INTRODUCTION:Variables predicting Alzheimer's disease (AD) are not limited to individual-level risk factors. The purpose of this investigation is to assess multilevel predictors of AD prevalence. METHODS:US county-level datasets incorporating 45 predictor variables were analyzed cross-sectionally using artificial intelligence analytical methods. A Light Gradient-Boosting Machine model was trained to predict county-level AD after which model performance and feature importance were evaluated. RESULTS:The final model retained 20 features and explained 75% (R 2 = 0.75) of the variance in AD prevalence. Racial and ethnic minority status showed the highest importance value (0.848), far exceeding all other features (e.g., poor sleep ranked second with importance value of 0.153). DISCUSSION:This study confirmed upstream factors as being significant predictors of AD prevalence and racial and ethnic minority status as being the most important. From a policy perspective, efforts to reduce population levels of AD prevalence should consider addressing racial and ethnic disparities.

Background: Dual-task (DT) interventions involving simultaneous motor and cognitive task performance may improve balance control, although rarely target reactive balance control, which is a key component of fall resistance. This study examined the feasibility, tolerability, and preliminary effects of a single session of DT perturbation training in older adults with mild cognitive impairment (OAwMCI) compared with cognitively intact older adults (CIOA). Methods: Fifteen OAwMCI (MoCA: 18-24/30) and 15 CIOA (MoCA: >25/30), all aged >55 years and able to walk 10 m independently, participated. Pre- and post-training, participants underwent large-magnitude slip perturbations during standing (single task, ST) and 4 DT conditions: visuomotor target game (TGM), visuomotor tracking (TRK), letter-number sequencing (LNS), and auditory clock test (ACT),. Reactive balance control was quantified using margin of stability (MOS). Cognitive outcomes included correct responses, accuracy, and performance error. Training consisted of 5 blocks of repeated slip perturbations (12 slips/block): 1 ST and 4 DT blocks involving mental math, visual stroop, and visuomotor spatial games. Results: Post-training, MOS improved significantly during ST (p<0.001) and all DT conditions (p<0.05). Both groups had improved MOS during ST and TRK (p<0.001), whereas only CIOA had improved MOS during TGM (p<0.001), LNS (p<0.05), and ACT (p<0.01). For cognitive performance, only TGM error decreased significantly in both groups (p<0.001), with no significant changes in the other tasks. Conclusion: A single session of DT perturbation training appears feasible, well tolerated and may improve reactive balance control in OAwMCI and CIOA. However, immediate cognitive benefits were limited, and improvements were smaller in OAwMCI, suggesting multisession training may be needed.

Muscle fatigue, particularly in the quadriceps, can adversely affect squat mechanics and increase lumbar injury risk. Although robotic ankle-foot orthoses (AFOs) have been studied primarily for walking, their potential to assist squatting remains underexplored. This study developed and evaluated a Human-in-the-Loop optimization framework to personalize robotic AFO assistance during squatting using electromyography (EMG). Seven unimpaired male participants completed a two-day protocol including acclimation, HIL optimization, and validation. Bayesian optimization used rectus femoris EMG on the assisted leg as the cost function to tune descent and ascent assistance parameters, implemented through a stiffness-based control law. Personalized assistance reduced rectus femoris activation by 15.48% - 20.28% relative to the unpowered, no-device, and generic-assistance conditions. Vastus medialis and vastus lateralis also decreased significantly by 7.1% - 12.76% relative to all baseline conditions, while trunk and contralateral muscle activities showed no significant compensatory increases. Metabolic costs were significantly reduced by more than 11% relative to the unpowered and no-device conditions. These findings suggest that EMG-based personalization reduces knee extensor demand and lowers steady-state metabolic cost relative to the unpowered and no-device conditions during squatting.

