Gait Measures Research Articles

Preliminary Effectiveness of a Companion Dog Whole Health Intervention for Improving Balance and Gait Quality in Veterans.

The benefits of exercise for older adults are well known; however, most older adults do not meet recommendations for regular physical activity. Alternative methods of improving physical activity are important and can be effective at improving mobility. This analysis evaluated if participation in a Whole Health companion dog adoption program supported changes in balance and gait performance for veterans. The role of time veteran and dog spent being physically active together (i.e., walking) on observed balance and gait changes was also explored. Veterans were paired with companion dogs and physical function, self-reported physical activity, and gait quality with an instrumented 6-minute walk test were assessed at baseline and after 1 year of participation. Physical activity was captured by accelerometers worn by both the veteran and dog. Paired samples t-tests were used to evaluate change in gait and physical performance measures from baseline to follow-up. Simple linear regressions were used to explore the role of time the veteran and companion dog spent being active together on observed changes in gait and physical function. Participants completed informed consent before participation in the IRB-approved study procedures (HP-97664; 1651218). Fourteen veterans (71.4% male, 62.3 ± 12.0 years) participated in the program. Improvements were seen in balance (Four Square Step Test change 95% CI: -3.94 to -1.36 s), lower body strength (30-second Chair Stand change 95% CI: 1.89-6.40 reps), and endurance (6-Minute Walk Test change 95% CI: 27.03-80.55 m). Gait quality improved (stance time 95% CI: -0.11 to -0.03 s, stride time 95% CI: -0.09 to -0.02 s). Of participants, 42% reported increased physical activity at follow-up. The percentage of the day veterans and their dogs spent being active together explained 31%-33% of the changes in functional performance. A Whole Health companion dog adoption intervention can improve gait, balance, physical functioning, and physical activity.

Motor control complexity estimation using gait measures in individuals post-stroke

Motor control complexity estimation using gait measures in individuals post-stroke

Effect of Vibro-Tactile Stimulation Sequence and Support Surface Inclination on Gait and Balance Measures

The plantar surfaces of the feet are important for balance control during walking, specifically by allowing for the perception of pressure movements during stance. Background/Objectives: The current study aimed to perturb CoP movement perception in healthy individuals by applying vibrations to the soles of the feet in different stimulation sequences: a natural pattern that followed CoP movement (gait-like) and a perturbing pattern that did not follow the CoP (random) during walking. We hypothesized that the gait-like stimulation sequence would be similar to walking without any stimulation and therefore have no effect on balance measures and that the random sequence would negatively affect balance measures such as the anteroposterior (AP) and mediolateral (ML) margins of stability (MoSs) and foot placement area. Methods: Subjects walked at a level angle and 5.0 and 8.0 degrees of incline and with low visual conditions to increase reliance on tactile sensations from the feet. Results: No significant effect of the stimulation sequence was found at any incline, while there was a significant effect of incline. As the incline increased from level to 5 deg, subjects reduced their AP MoS measured at heel strikes from 4.36 ± 0.56 cm to 1.95 ± 1.07 cm and increased their foot placement area from 24.04 ± 11.13 cm2 to 38.98 ± 17.47 cm2. However, the AP MoS measured at midstance did not significantly change as the incline increased. Conclusions: The stimulation sequence had no effect on the dependent measures, but the subjects could still feel the vibrations on the plantar surfaces during walking; this implies that similar stimulation techniques could be a useful method for applying directive biofeedback without negatively impacting gait. Overall, this study demonstrates the detailed control of our tactile system and the adaptability of healthy individuals while walking with a perturbing stimulation.

Gait speed assessment in confined spaces: Development of a novel automated 4-m static-start test to measure dynamic-start gait speed.

