Gait Variability Research Articles

Assessment of lumbar disc herniation-impaired gait by using IMU data fusion method

The inertial motion unit (IMU) is an effective tool for monitoring and assessing gait impairment in patients with lumbar disc herniation(LDH). However, the current clinical assessment methods for LDH gait focus on patients’ subjective scoring indicators and lack the assessment of kinematic ability; at the same time, individual differences in the motor function degradation of the healthy and affected lower limbs of LDH patients are also ignored. To solve this problem, we propose an LDH gait feature model based on multi-source adaptive Kalman data fusion of acceleration and angular velocity. The gait phase is segmented by using an adaptive Kalman data fusion algorithm to estimate the attitude angle, and obtaining gait events through a zero-velocity update technique and a peak detection algorithm. Two IMUs were used to analyze the gait characteristics of lumbar disc patients and healthy gait people, including 12 gait characteristics such as gait spatiotemporal parameters, kinematic parameters, gait variability and stability. Statistical methods were used to analyze the characteristic model and verify the biological differences between the healthy affected side of LDH and healthy subjects. Finally, feature engineering and machine learning technology were used to identify the gait pattern of inertial movement units in patients with lumbar intervertebral disc disease, and achieved a classification accuracy of 95.50%, providing an effective gait feature set and method for clinical evaluation of LDH.

Evaluation of forelimb gait variation overground at a walk in sound and lame dogs using a combination of diagnostic techniques

BackgroundKinetic and kinematic gait analysis is increasingly practised as a part of lameness evaluation in dogs. The aim of this study was to examine the normal short- and long-term variation in forelimb gait in sound control dogs (CD) at a walk using seven selected variables of objective kinetic and kinematic gait analyses. Also, to compare the findings in CD to a group of forelimb lame dogs with elbow osteoarthritis (OAD). An additional aim was to test a kinetic based graphic method for lameness detection; symmetry squares (SS). A prospective longitudinal study was carried out on client owned CD and OAD. Clinical and orthopaedic evaluations were performed to ensure soundness and detect and grade lameness. Seven kinetic and kinematic variables and SS were tested for lameness evaluation. The CD were divided into two subgroups, CD1 and CD2, and examined twice: CD1 with two months interval and CD2 with 3–4 h interval. The OAD group was evaluated once and compared to the CD groups’ first examination.ResultsThirteen CD and 19 OAD were included. For CD1 and CD2, there were no significant differences in any examined variable between examination occasions. Total peak force/impulse symmetry and fore-hind peak force/impulse symmetry differed significantly between OAD and CD. Symmetry squares had a 74% agreement to subjective orthopaedic evaluations.ConclusionsIn CD, no difference in the examined variables was seen between examination occasions. Four out of seven objective variables differed significantly between CD and OAD. The graphic SS method might have diagnostic potential for lameness detection, making it possible to detect a shift from lame to non-lame limbs. Potentially, this might be especially helpful in bilaterally lame dogs, which often represent a clinical challenge in lameness evaluation.

Discrete Relationships between Spatiotemporal Gait Characteristics and Domain-Specific Neuropsychological Performance in Midlife.

Midlife risk factors such as type 2 diabetes mellitus (T2DM) confer a significantly increased risk of cognitive impairment in later life with executive function, memory, and attention domains often affected first. Spatiotemporal gait characteristics are emerging as important integrative biomarkers of neurocognitive function and of later dementia risk. We examined 24 spatiotemporal gait parameters across five domains of gait previously linked to cognitive function on usual-pace, maximal-pace, and cognitive dual-task gait conditions in 102 middle-aged adults with (57.5 ± 8.0 years; 40% female) and without (57.0 ± 8.3 years; 62.1% female) T2DM. Neurocognitive function was measured using a neuropsychological assessment battery. T2DM was associated with significant changes in gait phases and rhythm domains at usual pace, and greater gait variability observed during maximal pace and dual tasks. In the overall cohort, both the gait pace and rhythm domains were associated with memory and executive function during usual pace. At maximal pace, gait pace parameters were associated with reaction time and delayed memory. During the cognitive dual task, associations between gait variability and both delayed memory/executive function were observed. Associations persisted following covariate adjustment and did not differ by T2DM status. Principal components analysis identified a consistent association of slower gait pace (step/stride length) and increased gait variability during maximal-pace walking with poorer memory and executive function performance. These data support the use of spatiotemporal gait as an integrative biomarker of neurocognitive function in otherwise healthy middle-aged individuals and reveal discrete associations between both differing gait tasks and gait domains with domain-specific neuropsychological performance. Employing both maximal-pace and dual-task paradigms may be important in cognitively unimpaired populations with risk factors for later cognitive decline-with the aim of identifying individuals who may benefit from potential preventative interventions.