BACKGROUND:Falls during walking remain a major cause of disability after stroke. Perturbation-based balance training (PBBT) improves reactive stability, but its effects on gait-related neuromuscular coordination and the added value of functional electrical stimulation (FES) are not well established. OBJECTIVES:To determine whether PBBT, performed with or without task-synchronized FES, improves clinical performance, intermuscular coordination during gait, and reactive balance stability in individuals with chronic stroke. METHODS:In this randomized controlled trial, 35 ambulatory individuals ≥ 6 months post-stroke were allocated to PBBT alone (n = 18) or PBBT combined with FES (n = 17). Participants completed eight sessions over four weeks. Outcomes were assessed at baseline, post-intervention, and 3-month follow-up. Clinical measures included the Mini-BESTest, Timed Up and Go (TUG), Fugl-Meyer Assessment-Lower Extremity, and 10-Meter Walk Test. Neuromuscular coordination was quantified using the Peak Activation Interval (PAI) between vastus lateralis and medial gastrocnemius during gait. Reactive balance stability was assessed using center-of-mass (CoM) stability after balance perturbation. Linear mixed-effects models were used for analysis. RESULTS:Significant main effects of Time were observed across clinical outcomes (p < 0.05), with improvements maintained at follow-up. PAI increased from baseline to post-intervention (β = 7.29, p = 0.003), indicating improved intermuscular timing. CoM stability improved from baseline to post-intervention (β = 0.171, p < 0.001) and remained higher at follow-up (p = 0.009). No significant Group × Time interactions were detected (all p > 0.05). CONCLUSIONS:PBBT improved mobility, gait neuromuscularcoordination, and reactive balance stability in persons with stroke. Theaddition of FES did not provide additional group-level benefit. CLINICALTRIALS.GOV:NCT06237972.

Research Objectives To investigate the effect of unilateral quadriceps fatigue of the unperturbed limb (right) on falls and reactive measures, to an unexpected overground trip (left) during walking in healthy young adults. Design Quasi-experimental-control study Setting Gait laboratory with 3-D motion system in a research institution Participants 40 healthy young adults: Fatigue group (N=20; 25±5 yrs; 9 males; 72.6±14 kg) and Control group (N=20; 26±5 yrs; 8 males; 70±10 kg). Interventions For right unilateral quadriceps fatigue, participants performed seated knee extensions at a load of 50% max. voluntary contraction and 60°/s on a Biodex until torque fell to 50% (Bersotti 2019). Immediately after the fatigue, participants were made to walk with joint markers at their self-selected speed on a 7m overground walkway secured in a ceiling-mounted safety harness system for < 10 lt; 10 minutes and then exposed to a novel, unexpected obstacle-induced left-foot trip (height -11cm) during mid-swing. The Control group experienced a single trip without undergoing fatigue. Main Outcome Measures Falls were identified with a load cell attached to a harness recording >30% bodyweight with video confirmation. Reactive (after obstacle hit) measures like the center of mass position (COMx) and velocity (COMv) were recorded at multiple time points of touchdown (TD) for tripping-foot and recovery-foot (left/right). Peak trunk flexion and forward trunk velocity from obstacle hit to recovery-foot TD were recorded. Comparisons between groups were made using chi-square and independent samples t-tests. Results The Fatigue group experienced significantly more falls than the Control group (40% vs. 0%; p=0.002).The Fatigue group also showed greater COMx at tripping-foot TD (p=0.02) and recovery-foot TD (p=0.01), higher COMv at tripping-foot TD (p=0.02), increased peak trunk flexion (p=0.013), and higher forward trunk velocity (p=0.008) compared to the Control group. Conclusions Right unilateral quadriceps fatigue compromises neuromuscular control, leading to reduced extensor torque and decreased knee stability by increasing anterior tibial translation. This instability in late swing following trip is critical, as the unperturbed limb alone holds the COMPOSITION until the left tripping foot lands. The Fatigue group showed significantly greater forward COM displacement and velocity before the tripping foot's touchdown, indicating ineffective control of body momentum. At recovery foot touchdown, higher COM displacement persisted due to increased trunk flexion and velocity, making it difficult to regain stability, and raising fall risk (40%) in the fatigue group. This preliminary evidence underscores the need to identify unilateral quadriceps fatigue, which is essential to prevent tripping-related falls and reduce injury risk.

