Mobility of Older Adults: Gait Quality Measures are associated with Life-Space Assessment Scores

Individual and Neighborhood Characteristics of Walking Activity in People Living With Dementia: A Proof of Concept for Quantitative Spatial Analysis

BACKGROUND/OBJECTIVES

Creating dementia-friendly neighborhoods is crucial for enhancing outdoor walking activity and maintaining social participation among people living with dementia (PLWD). This study utilizes GPS and geographic information system technologies to conduct a quantitative spatial analysis, revealing how individual and neighborhood characteristics are associated with PLWD's walking activity characteristics.

METHODS

Twenty-five participants from Metro Vancouver had their regular walking routes (RWR) from home to neighborhood destinations recorded using GPS technology. Spatial analysis tools and existing survey data were utilized to construct the research geodatabase. Nonparametric tests (Spearman's rank correlation, Kendall's tau, and Mann-Whitney) and parametric tests (Pearson correlation and point biserial) assessed associations between independent variables, including sociodemographic characteristics of participants (e.g., age and health) and their neighborhoods (e.g., age structure and language barriers), and built environment features (e.g., land use diversity), with two dependent variables: length of RWR and walking time to regular destination within the 20-min walkshed.

RESULTS

Longer RWR and increased walking time to regular destination within the 20-min walkshed are associated with fewer physical health limitations, gentler terrain, proximity to green spaces, and bus stops. In addition, higher land use diversity, proximity to secondary streets, integrated sidewalks, higher number of benches and intersections, and a slight street network curvature showed positive associations with RWR length and walking time to regular destination within the 20-min walkshed.

CONCLUSION

GPS and geographic information system technologies provide a unique quantitative method for understanding mobility patterns among PLWD. While limited by participant numbers, this exploratory study provides directions for future investigations. Significance/Implications: This study offers insights into designing dementia-friendly neighborhoods that support social engagement and physical activity among PLWD.

The Life-Space Mobility of Community-Dwelling Older Adults is Associated With Personality Traits

Life-space mobility (LSM) in older adults is influenced by physical, cognitive, and psychological states. However, the relationship between LSM and personality traits remains unclear. Thus, our cross-sectional study investigated this correlation, which included 144 participants aged ≥60 years. LSM was assessed using the life-space assessment (LSA), and personality traits were evaluated using the Japanese version of the Ten-Item Personality Inventory (TIPI-J). Physical data were also collected. Univariate analyses revealed that among young-older adults, extroversion in the TIPI-J showed a significant association with LSA scores in addition to handgrip strength. Among old-older adults, openness to experience in the TIPI-J demonstrated a significant association with LSA scores in addition to quadriceps strength. This study revealed correlations between personality traits (extroversion and openness to experience) and LSM, in addition to physical function. Considering older adults' personality traits is crucial for designing support and interventions to maintain and expand LSM.

Discriminative ability, responsiveness, and interpretability of smoothness index of gait in people with multiple sclerosis

Introduction

Gait impairments are common in People with Multiple Sclerosis (PwMS). Several studies have examined the clinometric properties of Inertial Measurement Units (IMUs), with LDLJa identified as a robust metric for gait smoothness. However, its responsiveness and interpretability have not been explored.

Methods

This cross-sectional study at IRCCS Santa Lucia Hospital enrolled 44 PwMS (age: 28-71; EDSS: 0-6) and 43 age- and gait-speed-matched healthy participants (HP). Two physiotherapists conducted assessments with five synchronized IMUs during a 10-meter walk at participants' preferred speed. Data were collected at baseline (T0) and after 4 weeks of training (T1).

Results

Significant differences in log dimensionless jerk (LDLJa) were found between PwMS and HP in the AP (p < 0.001, d = 0.63), ML (p < 0.001, d = 1.08), and CC (p = 0.03, d = 0.68) directions. PwMS had lower LDLJaAP values (< -4.88) and LDLJaML values (< -5.40) with probabilities of 63% and 76%, respectively. ΔLDLJaML demonstrated good responsiveness to rehabilitation (AUC ~0.80), with improvements >4.02% representing the optimal MCID for clinical improvement in MiniBesTest.

Conclusion

Lower LDLJa values in the AP and ML directions characterize gait smoothness impairment in PwMS. LDLJa in the ML direction is responsive to balance-focused rehabilitation, highlighting its potential for tracking gait disorders and rehabilitation progress.