Effects of Cognitive-Motor and Motor-Motor Dual Tasks on Gait Performance in Older Adults with Sarcopenia.

With the advent of global aging, the health of the older population has become a critical public health challenge. The purpose of this study was to investigate the effect of dual-tasking on gait performance in patients with sarcopenia. Thirty participants with sarcopenia (age: 70.73 ± 4.12 yr, MMSE score: 26.90 ± 3.00), including 14 males and 16 females, were selected according to the diagnostic criteria of the Asian Working Group on Sarcopenia. All participants were instructed to perform the gait test in three modes: single task (ST), cognitive-motor dual task (CMDT), and motor-motor dual task (MMDT). Statistical analyses were performed using one-way ANOVA to evaluate the effects of different task types on gait parameters of the participants. (1) Compared with ST walking, gait frequency, step length, and step speed decreased, and the gait cycle and double-support phase increased in patients with sarcopenia during dual-task walking (p < 0.05); (2) Compared with ST walking, gait variability indices such as stride frequency, stride length, and support period significantly increased in patients with sarcopenia during dual-task walking (p < 0.05). The increased difficulty in postural control caused by dual-task interference may reduce the safety of motor strategies in patients with sarcopenia and increase the risk of falls. Future studies should focus on the effects of exercise interventions on multitasking patterns in people with sarcopenia to promote balance function in these populations.

Classification of gait variation under mental workload in big five personalities

BackgroundHuman behavior patterns involve mutual interactions among psychology, physiology, and stress, which are all associated with gait at different grades. Research questionsThe study aims to reveal the interrelationship among personality, mental workload, and gait patterns by capturing gait variations using inertial sensors. It also assesses individual personality traits and simulates stress to construct a gait classification model. MethodsSixty participants were instructed to perform regular, low, and high mental workload walking on the corridor to simulate a natural setting walking. Meanwhile inertial measurement units (IMUs) were placed on eight body parts. Mental workload was induced using the auditory n-back task, and their Big Five personality traits were evaluated. Gait data from IMUs were categorized into nine classifications of average, low, and high Big Five Inventory scores with three levels of mental workload walking. Subsequently, the segmentation gait data were used as input features for classifications in deep learning models, employing a sliding window long short-term memory network for nine classifications for different personality dimensions. ResultsThe results indicated average accuracies of nine classifications were 83.6 % for Openness, 84.4 % for Conscientiousness, 82.0 % for Extraversion, 85.2 % for Agreeableness, and 84.5 % for Neuroticism across all IMU placements. Remarkably, gait data from the lower back IMU achieved the highest model performance, with an average accuracy of 92.7 %, in classifying the different levels of personality and mental workload walking. In contrast, the left wrist and chest showed several misclassifications among regular, low, and high mental workload walking across personality traits. SignificanceSuccessful classification can help monitor an individual's mental state in real time and analyze personality dimensions, providing feedback and suggestions. The present study demonstrated that gait characteristics can contribute to more profound and personalized health information.

In-home Gait Abnormality Detection through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.

Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromusculoskeletal disorders such as Parkinson's and stroke. Traditional assessments in gait clinics are infrequent and pose barriers, particularly for disadvantaged populations. Previous efforts have explored sensor-based approaches for in-home gait assessments, yet they face limitations such as visual obstructions (cameras), limited coverage (pressure mats), and the need for device carrying (wearables and insoles). To overcome these limitations, we introduce an in-home gait abnormality detection system using footstep-induced floor vibrations, enabling low-cost, non-intrusive, device-free gait health monitoring. The main research challenge is the high uncertainty in floor vibrations due to gait variations among people, making it challenging to develop a generalizable model for new patients. To address this, we analyze time-frequency-domain features of floor vibration data during specific gait phases and develop a feature transformation method through contrastive learning to address the between-people gait variation challenge. Our method transforms the features from vibrations to an embedding space where samples from different people stay close to each other (robust to people variation) while normal and abnormal gait samples are far apart (sensitive to gait abnormality). After that, gait abnormalities are detected by a downstream classifier after feature transformation. We evaluated our approach through a real-world walking experiment with 21 participants and achieved an 85% to 95% mean accuracy in detecting various gait abnormalities. This novel method overcomes prior limitations in in-home gait assessments, offering accessible gait abnormality detection without the need for intrusive devices or labels for new patients.

