Gait Changes Research Articles

Deep brain stimulation (DBS) as a therapeutic approach in gait disorders: What does it bring to the table?

Gait deficits are found in various degenerative central nervous system conditions, and are particularly a hallmark of Parkinson's disease (PD). While there is no cure for such neurodegenerative disorders, Levodopa is considered as the standard medication in PD patients. Often times, the therapy of severe PD consists of deep brain stimulation (DBS) of the subthalamic nucleus. Earlier research exploring the effect of gait have reported contradictory results or insufficient efficacy. A change in gait includes various parameters, such as step length, cadence, Double-stance phase duration which may be positively affected by DBS. DBS could also be effective in correcting the levodopa-induced postural sway abnormalities. Moreover, during normal walking, interaction among the subthalamic nucleus and cortex -essential regions which exert a role in locomotion- are coupled. However, during the freezing of gait, the activity is desynchronized. The mechanisms underlying DBS-induced neurobehavioral improvements in such scenarios requires further study. The present review discusses DBS in the context of gait, the benefits associated with DBS compared to standard pharmacotherapy options, and provides insights into future research.

Spatial-Temporal Analysis of Gait in Amyotrophic Lateral Sclerosis Using Foot-Worn Inertial Sensors: An Observational Study

Introduction: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that alters gait and increases the risk of falls. The current model of care involves in-person multidisciplinary clinic visits to, in part, assess alterations in gait, evaluate safety, and make recommendations for management. Clinic visits, however, are relatively infrequent, and multidisciplinary evaluations can be physically demanding for patients. To better understand how gait changes over time in those with ALS and enable healthcare providers to properly respond to these changes, remote monitoring of functional mobility would be advantageous. Methods: The objective of this study was to remotely track long-term changes in walking speed using wearable inertial measurement units (IMUs). Nine ALS patients and 6 healthy controls submitted twice-weekly home walking recordings for 24 and 4 weeks, respectively. An IMU data processing method was developed and validated against laboratory-measured walking speed. Results: For both ALS patients and healthy controls, home walking speed was less than clinic walking speed by an average of 0.19 m/s (p = 0.0024). Over 24 weeks, home walking speed significantly decreased for 5 of 9 ALS patients at an average of −0.021 m/s/months (p = 0.005). Those who eventually transitioned to using assistive device (AD) while on the study demonstrated a greater decrease in walking speed than those who did not. Conclusions: Remote longitudinal gait monitoring of ALS patients is feasible with the use of an IMU. Decreases in walking speed were detected in the majority of patients, most strongly in those who eventually transitioned to an AD. Home walking speed may more accurately represent the walking abilities of ALS patients in their real-life environments, a finding which further supports the case for remote monitoring in ALS.

Change in gait speed and fall risk among community-dwelling older adults with and without mild cognitive impairment: a retrospective cohort analysis

BackgroundAlthough slow gait speed is an established risk factor for falls, few studies have evaluated change in gait speed as a predictor of falls or considered variability in effects by cognitive status. Change in gait speed may be a more useful metric because of its potential to identify decline in function. In addition, older adults with mild cognitive impairment are at an elevated risk of falls. The purpose of this research was to quantify the association between 12-month change in gait speed and falls in the subsequent 6 months among older adults with and without mild cognitive impairment.MethodsFalls were self-reported every six months, and gait speed was ascertained annually among 2,776 participants in the Ginkgo Evaluation of Memory Study (2000–2008). Adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for fall risk relative to a 12-month change in gait speed.ResultsSlowing gait speed over 12 months was associated with increased risk of one or more falls (HR:1.13; 95% CI: 1.02 to 1.25) and multiple falls (HR:1.44; 95% CI: 1.18 to 1.75). Quickening gait speed was not associated with risk of one or more falls (HR 0.97; 95% CI: 0.87 to 1.08) or multiple falls (HR 1.04; 95% CI: 0.84 to 1.28), relative to those with a less than 0.10 m/s change in gait speed. Associations did not vary by cognitive status (pinteraction = 0.95 all falls, 0.25 multiple falls).ConclusionsDecline in gait speed over 12 months is associated with an increased likelihood of falls among community-dwelling older adults, regardless of cognitive status. Routine checks of gait speed at outpatient visits may be warranted as a means to focus fall risk reduction efforts.