Purpose: Vestibular dysfunction (VD) is associated with fall risk and is more common in older adults with mild cognitive impairment (OAwMCI) than cognitively intact older adults (CIOA). However, it is unknown if VD contributes to the reactive balance deficits observed in OAwMCI (e.g., higher fall rate, lower reactive center of mass stability). Methods: This study examined how VD affected reactive stepping kinematics and neuromuscular control in OAwMCI ( n = 28) and CIOA ( n = 35) when exposed to a large anterior support surface perturbation. VD was identified by a positive score on ≥2/3 clinical tests (head thrust, vestibular ocular reflex slow, vestibular ocular reflex cancelation), and was more common in OAwMCI (46%) than CIOA (23%) ( P < 0.05). Results: Only OAwMCI with VD showed a higher fall rate, lower reactive center of mass stability, delayed step initiation, and longer onset latencies of the bilateral medial gastrocnemius than those without VD (significant group × VD interaction, P < 0.05). However, both OAwMCI and CIOA with VD showed longer step execution, reduced activation amplitude of the stepping limb hamstrings and tibialis anterior during step initiation and execution (relative to peak activation), and longer burst durations of the stepping limb quadriceps than those without VD (significant main effect of VD, P < 0.05). Conclusions: This suggests that VD may affect reactive balance control in OAwMCI more than CIOA by interfering with reactive step triggering/initiation, although it may affect reactive step execution in both CIOA and OAwMCI. Vestibular inputs may contribute to both perturbation detection/response triggering and motor execution, and OAwMCI may have reduced capacity to compensate for unreliable vestibular sensory inputs due to impaired sensory reweighting. Comprehensive fall risk screenings could consider the combination of both cognitive decline and VD.

Older adults with mild cognitive impairment (OAwMCI) fall 2 × more than cognitively intact older adults (CIOA), possibly due to impaired reactive stepping. However, most studies in OAwMCI have focused on slip-like perturbations (backward loss of balance), rather than trip-like perturbations (forward loss of balance). This study examined reactive stepping strategies following a novel support surface perturbation during treadmill walking, and compared fall rate, margin of stability (MOS), step length, and trunk angle between OAwMCI and CIOA during unperturbed walking (i.e., pre-trip) and recovery stepping (i.e., post-trip). As an exploratory analysis, muscle synergies were also extracted from bilateral lower limb EMG data from perturbation onset to recovery touchdown. After trip onset, most participants took a lowering-like step with the swing limb, followed by a forward recovery step with the contralateral (43

Background: Our long-term goal is to determine the optimal volume of reactive balance training (RBT) in people with sub-acute stroke. This study aims to inform the design of a larger trial to address this long-term goal. Trial design: Assessor-blinded three-arm pilot randomized controlled trial. Methods: Participants (n=36) with sub-acute stroke were randomly allocated to one of three groups: 1, 3, or 6 RBT sessions. All sessions were delivered over 2-3 weeks. Feasibility outcomes included recruitment and retention rates, intervention fidelity and adherence, and completeness of outcome assessments. Participants reported falls and physical activity for 6 months post-training; falls data were used to estimate sample size for a future trial. Functional balance, balance confidence, and balance reactions were assessed at: 1) study enrolment; 2) post-training; and 3) 6 months post-training to estimate effect sizes for a future trial. Results: Thirty-five participants initiated training and 34 contributed post‑training assessment data. Intervention adherence was high: participants completed 1.0, 2.9, and 5.7 RBT sessions on average in the 1-, 3- and 6-session, respectively. Functional and questionnaire outcomes were ≥80% complete at most time points, although follow‑up questionnaires at 2 and 4 months met only 74% completeness. Falls monitoring data were available for 30 participants, with 15 falls reported. Estimated sample sizes for a definitive trial using falls as the primary outcome (n=408-782) were not feasible for a single site; alternative primary outcomes (stability following balance perturbations) produced more feasible sample size estimates (n=30-72). Minor adverse events were reported by 1, 2, and 6 participants in the 1-, 3- and 6-session groups, respectively. Conclusions: The modified intervention and assessment procedures were feasible; however, a definitive single‑site trial using falls as the primary outcome is not feasible. Stability-based outcomes may support a more feasible future trial. Trial registration: clinicaltrials.gov, NCT04219696