To promote standardization and feasible measurements of gait speed across the field, we developed a device that used light detection and ranging (LiDAR) technology to measure gait speed from a standing-start testing procedure conducted on a 4-m total walkway. We compared this automated (LiDAR-based) standing-start 4-m gait speed test (AS-4MG) with automated and manual (stopwatch-based) dynamic-start 4-m gait speed tests (AD-4MG and MD-4MG, respectively) on between-method agreement, measurement repeatability, and predictive validity with functional outcomes. A sample of 48 community-dwelling adults (mean [SD], 69 [9] years) participated in this method comparison study. Participants completed a survey and a physical function assessment, from which self-reported stair difficulty, handgrip strength, sit-to-stand performance, and gait speed (AS-, AD-, and MD-4MG) were measured. Mean AS-4MG, AD-4MG, and MD-4MG were 1.12, 1.13, and 1.14 m/s, respectively, with a strong correlation (r = 0.94) and no systematic bias observed between AS-4MG and the referent AD-4MG. In the analyses of repeated gait measurements, coefficients of repeatability were <0.20 m/s for the automated tests (0.16 and 0.18 m/s for AS-4MG and AD-4MG, respectively) but not for MD-4MG (0.22 m/s). Correlations between gait speed and functional measures ranged between 0.44 and 0.68 (Ps < 0.01). Correlations for the automated tests were comparable, while AS-4MG correlations tended to exceed MD-4MG correlations. In community-dwelling adults, the AS-4MG test was unbiased when compared with the AD-4MG, encompassing a 9-m walkway, with both tests showing equivalence of measurement repeatability and predictive validity. The AS-4MG potentially allows gait measurements in confined spaces (e.g., doctor's office) where the gait speed test was previously unfeasible. Geriatr Gerontol Int 2025; ••: ••-••.

Randomized Controlled Studies on Smartphone Applications and Wearable Devices for Postoperative Rehabilitation After Total Knee Arthroplasty: A Systematic Review.

Smartphone and wearable technologies are novel devices for monitoring postoperative mobility and recovery in total knee arthroplasty (TKA) patients. This systematic review of the highest-level evidence studies evaluated the advantages of these technologies in postoperative care, specifically focusing on 1) smartphone applications, 2) wearable devices, and 3) their combined use. A systematic literature search from July 26, 2015, to June 13, 2024, identified Level-1 and -2 published studies investigating smartphone applications and wearables for monitoring post-TKA recovery. A total of 3,131 studies were screened, with 31 meeting inclusion criteria: 18 focused on applications, eight on wearables, and five on both. Study quality was evaluated using the Coleman Methodology Scoring. Key metrics analyzed included patient satisfaction scores and adherences, functional outcomes, and pain scores, ranges of motion and gait analyses, and measurements and comparison tools. Among the Level 1 and 2 publications, 17 of 18 studies on smartphone applications for postoperative recovery in TKA highlighted benefits including patient satisfaction, improved gait, optimized pain management through medication scheduling guidance, cost savings, and better functional outcomes. Among the eight studies focused solely on wearable technologies, seven exhibited positive outcomes and demonstrated accuracy in monitoring and effectiveness in gait and motion analysis. Additional benefits included improved recovery outcomes, enhanced return to function, cost reduction, and better pain management through patient interaction and guidance. The five studies, which integrated both applications and wearables, corroborated these findings, emphasizing patient satisfaction and overall mobility enhancement at three months post-surgery. Smartphone applications and wearable devices offer enhancements in postoperative rehabilitation following TKA. Randomized trials validate their accuracy, effectiveness, and utility in this context. Improved adherence to care plans and medication schedules emerged as recurrent findings. These technologies and resultant data not only provide direct patient benefits, but also promise potential cost savings.

Exploring the Effect of Sampling Frequency on Real-World Mobility, Sedentary Behaviour, Physical Activity and Sleep Outcomes Measured with Wearable Devices in Rheumatoid Arthritis: Feasibility, Usability and Practical Considerations.