Spatial and Temporal Gait Characteristics in Patients Admitted to a Neuro-Rehabilitation Department with Age-Related White Matter Changes: A Gait Analysis and Clinical Study.

Patients with age-related white matter changes (ARWMC) frequently present a gait disorder, depression and cognitive impairment. Our aims are to define which alterations in the gait parameters are associated with motor or neuro-psychological impairment and to assess the role of motor, mood or cognitive dysfunction in explaining the variance of the gait parameters. Patients with gait disorders admitted to a Neuro-rehabilitation Department, affected by vascular leukoencephalopathy who had ARWMC confirmed by a brain MRI, were consecutively enrolled, classified by a neuroradiological scale (Fazekas 1987) and compared to healthy controls. We excluded subjects unable to walk independently, subjects with hydrocephalus or severe aphasia, with orthopaedic and other neurological pathologies conditioning the walking pattern. Patients and controls were assessed by clinical and functional scales (Mini Mental State Examination, Geriatric Depression Scale, Nevitt Motor Performance Scale, Berg Balance Scale, Functional Independence Measure), and computerised gait analysis was performed to assess the spatial and temporal gait parameters in a cross-sectional study. We recruited 76 patients (48 males, aged 78.3 ± 6.2 years) and 14 controls (6 males, aged 75.8 ± 5 years). In the multiple regression analysis, the gait parameter with overall best model summary values, associated with the ARWMC severity, was the stride length even after correction for age, sex, weight and height (R2 = 0.327). The motor performances justified at least in part of the gait disorder (R2 change = 0.220), but the mood state accounted independently for gait alterations (R2 change = 0.039). The increase in ARWMC severity, the reduction of motor performance and a depressed mood state were associated with a reduction of stride length (R = 0.766, R2 = 0.587), reduction of gait speed (R2 = 0.573) and an increase in double support time (R2 = 0.421). The gait disorders in patients with ARWMC are related to motor impairment, but the presence of depression is an independent factor for determining gait alterations and functional status. These data pave the way for longitudinal studies, including gait parameters, to quantitatively assess gait changes after treatment or to monitor the natural progression of the gait disorders.

Control of center of mass during gait of stroke patients: Statistical parametric mapping analysis

BackgroundThe control of the center of mass is essential for a stable and efficient gait. Post-stroke patients present several impairments, which may compromise the control of the center of mass during gait in the sagittal and frontal planes. This study aimed to identify changes in the vertical and mediolateral behavior of the center of mass during the single stance phase of post-stroke patients using the statistical parametric mapping analysis. It also aimed to identify alterations in the center of mass trajectories regarding the motor recovery stages. MethodsSeventeen stroke patients and 11 neurologically intact individuals were analyzed. The statistical parametric mapping approach was used to identify changes in the center of mass trajectories between stroke and healthy groups. The trajectories of the center of mass of post-stroke individuals were compared according to their motor recovery status. FindingsA near-flat vertical trajectory of the center of mass was indenfitifed in the stroke group compared to their healthy counterparts, especially on the paretic side. The center of mass trajectories in both directions (vertical and mediolateral) presented substantial alteration at the end of the single stance phase in the stroke group. The trajectory of the center of mass of the stroke group was symmetrical in the mediolateral direction between the sides. The trajectories of the center of mass presented similar pattern irrespective of the motor recovery status. InterpretationThe statistical parametric mapping approach showed to be suitable for determining gait changes in post-stroke individuals, irrespective of their motor recovery stage.