A backward cycling programme for people with Parkinson's disease: a feasibility and preliminary results study.

To assess the feasibility of backward cycling for people with Parkinson's disease. Secondary objectives were to assess changes in gait and balance following a 6-week program. A single-group prospective pre-test, post-test study with 1-month follow-up. Twenty-six people with Parkinson's disease (mean age: 69 (7.74) years, gender: 83% males, time since diagnosis: 6 (4.44) years). Participants pedaled backward on a stationary bicycle for 30 minutes at moderate intensity twice a week for 6 weeks. Feasibility was assessed by acceptability, suitability, and burden. Data collected at pre- and post-intervention with 1-month follow-up included backward stepping response variables, forward/backward gait variables, Mini-Balance Evaluation Systems Test (MBT), and 6 Minute Walk Test. There was a high retention rate (95.8%) and adherence rate (100%) with one adverse event and minimal burden. Significant improvements were seen in step count and excursion distance during backward stepping responses, forward and backward gait velocity, forward step length, and the Mini-BESTest. Backward cycling was a feasible intervention for people with Parkinson's disease, demonstrating low burden with high retention and adherence rates, and it is a safe exercise with the potential for benefits in gait and balance variables.

The effects of rhythmic exercise using PNF patterns on gait variables in normal adults.

Maintaining gait stability is an important factor for preventing falls of normal adults. Thus, it is necessary to conduct research on gait variables in normal adults. In this study, we conducted research on the effect of rhythmic exercise using proprioceptive neuromuscular facilitation (PNF) patterns on gait variables in normal adults. Thirty-two subjects were divided into two groups, the training and control groups, with 16 subjects in each group. We measured various gait variables step time difference (STD), step length difference (SLD), single support difference (SSD), stance phase difference (STPD) and swing phase difference (SWPD) for the pre-test and post-test in each group. As a result of paired t-tests on various gait variables (STD, SLD, SSD, STPD, SWPD) of the training and control group, the training group showed significance in SLD, STPD and STD and the control group had no significance in all items. In this study, which verified the effect of rhythmic exercise using the PNF patterns on the gait variables of normal adults, there was statistical significance in SLD, STPD, and STD showing that dynamic exercise using the PNF pattern is helpful in improving the walking ability of normal adults.

Effect of manual manipulation on mechanical gait parameters.

A variety of manual manipulation techniques are utilized in clinical practice to alleviate pain and improve musculoskeletal function. Many manual practitioners analyze gait patterns and asymmetries in their assessment of the patient, and an increasing number of gait motion capture studies are taking place with recent improvements in motion capture technology. This study is the first systematic review of whether these manual modalities have been shown to produce an objectively measurable change in gait mechanics. This study was designed to perform a systematic review of the literature to assess the impact of manual medicine modalities on biomechanical parameters of gait. A master search term composed of keywords and Medical Subject Headings (MeSH) search terms from an initial scan of relevant articles was utilized to search six databases. We screened the titles and abstracts of the resulting papers for relevance and then assessed their quality with the Cochrane Risk of Bias Tool. Clinical trials that featured both a manual manipulation intervention and multiple mechanical gait parameters were included. Case reports and other studies that only measured gait speed or other subjective measures of mobility were excluded. We included 20 studies in our final analysis. They utilize manipulation techniques primarily from osteopathic, chiropractic, massage, and physiotherapy backgrounds. The conditions studied primarily included problems with the back, knee, and ankle, as well as healthy patients and Parkinson's patients. Control groups were highly variable, if not absent. Most studies measured their gait parameters utilizing either multicamera motion capture systems or force platforms. Twelve of 20 papers included in the final analysis demonstrated a significant effect of manipulation on gait variables, many of which included either step length, walking speed, or sagittal range of motion (ROM) in joints of the lower extremity. However, the results and study design are too heterogeneous to draw robust conclusions from these studies as a whole. While there are initial indications that certain modalities may yield a change in certain gait parameters, the quality of evidence is low and there is insufficient evidence to conclude that manual therapies induce changes in biomechanical gait parameters. Studies are heterogeneous with respect to the populations studied and the interventions performed. Comparators were variable or absent across the studies, as were the outcome variables measured. More could be learned in the future with consistent methodology around blinding and sham treatment, and if the gait parameters measured were standardized and of a more robust clinical significance.