A clinical application of gait quality patterns in osteoarthritis

AIM

To investigate whether a smartphone-based gait analysis tool can reliably output gait quality parameters that can be cross-analyzed to establish individual & disease-based changes in gait quality patterns.

METHODS

A cross-sectional study made up of a 48-patients undergoing disability certification at the "Dr. José Castro Villagrana" or the "Dr. David Fragoso Lizalde" Health Centers in Mexico City, Mexico. Their sensorimotor performance was evaluated through an in-house smartphone/IMU based digital tool. Gait was analyzed by means of frequency analysis of the acceleration of the body mass measured at the sternum. A composite gait quality score was determined through principal component analysis based primarily on the explainability and uniformity of gait. Quality independence against demographic variables (age & weight) was tested through ANCOVA. The association between gait quality and gait parameters was analyzed by using multiple linear regression.

RESULTS

A multiple regression model developed with a limited set of gait quality parameters successfully predicted gait smoothness with a 97.05 % accuracy with a mean square error of 0.085 between predicted and actual quality scores. The model demonstrates different predictive capacities across disease groups, with Osteoarthrosis + Osteoporosis having the highest R2 at 0.98 (p < 0.001) and Coxarthrosis having the lowest explained R2 at 0.79 (p < 0.001).

CONCLUSIONS

The assessment of gait quality, in family medicine, with low-cost digital tools is an area of opportunity yet to be explored. This tool can potentially disrupt the current disability workflow between primary and specialty care to have an objective method of assessing gait within a clinical consult. Individual patient-level benchmarking can give us insights into the patient's disease status, develop practical intervention strategies, and control the cost and quality of medical care by predicting an individualized course of disability or rehabilitation. Further studies are needed to validate digital gait assessments as clinical decision support tools for day-to-day clinical operations. MESH: Gait Analysis, Smartphone, Primary Health Care, Osteoarthrosis.

Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review

Spatiotemporal parameters such as gait velocity and stride length are simple indicators of functional status and can be used to predict major adverse outcomes in older adults. A smartphone can be used for gait analysis by providing spatiotemporal parameters useful for improving the diagnosis and rehabilitation processes in frail people. The aim of this study was to review articles published in the last 20 years (from 2004 to 2024) concerning the application of smartphones to assess the spatiotemporal parameters of gait in older adults. This systematic review was performed in line with Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA), and original articles were identified by searching seven electronic databases: SciVerse (ScienceDirect), Excerpta Medica Database (EMBASE), Medline, Scopus, PubMed, Web of Science and the Cochrane Library. Studies were rigorously screened using the inclusion criteria of smartphones and mobile apps, older adults and spatiotemporal gait parameters, and results were narratively synthesized. Seventy-three articles were initially identified while searching the scientific literature regarding this topic. Eleven articles were selected and included in this review. Analysis of these studies covered information about gait assessment using mobile apps recorded in 723 older adults and 164 control cases. Analysis of data related to the application of smartphones to assess spatiotemporal parameters of gait in older adults showed moderate-to-excellent test-retest reliability and validity (ICCs around 0.9) of gait speed, the most common parameter reported. Additionally, gait speeds recorded with mobile apps showed excellent agreement when compared to gold standard systems. Smartphones and mobile apps are useful, non-invasive, low-cost and objective tools that are being extensively used to perform gait analysis in older adults. Smartphones and mobile apps can reliably identify spatiotemporal parameters related to adverse outcomes, such as a slow gait speed, as predictors and outcomes in clinical practice and research involving older adults.

Efficacy of a Single-Bout of Auditory Feedback Training on Gait Performance and Kinematics in Healthy Young Adults