IRGA: An Intelligent Implicit Real-time Gait Authentication System in Heterogeneous Complex Scenarios

Gait authentication as a technique that can continuously provide identity recognition on mobile devices for security has been investigated by academics in the community for decades. However, most of the existing work achieves insufficient generalization to complex real-world environments due to the complexity of the noisy real-world gait data. To address this limitation, we propose an intelligent Implicit Real-time Gait Authentication (IRGA) system based on Deep Neural Networks (DNNs) for enhancing the adaptability of gait authentication in practice. In the proposed system, the gait data (whether with complex interference signals) will first be processed sequentially by the imperceptible collection module and data preprocessing module for improving data quality. In order to illustrate and verify the suitability of our proposal, we provide analysis of the impact of individual gait changes on data feature distribution. Finally, a fusion neural network composed of a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) is designed to perform feature extraction and user authentication. We evaluate the proposed IRGA system in heterogeneous complex scenarios and present start-of-the-art comparisons on three datasets. Extensive experiments demonstrate that the IRGA system achieves improved performance simultaneously in several different metrics.

Dynamics of excitable cells: spike-adding phenomena in action

We study the dynamics of action potentials of some electrically excitable cells: neurons and cardiac muscle cells. Bursting, following a fast–slow dynamics, is the most characteristic behavior of these dynamical systems, and the number of spikes may change due to spike-adding phenomenon. Using analytical and numerical methods we give, by focusing on the paradigmatic 3D Hindmarsh–Rose neuron model, a review of recent results on the global organization of the parameter space of neuron models with bursting regions occurring between saddle-node and homoclinic bifurcations (fold/hom bursting). We provide a generic overview of the different bursting regimes that appear in the parametric phase space of the model and the bifurcations among them. These techniques are applied in two realistic frameworks: insect movement gait changes and the appearance of Early Afterdepolarizations in cardiac dynamics.

Effect of pregnancy on female gait characteristics: a pilot study based on portable gait analyzer and induced acceleration analysis.

Introduction: The changes in physical shape and center of mass during pregnancy may increase the risk of falls. However, there were few studies on the effects of maternal muscles on gait characteristics and no studies have attempted to investigate changes in induced acceleration during pregnancy. Further research in this area may help to reveal the causes of gait changes in women during pregnancy and provide ideas for the design of footwear and clothing for pregnant women. The purpose of this study is to compare gait characteristics and induced accelerations between non-pregnant and pregnant women using OpenSim musculoskeletal modeling techniques, and to analyze their impact on pregnancy gait. Methods: Forty healthy participants participated in this study, including 20 healthy non-pregnant and 20 pregnant women (32.25 ± 5.36weeks). The portable gait analyzer was used to collect participants' conventional gait parameters. The adjusted OpenSim personalized musculoskeletal model analyzed the participants' kinematics, kinetics, and induced acceleration. Independent sample T-test and one-dimensional parameter statistical mapping analysis were used to compare the differences in gait characteristics between pregnant and non-pregnant women. Results: Compared to the control group, pregnancy had a 0.34m reduction in mean walking speed (p < 0.01), a decrease in mean stride length of 0.19m (p < 0.01), a decrease in mean stride frequency of 19.06 step/min (p < 0.01), a decrease in mean thigh acceleration of 0.14m/s2 (p < 0.01), a decrease in mean swing work of 0.23g (p < 0.01), and a decrease in mean leg falling strength of 0.84g (p < 0.01). Induced acceleration analysis showed that pregnancy muscle-induced acceleration decreased in late pregnancy (p < 0.01), and the contribution of the gastrocnemius muscle to the hip and joint increased (p < 0.01). Discussion: Compared with non-pregnant women, the gait characteristics, movement amplitude, and joint moment of pregnant women changed significantly. This study observed for the first time that the pregnant women relied more on gluteus than quadriceps to extend their knee joints during walking compared with the control group. This change may be due to an adaptive change in body shape and mass during pregnancy.

Development of a Gait Feature-Based Model for Classifying Cognitive Disorders Using a Single Wearable Inertial Sensor.