Modern treat-to-target management of rheumatoid arthritis (RA) involves titration of drug therapy to achieve remission, requiring close monitoring of disease activity through frequent clinical assessments. Accelerometry offers a novel method for continuous remote monitoring of RA activity by capturing fluctuations in mobility, sedentary behaviours, physical activity and sleep patterns over prolonged periods without the expense, inconvenience and environmental impact of extra hospital visits. We aimed to (a) assess the feasibility, usability and acceptability of wearable devices in patients with active RA; (b) investigate the multivariate relationships within the dataset; and (c) explore the robustness of accelerometry outcomes to downsampling to facilitate future prolonged monitoring. Eleven people with active RA newly starting an arthritis drug completed clinical assessments at 4-week intervals for 12 weeks. Participants wore an Axivity AX6 wrist device (sampling frequency 100 Hz) for 7 days after each clinical assessment. Measures of macro gait (volume, pattern and variability), micro gait (pace, rhythm, variability, asymmetry and postural control of walking), sedentary behaviour (standing, sitting and lying) and physical activity (moderate to vigorous physical activity [MVPA], sustained inactive bouts [SIBs]) and sleep outcomes (sleep duration, wake up after sleep onset, number of awakenings) were recorded. Feasibility, usability and acceptability of wearable devices were assessed using Rabinovich's questionnaire, principal component (PC) analysis was used to investigate the multivariate relationships within the dataset, and Bland-Altman plots (bias and Limits of Agreement) and Intraclass Correlation Coefficient (ICC) were used to test the robustness of outcomes sampled at 100 Hz versus downsampled at 50 Hz and 25 Hz. Wearable devices obtained high feasibility, usability and acceptability scores among participants. Macro gait outcomes and MVPA (first PC) and micro gait outcomes and number of SIBs (second PC) exhibited the strongest loadings, with these first two PCs accounting for 40% of the variance of the dataset. Furthermore, these device metrics were robust to downsampling, showing good to excellent agreements (ICC ≥ 0.75). We identified two main domains of mobility, physical activity and sleep outcomes of people with RA: micro gait outcomes plus MVPA and micro gait outcomes plus number of SIBs. Combined with the high usability and acceptability of wearable devices and the robustness of outcomes to downsampling, our real-world data supports the feasibility of accelerometry for prolonged remote monitoring of RA disease activity.

Instrumenting Parkrun: Usefulness and Validity of Inertial Sensors.

The analysis of running gait has conventionally taken place within an expensive and restricted laboratory space, with wearable technology offering a practical, cost-effective, and unobtrusive way to examine running gait in more natural environments. This pilot study presents a wearable inertial measurement unit (IMU) setup for the continuous analysis of running gait during an outdoor parkrun (i.e., 5 km). The study aimed to (1) provide analytical validation of running gait measures compared to time- and age-graded performance and (2) explore performance validation. Ten healthy adults (7 females, 3 males, mean age 37.2 ± 11.7 years) participated. The participants wore Axivity AX6 IMUs on the talus joint of each foot, recording tri-axial accelerometer and gyroscope data at 200 Hz. Temporal gait characteristics-gait cycle, ground contact time, swing time, and duty factor-were extracted using zero-crossing algorithms. The data were analyzed for correlations between the running performance, foot strike type, and fatigue-induced changes in temporal gait characteristics. Strong correlations were found between the performance time and both the gait cycle and ground contact time, with weak correlations for foot strike types. The analysis of asymmetry and fatigue highlighted modest changes in gait as fatigue increased, but no significant gender differences were found. This setup demonstrates potential for in-field gait analysis for running, providing insights for performance and injury prevention strategies.

Understanding the implication of task conditions on asymmetry in gait of post-stroke individuals using an Integrated Wearable System.

Hemiplegic individuals often demonstrate gait abnormality causing asymmetry in lower-limb muscle activation-related (implicit) and gait-related (explicit) measures (offering complementary information on one's gait) while walking. Added to hemiplegia, such asymmetry can be aggravated while walking under varying task conditions, namely, walking without speaking (single task), walking while counting backwards (dual task), and walking while holding an object and counting backwards (multiple task). This emphasizes the need to quantify the extent of aggravated implication of multiple-task and dual-task on gait asymmetry compared to single task. Here, we used Integrated Wearable System and carried out a study with a group of age-matched hemiplegic (Grp_S) and healthy (Grp_H) individuals to understand the potential of our system in quantifying asymmetry in explicit and implicit measures of gait, implication of hemiplegic condition and varying task conditions on these asymmetry measures along with their clinical relevance. Results showed the potential of our system in quantifying asymmetry in both explicit and implicit measures of gait, and these measures were statistically higher (p-value < 0.05) in Grp_S than Grp_H irrespective of the task conditions. Also, for Grp_S, these asymmetry measures became more pronounced as task demand increased, and again, these measures have shown a correlation with their risk of fall specifically during more attention-demanding tasks that could be clinically relevant.

Steps to Facilitate the Use of Clinical Gait Analysis in Stroke Patients: The Validation of a Single 2D RGB Smartphone Video-Based System for Gait Analysis.