[Purpose] This study reports: (Aim 1) a feasibility study of a distributed supervision model (DSG) within a smartphone-guided home stroke rehabilitation program incorporating functional electrical stimulation (FES); and (Aim 2) a retrospective cohort comparison of DSG outcomes against a previously published front-loaded supervision group (FSG). [Participants and Methods] Thirty-one adults with chronic hemiparetic stroke (onset >6 months) completed a 6-week multicomponent home exercise program (3 sessions/week, 1 hour/session) incorporating gait, strength, and balance training with FES delivered via smartphone app. FSG (n=12) received 2 weeks of supervised onboarding followed by 4 weeks of independent home training. DSG (n=19) received one supervised and two independent sessions weekly. Pre- and post-assessments included the 10-Meter Walk Test, Mini-BESTest, Berg Balance Scale, Timed Up and Go, and 30-Second Sit-to-Stand Test. [Results] No adverse events were reported. Both groups demonstrated high adherence (DSG: 90.3 ± 10.2%; FSG: 87.3 ± 8.7%) and significant within-group improvements across all outcomes, exceeding minimal clinically important differences. Between-group comparisons showed significantly greater improvements in the DSG on the 30STS (Welch's t, p<0.001, d=1.57, achieved power=0.98) and TUG (p=0.020, d=0.74, achieved power=0.48); contrasts for BBS, Mini-BESTest, and 10MWT were non-significant with low achieved power (0.05-0.21) and are reported as inconclusive. All findings should be interpreted as preliminary given the retrospective, non-randomized design. [Conclusion] Both supervision models demonstrated high feasibility, safety, and clinically meaningful functional gains. Supervision timing may influence the magnitude of functional gains and warrants investigation in future randomized trials.

Outcomes associated with the coronavirus disease 2019 (COVID-19) pandemic in the United States (U.S.), particularly in terms of infection rates and deaths due to viral infection, has been and continues to be widely discussed. The current study utilized several U.S. county-level datasets representing over 30 predictive variables of the ecological framework of health, a model that includes measures of culture, politics, policy, socioeconomics, lifestyle behaviors, and both chronic disease risk factors and diagnoses. A non-linear artificial intelligence statistical approach was used to assess the ability of these variables (i.e., features) to predict U.S. county-level COVID-19 mortality and case rates. For both COVID-19 deaths and cases per 100,000 persons, the highest R² was achieved using 30 features, representing all areas of the ecological framework for health. Measures of vaccine compliance, hesitancy and concern over a difficult rollout were also retained in the model. The U.S. faces numerous health challenges. Unhealthy lifestyle behaviors, chronic disease risk factors, and diagnoses of chronic conditions have reached crisis levels with few improvements in sight. This is further being compounded by an unprecedented culture clash and politicization of health-related decisions and outcomes. These issues may have been simmering for some time based upon the regional disparities in health characteristics and outcomes and their associations with distinct cultural and political preferences. The COVID-19 pandemic appears to have forcefully brought these issues to the surface.

Highly accurate, data-efficient, and real-time detection of human motion intention is essential for the effective control of assistive and rehabilitation robots in post-stroke recovery. However, existing approaches focused on healthy participants and often require large amounts of subject-specific data, limiting their clinical applicability. To address these challenges, we propose GaitNet, a novel transfer learning-enhanced dual branch CNN-GRU framework designed to deliver robust and data-efficient motion intention detection for both healthy and post-stroke participants. GaitNet combines convolutional layers for spatial feature learning, cross-attention for latent space fusion, and gated recurrent units (GRUs) for temporal modelling, while leveraging transfer learning to reduce reliance on extensive subject-specific data. In evaluations, using full amount of data, GaitNet achieved an accuracy of 99.29%±0.17 on healthy participants and 98.96%±0.47 on post-stroke participants, outperforming baseline deep learning and classical models. In transfer learning, GaitNet was pre-trained on healthy participants and fine-tuned on post-stroke data. Remarkably, under joint supervised pretraining (JSP), it maintained > 98% accuracy, precision, recall, and F1-score with only 45% of the training set on post-stroke participants (9 repetitions per motion), reducing the data requirement by 65% while preserving high performance. Furthermore, with an inference time of 27.46 ms per input batch, GaitNet operates well within the real-time constraints reported in related assistive robotics studies and was successfully deployed in a closed-loop robotic control setting with healthy participants, confirming its suitability for real-time rehabilitation scenarios. These results establish GaitNet as a practical and scalable solution for highly accurate, data-efficient detection of motion intention in post-stroke participants.