This study investigated the immediate effects of auditory feedback training on gait performance and kinematics in 19 healthy young adults, focusing on bilateral changes, despite unilateral training. Baseline and post-training kinematic measurements, as well as the feedback training were performed on a treadmill with a constant velocity. Significant improvements were seen in step length (trained: 590.7 mm to 611.1 mm, 95%CI [7.609, 24.373]; untrained: 591.1 mm to 628.7 mm, 95%CI [10.698, 30.835]), toe clearance (trained: 13.9 mm to 16.5 mm, 95%CI [1.284, 3.503]; untrained: 11.8 mm to 13.7 mm, 95%CI [1.763, 3.612]), ankle dorsiflexion angle at terminal stance (trained: 8.3 deg to 10.5 deg, 95%CI [1.092, 3.319]; untrained: 9.2 deg to 12.0 deg, 95%CI [1.676, 3.573]), hip flexion angular velocity, (trained: -126.5 deg/s to -131.0 deg/s, 95%CI [-9.054, -2.623]; untrained: -130.2 deg/s to -135.3 deg/s, 95%CI [-10.536, -1.675]), ankle angular velocity at terminal stance (trained: -344.7 deg/s to -359.1 deg/s, 95%CI [-47.540, -14.924]; untrained: -340.3 deg/s to -376.9 deg/s, 95%CI [-37.280, -13.166s]), and gastrocnemius EMG activity (trained: 0.60 to 0.66, 95%CI [0.014, 0.258]; untrained: 0.55 to 0.65, 95%CI [0.049, 0.214]). These findings demonstrate the efficacy of auditory feedback training in enhancing key gait parameters, highlighting the bilateral benefits from unilateral training.

Fear of falling in community-dwelling older adults: What their gait acceleration pattern reveals

BACKGROUND

Fear of Falling (FOF) is common among community-dwelling older adults and is associated with increased fall-risk, reduced activity, and gait modifications.

OBJECTIVE

In this cross-sectional study, we examined the relationships between FOF and gait quality.

METHODS

Older adults (N=232; age 77±6; 65 % females) reported FOF by a single yes/no question. Gait quality was quantified as (1) harmonic ratio (smoothness) and other time-frequency spatiotemporal variables from triaxial accelerometry (Vertical-V, Mediolateral-ML, Anterior-Posterior -AP) during six-minute walk; (2) gait speed, step-time CoV (variability), and walk-ratio (step-length/cadence) on a 4-m instrumented walkway. Mann Whitney U-tests and Random forest classifier compared gait between those with and without FOF. Selected gait variables were used to build Support Vector Machine (SVM) classifier and performance was evaluated using AUC-ROC.

RESULTS

Individuals with FOF had slower gait speed (103.66 ± 17.09 vs. 110.07 ± 14.83 cm/s), greater step time CoV (4.17 ± 1.66 vs. 3.72 ± 1.24 %), smaller walk-ratio (0.53 ± 0.08 vs. 0.56 ± 0.07 cm/steps/minute), smaller standard deviation V (0.15 ± 0.06 vs. 0.18 ± 0.09 m/s2), and smaller harmonic-ratio V (2.14 ± 0.73 vs. 2.38 ± 0.58), all p<.01. Linear SVM yielded an AUC-ROC of 67 % on test dataset, coefficient values being gait speed (-0.19), standard deviation V (-0.23), walk-ratio (-0.36), and smoothness V (-0.38) describing associations with presence of FOF.

CONCLUSION

Older adults with FOF have reduced gait speed, acceleration adaptability, walk-ratio, and smoothness. Disrupted gait patterns during fear of falling could provide insights into psychosocial distress in older adults. Longitudinal studies are warranted.

Association of Gait Quality With Daily-Life Mobility: An Actigraphy and Global Positioning System Based Analysis in Older Adults

OBJECTIVE

Walking is a key component of daily-life mobility. We examined associations between laboratory-measured gait quality and daily-life mobility through Actigraphy and Global Positioning System (GPS). We also assessed the relationship between two modalities of daily-life mobility i.e., Actigraphy and GPS.

METHODS

In community-dwelling older adults (N = 121, age = 77±5 years, 70% female, 90% white), we obtained gait quality from a 4-m instrumented walkway (gait speed, walk-ratio, variability) and accelerometry during 6-Minute Walk (adaptability, similarity, smoothness, power, and regularity). Physical activity measures of step-count and intensity were captured from an Actigraph. Time out-of-home, vehicular time, activity-space, and circularity were quantified using GPS. Partial Spearman correlations between laboratory gait quality and daily-life mobility were calculated. Linear regression was used to model step-count as a function of gait quality. ANCOVA and Tukey analysis compared GPS measures across activity groups [high, medium, low] based on step-count. Age, BMI, and sex were used as covariates.