Clinical gait analysis plays a central role in the rehabilitation of stroke patients. However, practical and technical challenges limit their use in clinical settings. This study aimed to validate SMARTGAIT, a deep learning-based gait analysis system that addresses these limitations. Eight stroke patients took part in the study at the Human Performance Research Centre of the University of Konstanz. Gait measurements were taken using both the marker-based Vicon motion capture system and the single-smartphone-based SMARTGAIT system. We evaluated the agreement for knee, hip, and ankle joint angle kinematics in the frontal and sagittal plane and spatiotemporal gait parameters between the two systems. The results mostly demonstrated high levels of agreement between the two systems, with Pearson correlations of ≥0.79 for all lower body angle kinematics in the sagittal plane and correlations of ≥0.71 in the frontal plane. RMSE values were ≤4.6°. The intraclass correlation coefficients for all derived gait parameters showed good to excellent levels of agreement. SMARTGAIT is a promising tool for gait analysis in stroke, particularly for quantifying gait characteristics in the sagittal plane, which is very relevant for clinical gait analysis. However, further analyses are required to validate the use of SMARTGAIT in larger samples and its transferability to different types of pathological gait. In conclusion, a single smartphone recording (monocular 2D RGB camera) could make gait analysis more accessible in clinical settings, potentially simplifying the process and making it more feasible for therapists and doctors to use in their day-to-day practice.

Do Worn-In Tactical Boots Affect Lower-Extremity Biomechanics During Walking and Running?

Background: Much of the research conducted on tactical-style boots has evaluated the biomechanical effect of boots in brand-new condition; however, the extent to which changes due to wear influence lower-extremity biomechanics remains uninvestigated. The purpose of this study was to compare lower-extremity biomechanics with worn-in boots and running shoes during both walking and running. Methods: Lower-extremity biomechanical parameters were evaluated during walking and running in 12 individuals with previous tactical experience. Participants were asked to complete one 5 min bout of walking and running at a self-selected pace in both self-selected athletic shoes and their own worn-in standard-issue tactical boots while lower-extremity spatiotemporal, joint kinematic, kinetic, and ground reaction force data were collected. Differences between conditions were evaluated using the Wilcoxon signed-rank test. Results: Spatiotemporal measures of gait, as well as ankle and hip kinematics, were different between shoes and boots during walking. During running, no spatiotemporal differences existed. However, significant differences were found for the ankle, knee, and hip kinematics between shoe and boot conditions during both walking and running. Conclusions: The worn-in boots in our sample performed similarly to running shoes during both walking and running tasks. Though there were several biomechanical differences between boots and shoes during both tasks, small mean differences suggest that these differences may not be large enough to create substantive or relevant changes in performance. This information could aid in developing future tactical boot design strategies to help aid in lower-extremity injury as well as allowing for optimal performance when wearing boots.

A cross‐sectional analysis of Alzheimer’s disease plasma biomarkers and gait variables in cognitively normal older adults

AbstractBackgroundA decline in gait has been associated with an escalated risk of cognitive decline and changes in Alzheimer’s disease (AD) biomarkers, thus offering prognostic insight. However, the utility of gait analysis in preclinical stages of AD is unclear, and prior studies have primarily used qualitative or gross measures of gait. Furthermore, gait analysis has predominantly been performed in cohorts of non‐Hispanic Whites. We analyzed the correlations between plasma biomarkers and quantitative gait variables in a diverse cohort of cognitively normal older adults.MethodA cohort of 129 consecutive participants (age 56‐93, 30% Black/ African American, 10% Hispanic/Latino) from the NYU Alzheimer’s Disease Research Center were confirmed cognitively normal via the Uniform Data Set Version 3 psychometric battery. Participants underwent quantitative gait analysis via the GAITRite walkway. Means and intra‐individual variability (expressed as standard deviation across the laps) of gait variables were assessed over the eight passes of the walk. Plasma levels of Aβ42, Aβ40, NfL, pTau181, and total tau were determined using Quanterix SIMOA. The associations between the gait measures and plasma biomarkers were analyzed using multivariable linear regression models, adjusting for age, sex, and ApoE status.ResultThe mean velocity showed a statistically significant negative association with NfL and total tau, after adjusting for age, sex, and ApoE genotype. A 1pg/ml increase in NfL was associated with a 0.33 unit decrease in mean velocity (p=0.028). A 1pg/ml increase in total tau was associated with a 3.53 decrease in mean velocity (p=0.013). Intra‐individual variability in gait velocity also showed a statistically significant positive association with pTau181. A 1pg/ml increase in ptau181 level showed a 0.385 unit increase in velocity variability (p=0.018).ConclusionAD plasma biomarkers show correlations to quantitative gait measures even in a cognitively normal population, apart from age and ApoE genotype. Our findings also promote the utility of both means and variability of gait measures in stratifying preclinical risk of AD.