Gait Variability as a Potential Motor Marker of Cerebellar Disease-Relationship between Variability of Stride, Arm Swing and Trunk Movements, and Walking Speed.

Excessive stride variability is a characteristic feature of cerebellar ataxias, even in pre-ataxic or prodromal disease stages. This study explores the relation of variability of arm swing and trunk deflection in relationship to stride length and gait speed in previously described cohorts of cerebellar disease and healthy elderly: we examined 10 patients with spinocerebellar ataxia type 14 (SCA), 12 patients with essential tremor (ET), and 67 healthy elderly (HE). Using inertial sensors, recordings of gait performance were conducted at different subjective walking speeds to delineate gait parameters and respective coefficients of variability (CoV). Comparisons across cohorts and walking speed categories revealed slower stride velocities in SCA and ET patients compared to HE, which was paralleled by reduced arm swing range of motion (RoM), peak velocity, and increased CoV of stride length, while no group differences were found for trunk deflections and their variability. Larger arm swing RoM, peak velocity, and stride length were predicted by higher gait velocity in all cohorts. Lower gait velocity predicted higher CoV values of trunk sagittal and horizontal deflections, as well as arm swing and stride length in ET and SCA patients, but not in HE. These findings highlight the role of arm movements in ataxic gait and the impact of gait velocity on variability, which are essential for defining disease manifestation and disease-related changes in longitudinal observations.

International validation of meaningfulness of postural sway and gait to assess myeloneuropathy in adults with adrenoleukodystrophy.

The most common manifestation of X-linked adrenoleukodystrophy (ALD) is a slowly progressive myeloneuropathy, which leads to imbalance and gait disturbances. The variable progression of the disease complicates evaluation of its progression rate. Wearable sensors allow for easy and frequent balance and gait collection. This study reports baseline data from a longitudinal study on the quantitative assessment of balance and gait with wearable sensors and their clinical relevance. Data were collected from adult patients in two institutions. Postural body sway and gait parameters were measured using accelerometers. Disease severity was measured by the Expanded Disability Severity Scale (EDSS). Falling frequency and quality of life (QOL) were collected in men. The relationship between sway and gait variables and EDSS score, participants' use of a walking aid, and falling frequency was evaluated. One hundred twenty individuals with ALD were included. Sway variables significantly differentiate participants' assistive device use. Sway and gait variables were correlated to the EDSS in both sexes. Both gait speed and sway were correlated with falling frequency in men from one institution. Select QOL subscores were correlated with the EDSS in males from one institution. Accelerometry generated comparable results across sites. This study confirms the clinical correlation between spinal cord disease and imbalance and gait in ALD. For the first time, this study shows clinically meaningful relationships for sway and gait with use of an assistive device, falling frequency and QOL. Wearable accelerometers are a valid means to measure sway and gait in ALD. These measures are promising outcomes for clinical trial designs to assess myeloneuropathy in ALD and to monitor disease progression in individuals.

FP-GCN: Frequency Pyramid Graph Convolutional Network for Enhancing Pathological Gait Classification.

Gait, a manifestation of one's walking pattern, intricately reflects the harmonious interplay of various bodily systems, offering valuable insights into an individual's health status. However, the current study has shortcomings in the extraction of temporal and spatial dependencies in joint motion, resulting in inefficiencies in pathological gait classification. In this paper, we propose a Frequency Pyramid Graph Convolutional Network (FP-GCN), advocating to complement temporal analysis and further enhance spatial feature extraction. specifically, a spectral decomposition component is adopted to extract gait data with different time frames, which can enhance the detection of rhythmic patterns and velocity variations in human gait and allow a detailed analysis of the temporal features. Furthermore, a novel pyramidal feature extraction approach is developed to analyze the inter-sensor dependencies, which can integrate features from different pathways, enhancing both temporal and spatial feature extraction. Our experimentation on diverse datasets demonstrates the effectiveness of our approach. Notably, FP-GCN achieves an impressive accuracy of 98.78% on public datasets and 96.54% on proprietary data, surpassing existing methodologies and underscoring its potential for advancing pathological gait classification. In summary, our innovative FP-GCN contributes to advancing feature extraction and pathological gait recognition, which may offer potential advancements in healthcare provisions, especially in regions with limited access to medical resources and in home-care environments. This work lays the foundation for further exploration and underscores the importance of remote health monitoring, diagnosis, and personalized interventions.