Gait changes are potential markers of cognitive disorders (CDs). We developed a model for classifying older adults with CD from those with normal cognition using gait speed and variability captured from a wearable inertial sensor and compared its diagnostic performance for CD with that of the model using the Mini-Mental State Examination (MMSE). We enrolled community-dwelling older adults with normal gait from the Korean Longitudinal Study on Cognitive Aging and Dementia and measured their gait features using a wearable inertial sensor placed at the center of body mass while they walked on a 14-m long walkway thrice at comfortable paces. We randomly split our entire dataset into the development (80%) and validation (20%) datasets. We developed a model for classifying CD using logistic regression analysis from the development dataset and validated it in the validation dataset. In both datasets, we compared the diagnostic performance of the model with that using the MMSE. We estimated optimal cutoff score of our model using receiver operator characteristic analysis. In total, 595 participants were enrolled, of which 101 of them experienced CD. Our model included both gait speed and temporal gait variability and exhibited good diagnostic performance for classifying CD from normal cognition in both the development (area under the receiver operator characteristic curve [AUC] = 0.788, 95% CI 0.748-0.823, p < 0.001) and validation datasets (AUC = 0.811, 95% CI 0.729-0.877, p < 0.001). Our model showed comparable diagnostic performance for CD with that of the model using the MMSE in both the development (difference in AUC = 0.026, standard error [SE] = 0.043, z statistic = 0.610, p = 0.542) and validation datasets (difference in AUC = 0.070, SE = 0.073, z statistic = 0.956, p = 0.330). The optimal cutoff score of the gait-based model was >-1.56. Our gait-based model using a wearable inertial sensor may be a promising diagnostic marker of CD in older adults. This study provides Class III evidence that gait analysis can accurately distinguish older adults with CDs from healthy controls.

Wheel Running Exacerbates Joint Damage after Meniscal Injury in Mice, but Does Not Alter Gait or Physical Activity Levels.

Exercise and physical activity are recommended to reduce pain and improve joint function in patients with knee osteoarthritis (OA). However, exercise has dose effects, with excessive exercise accelerating OA development and sedentary behaviors also promoting OA development. Prior work evaluating exercise in preclinical models has typically used prescribed exercise regimens; however, in-cage voluntary wheel running creates opportunities to evaluate how OA progression affects self-selected physical activity levels. This study aimed to evaluate how voluntary wheel running after a surgically induced meniscal injury affects gait characteristics and joint remodeling in C57Bl/6 mice. We hypothesize that injured mice will reduce physical activity levels as OA develops after meniscal injury and will engage in wheel running to a lesser extent than the uninjured animals. Seventy-two C57Bl/6 mice were divided into experimental groups based on sex, lifestyle (physically active vs sedentary), and surgery (meniscal injury or sham control). Voluntary wheel running data were continuously collected throughout the study, and gait data were collected at 3, 7, 11, and 15 wk after surgery. At end point, joints were processed for histology to assess cartilage damage. After meniscal injury, physically active mice showed more severe joint damage relative to sedentary mice. Nevertheless, injured mice engaged in voluntary wheel running at the same rates and distances as mice with sham surgery. In addition, physically active mice and sedentary mice both developed a limp as meniscal injury progressed, yet exercise did not further exacerbate gait changes in the physically active mice, despite worsened joint damage. Taken together, these data indicate a discordance between structural joint damage and joint function. Although wheel running after meniscal injury did worsen OA-related joint damage, physical activity did not necessarily inhibit or worsen OA-related joint dysfunction or pain in mice.

What does climbing mean exactly? Assessing spatiotemporal gait characteristics of inclined locomotion in parrots.

At what inclination does climbing begin? In this paper, we investigate the transition from walking to climbing in two species of parrot (Agapornis roseicollis and Nymphicus hollandicus) that are known to incorporate both their tail and their craniocervical system into the gait cycle during vertical climbing. Locomotor behaviors ranging in inclination were observed at angles between 0° and 90° for A. roseicollis, and 45°-85° degrees for N. hollandicus. Use of the tail in both species was observed at 45° inclination, and was joined at higher inclinations (> 65°) by use of the craniocervical system. Additionally, as inclination approached (but remained below) 90°, locomotor speeds were reduced while gaits were characterized by higher duty factors and lower stride frequency. These gait changes are consistent with those thought to increase stability. At 90°, A. roseicollis significantly increased its stride length, resulting in higher overall locomotor speed. Collectively these data demonstrate that the transition between horizontal walking and vertical climbing is gradual, incrementally altering several components of gait as inclinations increase. Such data underscore the need for further investigation into how exactly "climbing" is defined and the specific locomotor characteristics that differentiate this behavior from levelwalking.