The Minimum Number of Strides Required for Reliable Gait Measurements in Older Adult Fallers and Non-Fallers.

While the value of walking gait metrics collected using pressure-sensing walkways has shown promise for fall risk assessment, there is no consensus on the minimum number of strides required to obtain reliable metrics. This study aimed to determine the minimum stride count required for reliable single-task (ST), dual-task (DT), and difference score (DS) measurements of the spatio-temporal parameters of gait in older adult fallers and non-fallers. Forty community-dwelling older adults (74.6 ± 3.5 years) performed 10 ST and 10 DT walking passes (~100 strides total) across a GAITRite™ pressure mat. Nine truncated datasets (1-9 passes) were created from the original for each walking condition to assess agreement using two-way random effects, absolute agreement, and single-rater intraclass correlations (ICCs). ICCs demonstrated that a minimum of one pass (~10 strides) is sufficient for reliable mean gait metrics for ST and DT conditions and 10-30 strides for DS, while 10-80 strides are needed for reliable gait variability measures, depending on the metric. This study provides stride count recommendations to ensure reliable gait measurement in older adult populations, highlighting that as few as 10-30 strides are necessary for mean metrics, while variability metrics may require up to 80 strides to ensure reliability.

Association Between Standard Gait Measures and Anterior Quadriceps Muscle Thickness as Measured by Point of Care Ultrasound (POCUS).

Background: Gait parameters and sarcopenia both predict falls risk among older adults. Our objective was to evaluate whether fast, easy-to-obtain measures of anterior thigh muscle by point of care ultrasound (POCUS) are significantly associated with standard gait measures. Methods: All subjects were referred from ambulatory geriatric medicine clinics at an academic center. Quadriceps muscle thickness was measured by a portable ultrasound device. Gait variables were measured by the patient in comfortable walking shoes walking for six minutes. The primary response variables were gait variables, and the predictor variables were age, biological sex, body mass index, and muscle thickness. Univariate and multivariate regression analyses were performed. Results: A total of 150 participants were recruited from geriatric medicine clinics (65 women, 84 men). Muscle thickness was measured in 149 participants, and the mean (SD) was 1.91 (0.52) (median 1.82 cm, 0.96 to 3.68 cm). Univariate analysis of gait parameters with age showed a statistically significant correlation with gait speed (R2=0.16, P < 0.000), average stride length (R2=0.142, P < 0.000), and average stride velocity (R2=0.182, P < 0.000). Among all the gait variables, average swing time (P = 0.010) and average stance time (P = 0.010) were correlated significantly with muscle thickness. For multivariate analysis with age and gait variables, age was a significant independent variable for all gait variables that were significant in univariate analysis. Conclusion: POCUS showed a significant association with average swing time, average stance time, and step time variability. Although more work needs to be done, POCUS has the potential to be a rapid screening tool for gait assessment.

Cell type–specific gene therapy confers protection against motor neuron disease caused by a TFG variant

Inherited forms of motor neuron disease (MND), including hereditary spastic paraplegias (HSP), are associated with the death or dysfunction of nerve cells that control skeletal muscle activity. However, in some cases, the impacts of genetic variants underlying MND act in a non-cell autonomous manner, instead affecting the function of other cell types necessary for neuronal maintenance. Pathological mutations in TFG, which have been implicated in HSP, lead to axonopathy within the corticospinal tract, but it remains unclear whether this problem arises due to perturbations within neurons or supporting neuroglia. To address this question, we leveraged a rat model harboring the recessive TFG p.R106C mutation (mRATBN7.2, g.11:43897639C>T, c.316C>T), which recapitulates multiple phenotypes associated with HSP in humans, including progressive motor deficits, leg spasticity, and indications of an inflammatory response within the motor cortex. In particular, we took advantage of cell type-specific gene therapies to demonstrate that the reintroduction of wild-type TFG into synapsin 1-positive neurons provides robust protection against MND, whereas its expression in GFAP-positive glial cells provides no significant improvement in quantitative measures of gait, despite a dramatic reduction in the presence of reactive astrocytes throughout the brain. These data strongly suggest that therapeutic approaches targeting neurons should be pursued in cases of TFG-HSP, with our animal model offering a unique platform for preclinical assessment.