Introduction:Physical inactivity continues to be a leading health crisis in the U.S. There are clear differences in physical inactivity prevalence across U.S. regions with unique distinctions and drivers. This study reports on improvements in self-reported physical activity in a school-based, K-8 health and wellness program in an underserved community in Chicago. In addition, the study also examines how the social vulnerability of the participants in the program compares with state and national standards. This study utilized a longitudinal cohort design. Methods:Seventy-two students participated in the Health and Wellness Academy, with a mean age of 10.43±2.18 years. Social vulnerability was higher in neighborhoods where students participating in the Health and Wellness Academy lived than Illinois overall and the national average. Among these participants, 58.3% were female, 54 of 72 (75%) were Hispanic, and the remaining 18 (25%) were Black. Each Health and Wellness Academy session had a portion of time dedicated to physical activity. Results:Results indicated that physical activity levels increased along with time points. Mixed linear model regression results further revealed a significant increase for time effects on physical activity (p<0.001). Conclusions:Having a consistent and sustained intervention allows youth to be exposed to a variety of physical activity options. These findings indicate that the Health and Wellness Academy's tailored model allows for youth to find a physical activity that is meaningful and relevant, thus implementing it into their daily lives.

Gait disorders are commonly observed in older adults, who frequently experience various issues related to walking. Additionally, researchers and clinicians extensively investigate mobility related to gait in typically and atypically developing children, athletes, and individuals with orthopedic and neurological disorders. Effective gait analysis enables the understanding of the causal mechanisms of mobility and balance control of patients, the development of tailored treatment plans to improve mobility, the reduction of fall risk, and the tracking of rehabilitation progress. However, analyzing gait data is a complex task due to the multivariate nature of the data, the large volume of information to be interpreted, and the technical skills required. Existing tools for gait analysis are often limited to specific patient groups (e.g., cerebral palsy), only handle a specific subset of tasks in the entire workflow, and are not openly accessible. To address these shortcomings, we conducted a requirements assessment with gait practitioners (e.g., researchers, clinicians) via surveys and identified key components of the workflow, including (1) data processing and (2) data analysis and visualization. Based on the findings, we designed VIGMA, an open-access visual analytics framework integrated with computational notebooks and a Python library, to meet the identified requirements. Notably, the framework supports analytical capabilities for assessing disease progression and for comparing multiple patient groups. We validated the framework through usage scenarios with experts specializing in gait and mobility rehabilitation.

Older adults with mild cognitive impairment (OAwMCI) demonstrate reactive balance deficits (impaired responses to external perturbations) compared to cognitively intact older adults (CIOA), which are exacerbated while performing a cognitive task (i.e., dual-tasking). However, it is unknown if these cognitive-motor deficits (which could significantly increase fall risk) can even be perceived by OAwMCI. Thus, this study examined if objective performance during dual-task reactive balance control (cognitive errors, reactive center of mass (COM) stability) was associated with subjective workload in OAwMCI and CIOA. 34 OAwMCI (Montreal Cognitive Assessment (MoCA): 18-25) and 35 CIOA (MoCA ≥26) were exposed to a support surface perturbation while performing a visuomotor “Target” task, which involved rotating their head to catch virtual objects. This task was also completed while seated (single-task). Participants rated their perceived workload (0-100) on the NASA-Task Load Index (NASA-TLX) in six domains (mental, physical, temporal, performance, effort, frustration). OAwMCI reported lower mental demand, effort, and frustration than CIOA in single and dual-task (p < 0.05), although had higher cognitive errors and lower reactive COM stability (p < 0.05). Both groups reported higher workload in dual vs. single-task (p < 0.05). NASA-TLX scores were not correlated with objective performance in OAwMCI (p > 0.05), although were significantly correlated with cognitive errors and reactive COM stability in CIOA (Pearson’s r: 0.3-0.5). These results suggest that OAwMCI may not be able to accurately perceive the cognitive-motor demands of challenging conditions. This impaired perception could affect the execution or scaling of reactive balance responses and contribute to increased fall risk, especially in dual task conditions.

