background: Gait disability affects the daily lives of patients with stroke in both home and community settings. An abnormal foot–ankle position can cause instability on the supporting surface and negatively affect gait. Our research team explored the ability of a portable peroneal nerve-targeting electrical stimulator to improve gait ability by adjusting the foot–ankle position during walking in patients with chronic stroke undergoing home-based rehabilitation. Methods: This was a double-blinded, parallel-group randomized controlled trial. Thirty-one patients with chronic stroke and ankle–foot motor impairment were randomized to receive 3 weeks of gait training, which involved using the transcutaneous peroneal nerve stimulator while walking (tPNS group; n = 16, mean age: 52.25 years), or conventional home and/or community gait training therapy (CT group; n = 15, mean age: 54.8 years). Functional assessments were performed before and after the 3-week intervention. The outcome measures included spatiotemporal gait parameters, three-dimensional kinematic and kinetic data on the ankle-foot joint, and a clinical motor and balance function assessment based on the Fugl–Meyer Assessment of Lower Extremity (FMA-LE) and Berg Balance scales (BBS). Additionally, 16 age-matched healthy adults served as a baseline control of three-dimensional gait data for both trial groups.Results: The FMA-LE and BBS scores improved in both the tPNS groups (p = .004 and .001, respectively) and CT groups (p = .034 and .028, respectively) from before to after training. Participants in the tPNS group exhibited significant differences in spatiotemporal gait parameters, including opposite foot off, double support, stride length, and walking speed, after training (p = .010, .042, .017 and .001, respectively). Additionally, the tPNS group exhibited significant differences in kinematic parameters, such as the ankle angle at the transverse plane (p = .021) and foot progression angle at the frontal plane (p = .009) upon initial contact, and the peak ankle joint angle at the transverse plane (p = .023) and foot progression angle at the frontal and transverse planes (p = .032 and .046, respectively) during gait cycles after 3 weeks of training.Conclusions: Use of a portable tPNS device during walking tasks appeared to improve spatiotemporal gait parameters and ankle and foot angles more effectively than conventional home rehabilitation in patients with chronic stroke. Although guidelines for home-based rehabilitation training services and an increasing variety of market devices are available, no evidence for improvement of motor function and balance was superior to conventional rehabilitation.Trial registration: Chictr, ChiCTR2000040137. Registered 22 November 2020, https://www.chictr.org.cn/showproj.aspx?proj=64424