Objective gait assessment and quantified recurrence analysis using foot-worn wearable sensor for healthy individuals

Wearable sensors allow mobility assessment required for better locomotion, neurological and musculoskeletal disorders, current limitations include unknown reliability and accuracy in real-life settings. This work determined the concurrent validity and repeatability of the proposed foot-worn gait evaluation system using objective gait features and recurrence quantification analysis from 52 participants. Its agreement with the commercially available OpenGo® system in the unrestricted outdoor environment is determined. Reported measures showed no significant differences (p > 0.05) between systems. Test-retest reliability showed that the mean of the second-third trial (T2–T3) is the most significant. Thus, an affordable system provides accurate measurement of gait ensuring its suitability even in small clinical-settings.

Monitoring Age-Related Changes in Gait Complexity in the Wild with a Smartphone Accelerometer System.

Stride-to-stride fluctuations during walking reflect age-related changes in gait adaptability and are estimated with nonlinear measures that confine data collection to controlled settings. Smartphones, with their embedded accelerometers, may provide accessible gait analysis throughout the day. This study investigated age-related differences in linear and nonlinear gait measures estimated from a smartphone accelerometer (SPAcc) in an unconstrained, free-living environment. Thirteen young adults (YA) and 11 older adults (OA) walked within a shopping mall with a SPAcc placed in their front right pants pocket. The inter-stride interval, calculated as the time difference between ipsilateral heel contacts, was used for dependent measures calculations. One-way repeated-measures analysis of variance revealed significant (p < 0.05) age-related differences (mean: YA, OA) for stride-time standard deviation (0.04 s, 0.05 s) and coefficient of variation (3.47%, 4.16%), sample entropy (SaEn) scale 1 (1.70, 1.86) and scale 3 (2.12, 1.80), and statistical persistence decay (31 strides, 23 strides). The fractal scaling index was not different between groups (0.93, 0.95), but exceeded those typically found in controlled settings, suggesting an upregulation in adaptive behaviour likely to accommodate the increased challenge of free-living walking. These findings support the SPAcc as a viable telehealth instrument for remote monitoring of gait dynamics, with implications for unsupervised fall-risk assessment.

Gait performance in older adults across the cognitive spectrum: Results from the GAIT cohort.

Gait performance can provide valuable insights into cognitive functioning in older adult and may be used to screen for cognitive impairment. However, the optimal test condition and spatiotemporal parameter for accuracy have not yet been determined. This study aims to determine the gait measure with the highest accuracy identifying cognitive decline. A total of 711 participants were recruited, including 332 cognitively healthy individuals, 264 with mild cognitive impairment (MCI), and 115 with dementia, with a mean age of 72 years (interquartile range 69-76), and 43% (n = 307) of women. The participants underwent gait assessment in three different conditions, including a single task and dual tasks of counting backward by ones and naming animals. Gait performance was deteriorated as cognitive impairment progressed. The gait test performed during naming animals condition was the most accurate in differentiating between cognitive groups. Specifically, the naming animals gait speed was more accurate in discriminating control participants from those with cognitive impairment (area under the curve [AUC] = 76.9% for MCI and 99.7% for people with dementia with control group as reference). The coefficient of stride length variability while naming animals was the most effective parameter in discriminating between MCI and dementia groups (AUC = 96.7%). The naming animals dual-task gait test can be a valuable assessment for screening cognitive impairment in older adults, regardless of their cognitive abilities. The test is useful in clinical settings for subjects with a range of cognitive profiles.

Self-reported physical activity and gait in older adults without dementia: A longitudinal study.