Older adults with mild cognitive impairment (OAwMCI) demonstrate higher cognitive-motor interference (CMI) than cognitively intact older adults (CIOA) during dual tasking. However, studies have rarely examined how dual tasking affects reactive balance control in OAwMCI, or the effect of different cognitive task domains. This study compared how four cognitive tasks affected CMI during reactive balance control in OAwMCI vs. CIOA. In this study, 38 OAwMCI [Montreal Cognitive Assessment (MoCA): 18-25] and 38 CIOA (MoCA ≥ 26) were included and exposed to anterior support surface perturbations in single task and while performing four cognitive tasks: two visuomotor tasks (Target, Track), auditory clock test (ACT), and letter number sequencing (LNS). Cognitive tasks were also completed during unperturbed standing. In both single and dual task conditions, OAwMCI had a higher fall rate and lower reactive center of mass (COM) stability than CIOA. Reactive balance performance deteriorated in both groups while performing Target and Track, although was not affected by ACT or LNS. Cognitive performance was lower in dual vs. single task on the Target, Track, and LNS for both groups, although OAwMCI had higher cognitive costs than CIOA. These findings suggest that dual tasking could increase fall risk in both OAwMCI and CIOA, although visuomotor tasks induced greater CMI than executive function/working memory tasks, suggesting greater sharing of resources with reactive balance control. Furthermore, OAwMCI could experience higher CMI due to damage in sensorimotor areas involved in triggering/executing reactive balance responses, along with multidomain cognitive decline. Comprehensive dual task assessments could identify domain-specific cognitive decline in OAwMCI.NEW & NOTEWORTHY Although OAwMCI have higher CMI than CIOA during volitional balance tasks, it is unclear how dual tasking involving different cognitive domains affects reactive balance control in OAwMCI. This study showed that dual tasking could impair reactive balance responses in both CIOA and OAwMCI, although OAwMCI experienced greater performance deteriorations in dual vs. single task conditions. Furthermore, visuomotor tasks induced higher CMI than executive function/working memory tasks, suggesting greater sharing of resources with reactive balance control.

One emerging method in home stroke rehabilitation is digital technology. However, existing approaches typically target one domain (e.g., upper limb). Moreover, existing interventions do not cater to older adults with stroke (OAwS), especially those with high motor impairment, who require adjunct therapeutic agents to independently perform challenging exercises. We examined the feasibility of Smartphone-based Exercise Training after Stroke (SETS) with Functional Electrical Stimulation (FES). A total of 12 participants (67 ± 5 years) with stroke (onset > 6 months) exhibiting moderate-to-high motor impairment (Chedoke McMaster Leg ≤ 4/7) underwent 6 weeks of multicomponent (gait, functional strength, dynamic balance) training integrated with FES to paretic lower limb muscles. Primary measures included safety and adherence. Secondary measures included motivation, acceptability and attitude, usability, and clinical measures of gait and balance function like the 10-Meter Walk Test and Mini-BESTest. Participants reported no adverse events and moderate-to-high adherence (84.17 ± 11.24%) and improvement (up to 40%) in motivation, acceptability, and attitude and system usability. Participants also showed pre-post improvements in all measures of gait and balance function (p < 0.05). Integrating SETS and FES is feasible and yields short-term gains in gait and balance function among OAwS. Future studies could validate our findings by examining its efficacy with control groups to identify the differential effects of SETS and FES.

Accurate detection of gait events in older adults, particularly during perturbed walking, is essential for evaluating balance control and fall risk. Traditional force plate-based methods often face limitations in perturbed walking scenarios due to the difficulty in landing cleanly on the force plates. Subsequently, previous studies have not addressed gait event automatic detection methods for perturbed walking. This study introduces an automated gait event detection method using a bidirectional gated recurrent unit (Bi-GRU) model, leveraging ground reaction force, joint angles, and marker data, for both regular and perturbed walking scenarios from 307 healthy older adults. Our marker-based model achieved over 97% accuracy with a mean error of less than 14 ms in detecting touchdown (TD) and liftoff (LO) events for both walking scenarios. The results highlight the efficacy of kinematic approaches, demonstrating their potential in gait event detection for clinical settings. When integrated with wearable sensors or computer vision techniques, these methods enable real-time, precise monitoring of gait patterns, which is helpful for applying personalized programs for fall prevention. This work takes a significant step forward in automated gait analysis for perturbed walking, offering a reliable method for evaluating gait patterns, balance control, and fall risk in clinical settings.