Influence of cognitive and motor tasks using smartphone during gait: EMG and gait performance analysis – Dual-task study

Previous studies reported changes in spatiotemporal gait parameters during dual-task performance while walking using a smartphone compared to walking without a smartphone. However, studies that assess muscle activity while walking and simultaneously performing smartphone tasks are scarce. So, this study aimed to assess the effects of motor and cognitive tasks using a smartphone while simultaneously performing gait on muscle activity and gait spatiotemporal parameters in healthy young adults. Thirty young adults (22.83 ± 3.92 years) performed five tasks: walking without a smartphone (single-task, ST); typing on a smartphone keyboard in a sitting position (secondary motor single-task); performing a cognitive task on a smartphone in a sitting position (cognitive single-task); walking while typing on a smartphone keyboard (motor dual-task, mot-DT) and walking while performing a cognitive task on a smartphone (cognitive dual-task, cog-DT). Gait speed, stride length, stride width and cycle time were collected using an optical motion capture system coupled with two force plates. Muscle activity was recorded using surface electromyographic signals from bilateral biceps femoris, rectus femoris, tibialis anterior, gastrocnemius medialis, gastrocnemius lateralis, gluteus maximus and lumbar erector spinae. Results showed a decrease in stride length and gait speed from the single-task to cog-DT and mot-DT (p < 0.05). On the other hand, muscle activity increased in most muscles analyzed from single- to dual-task conditions (p < 0.05). In conclusion, performing a cognitive or motor task using a smartphone while walking promote a decline in spatiotemporal gait parameters performance and change muscle activity pattern compared to normal walking.

45 Quantifying gait quality changes in fragile foal syndrome carriers using artificial intelligence

The domestic horse has remarkable locomotor polymorphisms valuable to study of genetic musculoskeletal diseases and their effect on gait quality. Here we investigate a polymorphism in the PLOD1 gene, responsible for Fragile Foal Syndrome (FFS), as it impacts the organization of collagen fibers. We hypothesize that the changes in the biomechanical properties of tissues will result in change of locomotor phenotypes. We first addressed the need for a gait assessment tool that can accurately quantify various locomotor parameters. We created a pipeline built around the software package DeepLabCut (DLC), a user-friendly graphical user interface (GUI) written in Python, and a custom gait parameter calculator written in MatLab. DLC uses a pre-trained deep neural network model to apply 22 anatomical landmarks on jogging horses observed in video recordings. A custom GUI allows the user to perform error checks of the labels before the pipeline processes the raw marker coordinate files produced by DLC into geometric gait parameters. We then genotyped 138 horses in training for jumping competition by extracting DNA from the bulbs of pulled tail hair and running a PCR-RFLP test. We confirmed these genotypes via sanger sequencing. Of the 138 horses, 58 were purebred Thoroughbreds, 72 were warmbloods, and the remaining 8 were made up of stock horses. The carrier rate was n = 4 in Thoroughbreds, and n = 3in the warmbloods including an Irish Sport Horse, Sillia Argentina, and Holsteiner. We observed a FFS carrier frequency markedly higher in the Thoroughbred population than those reported in previous studies (6.9%, P = 0.015, Χ2 test). A Quadratic Discriminant Analysis then produced standardized coefficient scores for each of the 15 gait parameters to determine the best predictors of genotype within the model. The change in joint extension of both the hind and forelimb were the strongest predictors of genotype and indicated that FFS carriers had greater extension and swing of all 4 limbs. As a result, FFS carriers likely have an altered hoof flight path throughout the stride cycle. Future work will increase the sample size to capture more FFS carriers and will more precisely define the FFS locomotor phenotype. We will also apply this new phenotyping method to investigate changes in gait associated with other genetic variants for connective tissue disorders like HERDA and JEB. Improved quantification of gait parameters, and our understanding of the physiology of this and other known connective tissue disorders in the horse, will aid in future breeding and selection decisions to reduce injury risk and improve performance.