Physical activity (PA) is associated with higher gait speed. We aimed to examine the associations between PA and change in spatial and temporal gait measures as well as fall risk in community-dwelling individuals free of dementia. Longitudinal study among 4173 individuals aged ≥50 years (mean age 71 years; 2078 males; median follow-up 4 years) enrolled in the Mayo Clinic Study of Aging. Self-reported late-life PA was used to calculate overall PA and moderate-vigorous PA (MVPA) scores. Gait was assessed using GAITRite® and Zeno™ systems. Incident falls information was based on diagnostic codes retrieved from medical records. We ran linear mixed effects models to examine associations between z-scored PA variables and longitudinal gait parameters, adjusted for age, sex, education, body mass index (BMI), medical comorbidities, and including interactions between PA and time since baseline. In secondary analyses, we calculated Cox Proportional hazard models with age as time scale predicting incident falls by PA, adjusting for sex, education, BMI, medical comorbidities, and falls history. At baseline, higher PA was associated with higher velocity (overall PA: estimate 2.9935; MVPA: 2.2961; p < 0.001), higher cadence (overall PA: 1.0665; MVPA: 0.9073; p < 0.001), greater stride length (overall PA: 2.0805; MVPA: 1.4726; p < 0.001), shorter double support time (overall PA: -0.0257; MVPA: -0.0205; p < 0.001), and lower stance time variability (overall PA: -0.0204, p < 0.001; MVPA: -0.0152; p = 0.006). Overall PA was longitudinally associated with less decline in cadence, and MVPA with less increase in intraindividual stance time variability. Overall PA (Hazard ratio 0.892, 95% confidence interval 0.828-0.961, p = 0.003) and MVPA (HR 0.901; 95% CI 0.835-0.973, p = 0.008) were associated with a decreased risk of incident falls. Late-life PA was associated with favorable gait outcomes and decreased risk of incident falls. Thus, late-life PA may help to maintain gait performance and decrease fall risk in old age.

Validity and reliability of running gait measurement with the ViMove2 system.

Running biomechanics have traditionally been analysed in laboratory settings, but this may not reflect natural running gait. Wearable technology has the potential to enable precise monitoring of running gait beyond the laboratory. This study aimed to evaluate the analytical validity and intra-session reliability of temporal running gait outcomes measured by the ViMove2 wearable system in healthy adults. Seventy-four healthy adults (43 males, 31 females, aged 18-55 years) wore the inertial device, ViMove2 on the tibia. Participants ran on a treadmill for one minute at various speeds (8, 10, 12, 14km/hr), completed in a standardised shoe (Saucony Guide Runner). Running gait was measured with the ViMove2 wearable and 3D motion capture (Vicon). Temporal running gait outcomes included ground contact time (GCT) and cadence (steps/min). GCT and cadence from the ViMove2 had face validity with expected changes in outcome with different running speeds, but ViMove2 tended to over-estimate GCT, and under-estimate cadence compared to the reference, especially at slower speeds. GCT demonstrated moderate to good agreement to the reference at speeds >10km/hr, but poor agreement at 8km/hr and within female runners. Cadence had moderate to excellent agreement across speeds compared to the reference. GCT and cadence had excellent reliability across speeds, but at 8km/hr GCT had good agreement between trials. Overall, temporal gait outcomes of GCT and cadence can be measured with the ViMove2, but accuracy and reliability are impacted at slow running speeds and within female runners. Future work is needed to clarify sex or speed-dependent corrections to algorithms / outcomes to aid interpretation and application.

Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.

Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo-gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear. Patients with CSVD from a hospital-based cohort (n = 194) and individuals with presumed early CSVD from a community-based cohort (n = 319) were included. Oculo-gait patterns were measured using the artificial intelligence (AI) -assisted 'EyeKnow' eye-tracking and 'ReadyGo' motor evaluation systems. Multivariable linear and logistic regression models were employed to investigate the association between the oculo-gait parameters and cognition. Anti-saccade accuracy, stride velocity, and swing velocity were significantly associated with cognition in both patients and community dwellers with CSVD, and could identify cognitive impairment in CSVD with moderate accuracy (area under the curve [AUC]: hospital cohort, 0.787; community cohort, 0.810) after adjusting for age and education. The evaluation of oculo-gait features (anti-saccade accuracy, stride velocity, and swing velocity) may help screen cognitive impairment in CSVD. Oculo-gait features (lower anti-saccade accuracy, stride velocity, and swing velocity) were associated with cognitive impairment in cerebral small vessel disease (CSVD). Logistic model integrating the oculo-gait features, age, and education level moderately distinguished cognitive status in CSVD. Artificial intelligence-assisted oculomotor and gait measurements provide quick and accurate evaluation in hospital and community settings.