RESULTS

Greater gait speed, adaptability, smoothness, power, and lower regularity were associated with higher step-counts (0.20<|ρp| < 0.26, p < .05). Age(β = -0.37), BMI(β = -0.30), speed(β = 0.14), adaptability(β = 0.20), and power(β = 0.18), explained 41.2% variance in step-count. Gait characteristics were not related to GPS measures. Participants with high (>4800 steps) compared to low activity (steps<3100) spent more time out-of-home (23 vs 15%), more vehicular travel (66 vs 38 minutes), and larger activity-space (5.18 vs 1.88 km2), all p < .05.

CONCLUSIONS

Gait quality beyond speed contributes to physical activity. Physical activity and GPS-derived measures capture distinct aspects of daily-life mobility. Wearable-derived measures should be considered in gait and mobility-related interventions.

Weekly minutes of moderate to vigorous physical activity is associated with movement quality in overweight and obese older adults, independent of age

BACKGROUND

Physical activity can improve function and decrease healthcare spending among overweight and obese older adults. Although unstructured physical activity has been related to cardiometabolic improvements, the relationship between unstructured activity and movement quality is unclear.

AIMS

This study aimed to evaluate the association of amount of unstructured free-living moderate-vigorous physical activity (MVPA) with measures of movement quality in overweight and obese older adults.

METHODS

The association of MVPA with movement quality was assessed in 165 overweight and obese older adults (Age: 77.0(8.0) years; Body mass index (BMI): 29.2(5.3) kg/m2). Participants performed overground walking, the Figure of 8 Walk test, and the Five-Times Sit to Stand. Weekly physical activity was measured using a waist-worn Actigraph activity monitor.

RESULTS

Movement quality during straight path [gait speed (ρ = 0.30, p < 0.01), stride length (ρ = 0.33, p < 0.01), double-limb support time (ρ = -0.26, p < 0.01), and gait symmetry (ρ = 0.17, p = 0.02)] and curved path [F8W time (ρ = -0.22, p < 0.01) and steps (ρ = -0.22, p < 0.01)] walking were associated with weekly minutes of MVPA after controlling for age. Five-Times Sit to Stand performance was not significantly associated with weekly minutes of MVPA (ρ = -0.10, p = 0.13).

CONCLUSIONS

Older adults with high BMIs who are less active also demonstrate poorer movement quality, independent of age. Physical activity engagement and task-specific training should be targeted in interventions to promote healthy aging, decrease falls, and delay disability development. Future work should consider the interconnected nature of movement quality with physical activity engagement and investigate if targeting one influences the other.

Exercise interventions, postural control, and prefrontal cortex activation in older adults

Improving postural control in older adults is necessary for reducing fall risk, and prefrontal cortex activation may also play a role. We sought to examine the impact of exercise interventions on postural control and prefrontal cortex activation during standing balance tasks. We hypothesized that balance would improve and prefrontal control would be reduced. We assessed a subset of participants enrolled in a randomized trial of two exercise interventions. Both groups completed strength and endurance training and the experimental treatment arm included training on timing and coordination of stepping. Postural control and prefrontal cortex activation were measured during dual-task standing balance tasks before and after the intervention. Eighteen participants in the standard strengthening and mobility training arm and 16 in the timing and coordination training arm were included. We examined pre- to post-intervention changes within each study arm, and compared them between interventions. Results did not show any pre- to post-intervention changes on standing postural control nor prefrontal cortex activation in either arm. In addition, there were no differences between the two intervention arms in either balance or prefrontal activation. While exercise interventions can improve mobility, we do not demonstrate evidence of improved standing balance or prefrontal control in standing.

Uneven surface and cognitive dual-task independently affect gait quality in older adults

BACKGROUND

Real-world mobility involves walking in challenging conditions. Assessing gait during simultaneous physical and cognitive challenges provides insights on cognitive health.

RESEARCH QUESTION

How does uneven surface, cognitive task, and their combination affect gait quality and does this gait performance relate to cognitive functioning?

METHODS

Community-dwelling older adults (N = 104, age=75 ± 6 years, 60 % females) performed dual-task walking paradigms (even and uneven surface; with and without alphabeting cognitive task (ABC)) to mimic real-world demands. Gait quality measures [speed(m/s), rhythmicity(steps/minute), stride time variability (%), adaptability (m/s2), similarity, smoothness, power (Hz) and regularity] were calculated from an accelerometer worn on the lower back. Linear-mixed modelling and Tukey analysis were used to analyze independent effects of surface and cognitive task and their interaction on gait quality. Partial Spearman correlations compared gait quality with global cognition and executive function.