33 Assessing the effect of fatigue on stadium jumping penalty scores in elite three-day event horses utilizing artificial intelligence

Mandatory veterinary inspections assess lameness and fatigue to help predict the success of performance horses during competition. Horses competing at the international level in 3-d eventing must pass both mandatory inspections (pre-competition and post-cross country) to attempt the final phase: stadium jumping. With this in mind we hypothesize that quantifying the gait quality of horses for fatigue during the inspections will help predict if they will have faults in stadium jumping. However, these pass/fail exams are based on subjective and non-repeatable guidelines referencing the locomotor function of the horse, and do not have the ability to detect small gait changes over time. The development of artificial intelligence-based video analysis approaches allows for the objective production of quantitative scores which can be used to accurately assess the physical capability of the equine athlete. We quantified our custom gait parameter pipeline using the software package DeepLabCut (DLC) of horses at the trot during the veterinary inspections and analyzed 197 horses across 3 levels (CCI-2*, CCI-3*, and CCI-4*) and 5 venues. We used a Quadratic Discriminant Analysis to assign a standardized coefficient score, which we noted as a fatigue score, to all horses. Utilizing 3 common fatigueparameters in a multivariate model using the row-wise method we found stride length (P < 0.001) and speed (P < 0.001) had significant negative correlation probabilities, and stance time (P < 0.001) had a significant positive correlation probability with the fatigue scores. The significance supports the idea that a higher fatigue score is indicative of greater fatigue in the horse. We then applied a qualitative label to each horse, faults or no faults, where a horse with no faults had zero time and zero jump faults, and a horse with faults had any combination of the 2. Then we compared the horse's fatigue score to the qualitative label and found that horses with faults had a significantly higher (P = 0.0149, standard t-test) fatigue score suggesting that fatigue may impact stadium jumping performance more than previously appreciated. Further work investigating the impact of locomotor phenotypes and fatigue on competition performance will encourage the use of objective measures to protect sport horse welfare and improve training strategies, as well as providing the opportunity to add an objective tool to the procedures for mandatory veterinary inspections.

Dual-task changes in gait and brain activity measured in a healthy young adult population

BackgroundDual Task (DT) walking in everyday life is the norm rather than the exception. Complex cognitive-motor strategies are employed during DT and it is necessary to coordinate and regulate neural resources to ensure adequate performance. However, the underlying neurophysiology involved is not fully understood. Therefore, the aim of this study was to examine the neurophysiology and gait kinematics during DT gait. Research questionOur main research question was whether gait kinematics changed during DT walking for healthy young adults and whether this is reflected in brain activity. MethodsTen healthy young adults walked on a treadmill, performed a Flanker test while standing and performed the Flanker test while walking on a treadmill. Electroencephalography (EEG), spatial temporal, and kinematic data was recorded and analyzed. ResultsAverage alpha and beta activities were modulated during DT walking compared to single task (ST) walking while ERPs during the Flanker test showed larger P300 amplitudes and longer latencies for DT compared to standing. Cadence reduced and cadence variability increased during DT compared to ST whilst kinematic results showed that hip and knee flexions decreased, and the center of mass moved slightly back in the sagittal plane. SignificanceIt was found that healthy young adults employed a cognitive-motor strategy that included directing more neural resources to the cognitive task while adopting a more upright posture during DT walking.