BACKGROUND:A single session of perturbation-based training (PBT) reduces fall-risk and enhances reactive balance control in people with stroke (PwS). However, its long-term effect on clinical outcomes remains unclear. This study examined the retention effects of a single session of overground walk-PBT on clinical measures of body structure and function, activity limitation, and participation restriction in PwS. METHODS:Forty-eight PwS were randomized to training (n = 25) or control (n = 23) groups. Participants completed baseline, 6- and 12-month sessions, including reactive balance and clinical assessments. The training group underwent overground walk-PBT, while the control group completed unperturbed walking alone. Outcomes were assessed using the International Classification of Functioning, Disability, and Health (ICF) framework: body structure and function (Modified Rankin Scale, Activities-specific Balance Confidence - ABC), activity limitation (Berg Balance Scale, Timed Up and Go - TUG, 10-Meter Walk Test - 10MWT, 6-Minute Walk Test), and participation restriction (Community Integration Questionnaire - CIQ). A Two-way ANOVA examined group × time interactions on all outcomes followed by post-hoc comparisons. RESULTS:Significant group × time interactions were observed for ABC, TUG, 10MWT, and CIQ (p < 0.05). The training group demonstrated improvements from baseline to 6 months (p < 0.02), with no differences between the 6- and 12-month sessions (except improvements in CIQ) (p > 0.02). The control group showed no improvements (p > 0.02) and demonstrated a reduction in balance confidence from baseline to 6-months (p < 0.02). CONCLUSION:A single session of overground walk-PBT showed long-term improvements in outcomes across all ICF domains, highlighting its clinical utility as an effective rehabilitation strategy for PwS.

Unhealthy lifestyle behaviors are a doorway to downstream health consequences characterized by the following: 1) poor quality of life and diminished mobility; 2) increased likelihood of chronic disease risk factors and diagnoses; and, ultimately, 3) a shorter lifespan and healthspan. The aim of the current study is to assess if an ecological framework can predict U.S. lifespan via the use of artificial intelligence. The current study utilized several U.S. county-level datasets representing the predictive variables of the ecologic framework. A non-linear artificial intelligence statistical approach was used to assess the ability of these variables to predict life expectancy, death rate, and years of life lost. The R² values demonstrated that the performance of Extra trees models was different across the three outcomes, however, death rate always exhibited the highest R² for each feature number, indicating superior model accuracy for this outcome. Generally, an increase in the number of features led to improved model performance. Variables from all factors included in the proposed ecological framework were retained in the final predictive models. There is a need to understand why individuals/families/community, connected by shared cultural beliefs, decide to make one lifestyle behavior decision over another.

Objective(s) (1) To compile evidence on the effects of neuromuscular electrical stimulation (NMES) or functional electrical stimulation (FES), or both, on parameters of muscle strength among middle-age and older adults with or without systemic pathologies. (2) To determine commonly used NMES/FES stimulation parameters. Data Sources Electronic databases, including PubMed, Cochrane Library, and Scopus, were searched from year 2017 to 2023. Study Selection Studies were included if they (1) included middle-age or older adults (>45y); (2) were randomized controlled trials (RCTs); (3) used NMES or FES as a training tool; (4) examined ≥1 outcome of muscle strength; (5) reported ≥1 NMES/FES stimulation parameter (frequency or duration or amplitude). Studies were excluded if they (1) were not in English; (2) included adults with neurologic or orthopedic conditions. Data Extraction Two reviewers extracted the study design, demographics, intervention/control conditions, outcomes, and results. The quality of RCTs (risk of bias) was assessed using the PEDro scale. Data Synthesis Nine RCTs (PEDRo scores 5-9, fair-good) with a pooled sample of 335 participants aged 45-70 years were included. Two of 9 studies included adults undergoing hemodialysis, 3 studies included healthy older adults, others included adults with liver transplant, obstructive pulmonary disease, cancer, post-COVID-19. Four studies compared the effect of NMES/FES with standard care (eg, resistance training), 4 studies compared different stimulation parameters of NMES/FES (eg, frequency or muscle group), whereas 1 study compared NMES/FES with sham stimulation. Five studies delivered NMES/FES for 12 weeks, others delivered for 4-8 weeks. The most frequently assessed outcome was isometric muscle strength (8 studies), whereas other functional outcomes were 30-second chair stand and timed Up and Go test (2 studies). Eight of 9 studies showed greater improvements in outcomes of muscle strength with NMES/FES (most used frequency, 50Hz) than control conditions. One study did not show group differences in outcomes between 50 Hz and 75 Hz frequencies. The stimulation parameters varied from 50-90 Hz for frequency, 250-400 μs for duration, and 10-40 mA for intensity, with quadriceps being the most targeted group (5 studies), Conclusions NMES/FES seems to be a more effective agent compared with standard care (eg, resistance training) for improving muscle strength among middle-aged and older adults. Second, the included studies used a wide range of stimulation parameters without reporting scientific rationale for selection. There is a need to standardize stimulation parameters for inducing optimal NMES/FES effects. Disclosures none.