RESULTS

No interaction effects between surface and cognitive task were found. Uneven surface reduced gait speed(m/s) (β = -0.07). Adjusted for speed, uneven surface reduced gait smoothness (β = -0.27) and increased regularity (β = 0.09), Tukey p < .05, for even vs uneven and even-ABC vs uneven-ABC. Cognitive task reduced gait speed(m/s) (β = -0.12). Adjusted for speed, cognitive task increased variability (β = 7.60), reduced rhythmicity (β = -6.68) and increased regularity (β = 0.05), Tukey p < .05, for even vs even-ABC and uneven vs uneven-ABC. With demographics as covariates, gait speed was not associated with cognition. Gait quality [lower variability during even-ABC (ρp =-.31) and uneven-ABC (ρp =-.28); greater rhythmicity (ρp between.22 and.29) and greater signal-adaptability AP (ρp between.22 and.26) during all walking tasks] was associated with better global cognition. Gait adaptability during even (ρp =-0.21, p = 0.03) and uneven(ρp =-0.19, p = 0.04) walking was associated with executive function.

SIGNIFICANCE

Surface and cognitive walking tasks independently affected gait quality. Our study with high-functioning older adults suggests that task-related changes in gait quality are related to subtle changes in cognitive functioning.

OA-Pain-Sense: Machine Learning Prediction of Hip and Knee Osteoarthritis Pain from IMU Data

Joint pain is a prominent symptom of Hip and Knee Osteoarthritis (OA), impairing patients’ movements and affecting the joint mechanics of walking. Self-report questionnaires are currently the gold standard for Hip OA and Knee OA pain assessment, presenting several problems, including the fact that older individuals often fail to provide accurate self-pain reports. Passive methods to assess pain are desirable. This study aims to explore the feasibility of OA-Pain-Sense, a passive, automatic Machine Learning-based approach that predicts patients’ self-reported pain levels using SpatioTemporal Gait features extracted from the accelerometer signal gathered from an anterior-posterior wearable sensor. To mitigate inter-subject variability, we investigated two types of data rescaling: subject-level and dataset-level. We explored six different binary machine learning classification models for discriminating pain in patients with Hip OA or Knee OA from healthy controls. In rigorous evaluation, OA-Pain-Sense achieved an average accuracy of 86.79% using the Decision Tree and 83.57% using Support Vector Machine classifiers for distinguishing Hip OA and Knee OA patients from healthy subjects, respectively. Our results demonstrate that OA-Pain-Sense is feasible, paving the way for the development of a pain assessment algorithm that can support clinical decision-making and be used on any wearable device, such as smartphones.

Facilitators and barriers to real-life mobility in community-dwelling older adults: a narrative review of accelerometry- and global positioning system-based studies

Real-life mobility, also called "enacted" mobility, characterizes an individual's activity and participation in the community. Real-life mobility may be facilitated or hindered by a variety of factors, such as physical abilities, cognitive function, psychosocial aspects, and external environment characteristics. Advances in technology have allowed for objective quantification of real-life mobility using wearable sensors, specifically, accelerometry and global positioning systems (GPSs). In this review article, first, we summarize the common mobility measures extracted from accelerometry and GPS. Second, we summarize studies assessing the associations of facilitators and barriers influencing mobility of community-dwelling older adults with mobility measures from sensor technology. We found the most used accelerometry measures focus on the duration and intensity of activity in daily life. Gait quality measures, e.g., cadence, variability, and symmetry, are not usually included. GPS has been used to investigate mobility behavior, such as spatial and temporal measures of path traveled, location nodes traversed, and mode of transportation. Factors of note that facilitate/hinder community mobility were cognition and psychosocial influences. Fewer studies have included the influence of external environments, such as sidewalk quality, and socio-economic status in defining enacted mobility. Increasing our understanding of the facilitators and barriers to enacted mobility can inform wearable technology-enabled interventions targeted at delaying mobility-related disability and improving participation of older adults in the community.