Carrying children, groceries, and water across varying terrain: Changes in gait and comfortable walking speed

BackgroundCarrying items of substantial weight and value in one’s arms while traversing challenging terrain is a common task that requires considerable care. Carrying valuable (e.g., child) or variable (e.g., water) items, compared to stable ones (e.g., groceries) demands increased coordination, and is likely to lead to slower comfortable walking speed (CWS) and altered gait mechanics, especially on difficult terrain. Research questionHow are gait parameters altered by carrying items of substantial weight and varying value and dynamics across more and less demanding terrain? MethodsIn two experiments, participants carried their child, an equally weighted sack of groceries, or an open bucket of water in the same manner across level floor and across uneven stairs of varying heights with gaps between them. Kinematics were assessed for both terrains; kinetics were measured for one step up and one step down on stairs. ResultsMixed models ANOVAs with repeated measures revealed that CWS on uneven stairs was approximately 65 % of CWS for level floor, regardless of the item carried. Step-to-step coefficients of variation for step length and CWS were also greater. Water was carried most slowly, with shorter steps on level floor and reduced accelerations on uneven stairs. CWS with children and groceries did not differ. SignificanceCarrying items of weight and worth with varying dynamics across more and less challenging terrain illustrates the ecological complexity of walking. Terrain requiring greater flexibility, strength, and coordination reduced CWS substantially, a complexity-speed tradeoff. More variable, difficult to control items altered CWS and other gait patterns regardless of terrain difficulty, suggesting terrain and item dynamics contributed independently to gait adjustments. More valuable items were not carried more slowly than less valuable ones. Carrying tasks deserve greater attention in research and clinical assessment.

Axial Compressive Loading Attenuates Early Osteoarthritis by Reducing Subchondral Bone Remodeling

Background: Mechanical loading and alendronate (ALN) can be used as noninvasive physical therapy methods for osteoarthritis (OA). However, the timing and efficacy for treatments are unknown. Purpose: To determine whether the timing of mechanical loading and ALN influences the pathobiological changes of OA. Study Design: Controlled laboratory study. Methods: Mice with OA induced by anterior cruciate ligament transection were subjected to early (1-3 weeks) or late (5-7 weeks) axial compressive dynamic load or intraperitoneal injection of ALN. Changes in gait were analyzed using gait analysis system, pathobiological changes in subchondral bone, cartilage, osteophyte, and synovitis were assessed using micro–computed tomography, tartrate-resistant acid phosphatase staining, pathologic section staining, and immunohistochemistry at 1, 2, 4, and 8 weeks. Results: At 1, 2, and 4 weeks, the OA limb had lower mean footprint pressure intensity, lower bone volume per tissue volume (BV/TV) in the subchondral bone, and more osteoclasts. At 4 weeks, the early loading, ALN, and load + ALN treatments induced less cartilage destruction, with a corresponding reduction in Osteoarthritis Research Society International score and increased hyaline cartilage thickness. The treatments also resulted in fewer osteoclasts and higher BV/TV and bone mineral density of subchondral bone and suppressed inflammation and interleukin 1β– and tumor necrosis factor α-positive cells in synovium. At 8 weeks, early loading or load + ALN improved the mean footprint pressure intensity and knee flexion. At 8 weeks, early load + ALN had a synergistic effect on protecting hyaline cartilage and proteoglycans. Footprint pressure intensity and cartilage destruction were worse in late loading limbs, and no differences in BV/TV, bone mineral density, osteophyte formation, and synovium inflammation were found between the late load, ALN, and load + ALN groups and the anterior cruciate ligament transection group. Conclusion: Dynamic axial mechanical loading or ALN in the early stages of knee trauma protected against OA by suppressing subchondral bone remodeling. However, late loading promoted cartilage degeneration in advanced OA, indicating that reduced loading should be performed in the late stages of OA to avoid the acceleration of OA. Clinical Relevance: Early low-level functional exercise or antiosteoporotic drugs could clearly slow or prevent the progression of early OA. For patients with mild to severe OA, loading reduction via brace protection or maintenance of joint stability via early ligament reconstruction surgery may ameliorate OA exacerbation.

Exploring the Utility of ActiGraph in Measuring Gait Impairment and Physical Activity in Patients with MS Using Digital Biomarkers (P3-3.013)

<h3>Objective:</h3> To report findings from a pilot sub-study of the Phase 2b tolebrutinib long-term safety (LTS) study (NCT03889639) that assessed compliance with a wearable ActiGraph device and to describe the Phase 3 validation sub-study design assessing the use of actigraphy in measuring gait changes in participants with progressive multiple sclerosis (PwPMS). <h3>Background:</h3> Gait impairment is a common, clinically relevant issue for MS patients. Traditional disability assessments by Expanded Disability Status Scale [EDSS], Timed 25-Foot Walk are widely used, but more sensitive, objective, and clinically meaningful gait impairment measures are needed. <h3>Design/Methods:</h3> The LTS pilot sub-study assessed compliance with the ActiGraph device (defined as 8/14 compliant days with ≥11h/day of device wear/monitoring period) that monitored gait and activity over 4 one-month monitoring periods. The Phase 3 validation sub-study will recruit ~250 PwPMS from PERSEUS (NCT04458051) and HERCULES (NCT04411641) tolebrutinib trials. Participants will be monitored 14 days/month for ≥12 months. Primary endpoint is correlation of gait measures with standard disability progression assessments. Key gait measures include gait speed, step duration, and step length. Physical activity measures include number of steps and walking episodes. Secondary endpoints are to establish normative values for velocity, stride length, and step duration for subsets of EDSS. <h3>Results:</h3> Compliance in the Actigraphy LTS pilot sub-study was 61%–90% over 4 monitoring periods, with a mean daily wear time ranging from 5.9–14.9h. 79% of participants had a mean daily wear time of &gt;10h. Per literature reports, actigraphy gait measures were correlated with EDSS. Findings from Actigraphy LTS pilot sub-study supported the design of the Phase 3 validation sub-study. <h3>Conclusions:</h3> Actigraphy LTS pilot sub-study showed that participants can use the ActiGraph device with relatively good compliance. This Phase 3 validation sub-study will provide further clinical data on actigraphy as a more sensitive measure to track disability progression in PwPMS. <b>Disclosure:</b> Dr. Abou Zeid has nothing to disclose. Xiaoyu Jiang has received personal compensation for serving as an employee of Sanofi. Dr. Orogun has nothing to disclose. Dr. Sarker has received personal compensation for serving as an employee of Sanofi. Dr. Syed has received personal compensation for serving as an employee of Sanofi US.

Objective Measures of Gait Changes in ALS Correlate with Functional Rating Scale (P8-8.008)

Objective Measures of Gait Changes in ALS Correlate with Functional Rating Scale (P8-8.008)

Gait Parameters As Early Indicators: Exploring the Diagnostic Potential of Gait Analysis in Rare Diseases – A Preliminary Investigation On Mitochondrial Disorders

Background: Instrumented gait analysis is now increasingly used in clinical decision-making scenarios, as a marker of disease progression, as an early indicator of motor dysfunction, as a differentiating feature for diseases with same phenotype presentation and as an outcome measure for effect of interventions. This is particularly relevant for motor dysfunction in rare inherited neurological disorders which often result in gait impairment. Purpose: Several rare diseases have variable presenting features primarily manifesting as reduced quality of life and impaired function. We aim to investigate the role of gait analysis in the diagnosis of these disorders as it is often difficult and complex. Methods: This is a retrospective observational analysis of quantitative gait parameters of a 15-year-old male presenting with features of mitochondrial dysfunction, and our analysis of gait- related parameters before exercise, post exercise and in recovery phase. Results: The results depicted a few significant changes in gait analysis pattern post exercise which improved in recovery phase hinting at the potential use of gait analysis in such disorders particularly metabolic disorders. This study aims to bridge this gap by presenting three-dimensional gait parameters of a case with mitochondrial disorders and to explore its utility. Conclusions: 3D gait analysis may prove to be an adjunct in the diagnosis, classification and prognosis of rare neuromuscular diseases. It holds potential for diagnosing subtle changes in gait and quantifying the effect of treatment and rehabilitation on gait and hence functional abilities of the patients.