Physical functioning associated with life-space mobility in later life among men and women

Background

Life-space mobility is defined as the ability to access different areas extending from the room where the person sleeps to places outside one’s hometown. Life-space mobility is vital to support performance of daily life activities and autonomous participation in social life. However, there is a dearth of research that investigates a wider range of physical functions and functioning in relation to life-space mobility rather than just single aspects. Thus, the purpose of the present study was to identify and describe several measures of physical functioning associated with life-space mobility among older men and women.

Methods

Data used in this study was derived from the OCTO 2 study, a population-based study of health, functioning and mobility among older persons (n = 312) in Sweden. Associations between Life-Space Assessment (LSA) total score and age, sex, Short Physical Performance Battery (SPPB), dizziness, lung function i.e. Peak Expiratory Flow (PEF), grip strength, self-rated vision and hearing were analysed through bivariate and multivariate regression models.

Results

The bivariate models showed that life-space mobility was significantly associated with sex, but also age, SPPB, PEF and grip strength in the total group as well as among men and women. In addition, hearing was significantly associated with life-space mobility among women. Those factors that were statistically significant in the bivariate models were further analysed in multivariable models for the total group, and for men and women separately. In these models, sex, grip strength and SPPB remained significantly associated with life-space mobility in the total group, as well as SPPB among both men and women.

Conclusion

Sex, physical function in terms of physical performance measured by SPPB (balance, gait speed and chair stand), and grip strength are associated with life-space mobility. Consequently, these factors need to be considered in assessments and interventions aiming to maintain mobility in old age.

The Association of Mobility Determinants and Life Space Among Older Adults

BACKGROUND

It is important to understand the factors associated with life space mobility so that mobility disability can be prevented/treated. The purpose of this study was to identify the association between mobility determinants and life space among older adults.

METHODS

This study was a cross-sectional analysis of 249 community-dwelling older adults (mean age=77.4 years, 65.5% female, 88% white) who were recruited for a randomized, controlled, clinical intervention trial. Associations between cognitive, physical, psychosocial, financial, and environmental mobility determinants and the Life Space Assessment (LSA) at baseline were determined using Spearman's correlation coefficients and one-way analysis of variance. Multivariate analysis was performed using multivariable linear regression models.

RESULTS

The mean LSA score for the sample was 75.3 (SD=17.8). Personal factors (age, gender, education, comorbidities), cognitive (Trail Making Test A and B), physical (gait speed, lower extremity power, Six Minute Walk Test, Figure of 8 Walk Test, tandem stance, energy cost of walking, and Late Life Function and Disability Function Scale), psychosocial (Modified Gait Efficacy Scale), and financial (neighborhood socio-economic status) domains of mobility were significantly associated with LSA score. In the final regression model, age (β=-0.43), lower extremity power (β=0.03), gait efficacy (β=0.19), and energy cost of walking (β=-57.41) were associated with life space (R 2=0.238).

CONCLUSIONS

Younger age, greater lower extremity power, more confidence in walking, and lower energy cost of walking were associated with greater life space. Clinicians treating individuals with mobility disability should consider personal, physical, and psychosocial factors assessing barriers to life space mobility.

Is intensive gait training feasible and effective at old age? A retrospective case-control study on the use of Lokomat Free-D in patients with chronic stroke

BACKGROUND

In the last decade, the number of people over 60 has increased, leading to various healthcare problems. The aim of this retrospective study is to evaluate the effects of robotic rehabilitation in elderly patients as well as their perception of usability and adaptation to intensive robotic neurorehabilitation.

METHODS

This is a retrospective case-control study. Eighty elderly stroke patients were included in the analysis using an electronic data retrieval system. The enrolled patients were divided into two groups: the experimental group (EG) underwent rehabilitation training with Lokomat FreeD, equipped with a VR screen, while the control group (CG) performed traditional rehabilitation training. The two groups matched for age, sex, education, brain injury, stroke interval. The rehabilitation protocol included a total of 40 training sessions.

RESULTS

Both types of rehabilitation led to an improvement in the perceived level of disability (FIM) and in the performance in gait and balance (TT), highlighting a significant improvement especially in the EG. However, only in the EG, Lokomat training had induced an increase in the distance covered in 10 min (10 m walk test), and a significant improvement in mood (HRS-D). Moreover, Lokomat-FreeD was well tolerated by patients with high levels of usability.

CONCLUSIONS

Our results suggest that elderly patients may benefit from high-intensity robotic neurorehabilitation using the Lokomat-Pro FreeD.