Full-body kinematics and head stabilisation strategies during walking in patients with chronic unilateral and bilateral vestibulopathy

Chronic imbalance is a frequent and limiting symptom of patients with chronic unilateral and bilateral vestibulopathy. A full-body kinematic analysis of the movement of patients with vestibulopathy would provide a better understanding of the impact of the pathology on dynamic tasks such as walking. Therefore, this study aimed to investigate the global body movement during walking, its variability (assessed with the GaitSD), and the strategies to stabilise the head (assessed with the head Anchoring Index). The full-body motion capture data of 10 patients with bilateral vestibulopathy (BV), 10 patients with unilateral vestibulopathy (UV), and 10 healthy subjects (HS) walking at several speeds (slow, comfortable, and fast) were analysed in this prospective cohort study. We observed only a few significant differences between groups in parts of the gait cycle (shoulder abduction–adduction, pelvis rotation, and hip flexion–extension) during the analysis of kinematic curves. Only BV patients had significantly higher gait variability (GaitSD) for all three walking speeds. Head stabilisation strategies depended on the plan of motion and walking speed condition, but BV and UV patients tended to stabilise their head in relation to the trunk and HS tended to stabilise their head in space. These results suggest that GaitSD could be a relevant biomarker of chronic instability in BV and that the head Anchoring Index tends to confirm clinical observations of abnormal head-trunk dynamics in patients with vestibulopathy while walking.

Impact of distinct cognitive domains on gait variability in individuals with mild cognitive impairment and dementia.

Gait variability is a common feature in neurodegenerative diseases and has been linked to cognitive impairment. Despite this link, the influence of specific cognitive domains, such as memory, visual spatial skills, executive function, and verbal function on gait variability is not well-understood. To investigate the predictive value of these specific cognitive domains on gait variability in people with mild cognitive impairment (MCI) and dementia during preferred and dual task walking. One hundred and two participants with either MCI or dementia underwent a comprehensive cognitive assessment and completed preferred and dual-task walking trials on a pressure-sensing walkway. Gait variability was assessed using the PKMAS software. Lower extremity function was evaluated with a self-reported validated scale. Our findings indicate that only visual spatial abilities had a moderate predictive value on gait variability [F (1, 78) = 17.30, p < 0.01, r = 0.43], both in preferred pace walking (70% direct effect) and dual-task walking (90% direct effect) (p's < 0.05). Additionally, lower extremity functional skills had a significant indirect effect (30%) on gait variability in preferred walking contexts. For individuals diagnosed with MCI or dementia, increased gait variability may be driven by deficits in visual spatial processing. An increased understanding of the role of visual spatial processing in gait variability can aid in the assessment and management of individuals with MCI or dementia, potentially leading to targeted interventions to improve mobility and safety.

Effects of Dalcroze Eurhythmics Exercise Versus Multicomponent Exercise on Physical and Cognitive Function, and Falls in Older Adults: The EPHYCOS Randomized Controlled Trial.

Currently, robust evidence is lacking to support one exercise type over another in the prevention of physical and cognitive decline and falls among older adults, primarily because of the lack of comparative trials of proven interventions. Therefore, a 12-month randomized, single-blind, comparative effectiveness trial is conducted, in which 142 older adults at high risk for falls are randomized (1:1) to receive an evidence-based Dalcroze Eurhythmics (DE) exercise program (once weekly, group-based) or an evidence-based multicomponent (MULTI) exercise program incorporating balance, functional, and strength training activities (twice weekly, group- and home-based), for 12 months. The primary outcome is gait variability under dual-task at 12 months. At 12 months, the DE group has significant improvements compared with MULTI group on gait under both dual-task (adjusted β for stride variability: -2.3, 95%CI, -3.1 to -1.4; p < 0.001) and single-task, and on a variety of secondary physical and cognitive/executive function outcomes. The adjusted hazard ratio for falls is 0.58 (95%CI, 0.37 to 0.93) for the DE group compared with MULTI group. In conclusion, DE exercise is more effective than MULTI exercise in improving physical and cognitive function and reducing falls in older adults. The mechanisms underlying DE exercise-induced benefits remain to be fully elucidated.

Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.

Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 (N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 (N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.

The clinical characteristics of cerebral small vessel disease patients with motoric cognitive risk syndrome during single- and dual-task walking

ObjectiveWe aimed to (1) identify neuroimaging biomarkers of distinguishing motoric cognitive risk syndrome (MCRS) risk among older Chinese adults with cerebral small vessel disease (CSVD) and (2) detect differences in gait parameters and neuroimaging biomarkers between CSVD individual with and without MCRS, especially during dual-task walking (DTW). MethodsWe enrolled 126 inpatients with CSVD who were divided into two groups according to MCRS status. Data on basic parameters, variability, asymmetry, and coordination were collected during single-task walking (STW) and DTW. Neuroimaging features (white matter hyperintensities, lacunes, and microbleeds) and total disease burden were calculated. Analysis of variance and logistic regression analyses were applied to assess the role of STW, DTW, and neuroimaging biomarkers in MCRS. ResultsIn total, 126 consecutive inpatients with CSVD were included (84 and 42 patients were classified as MCRS-negative and MCRS-positive, respectively). The MCRS-positive group showed poorer performance for nearly all gait parameters compared with the MCRS-negative group during cognitive DTW. Meanwhile, all gait parameters except asymmetry were assessed in participants with MCRS for significant deterioration during cognitive DTW compared with that during STW. However, only basic parameters differed between STW and cognitive DTW in participants without MCRS. A significant independent association between total CSVD scores and MCRS was also detected. ConclusionsFor CSVD patients, with higher total CSVD burden rather than any single neuroimaging marker, was linked to a greater risk of MCRS. In addition, CSVD individuals with MCRS had higher variability and phase coordination index (PCI), especially in cognitive DTW. Thus, they should concentrate more on their gait variability or coordination and reduce secondary task loads while walking in daily life, especially in cognitive secondary tasks.

Vertical locomotion improves horizontal locomotion: effects of climbing on gait and other mobility aspects in Parkinson’s disease. A secondary analysis from a randomized controlled trial

BackgroundIn the Climb Up! Head Up! trial, we showed that sport climbing reduces bradykinesia, tremor, and rigidity in mildly to moderately affected participants with Parkinson’s disease. This secondary analysis aimed to evaluate the effects of sport climbing on gait and functional mobility in this cohort.MethodsClimb Up! Head Up! was a 1:1 randomized controlled trial. Forty-eight PD participants (Hoehn and Yahr stage 2–3) either participated in a 12-week, 90-min-per-week sport climbing course (intervention group) or were engaged in regular unsupervised physical activity (control group). Relevant outcome measures for this analysis were extracted from six inertial measurement units placed on the extremities, chest, and lower back, that were worn during supervised gait and functional mobility assessments before and after the intervention. Assessments included normal and fast walking, dual-tasking walking, Timed Up and Go test, Instrumented Stand and Walk test, and Five Times Sit to Stand test.ResultsCompared to baseline, climbing improved gait speed during normal walking by 0.09 m/s (p = 0.005) and during fast walking by 0.1 m/s. Climbing also reduced the time spent in the stance phase during fast walking by 0.03 s. Climbing improved the walking speed in the 7-m- Timed Up and Go test by 0.1 m/s (p < 0.001) and the turning speed by 0.39 s (p = 0.052), the speed in the Instrumented Stand and Walk test by 0.1 m/s (p < 0.001), and the speed in the Five Times Sit to Stand test by 2.5 s (p = 0.014). There was no effect of sport climbing on gait speed or gait variables during dual-task walking.ConclusionsSport climbing improves gait speed during normal and fast walking, as well as functional mobility in people with Parkinson’s disease.Trial registration This study was registered within the U.S. National Library of Medicine (No: NCT04569981, date of registration September 30th, 2020)

The Effect of a Cognitive Dual Task on Gait Parameters among Healthy Young Adults with Good and Poor Sleep Quality: A Cross-Sectional Analysis.

Background: Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to investigate the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality. Methods: In total, 65 young adults with a mean age of 21.1 ± 2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants' sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The dual-task cost (DTC) on each gait parameter was calculated. The Mann-Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. Results: At a significance level of p < 0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC in participants with poorer sleep quality. Conclusions: These findings contribute to our perception of the significance of sleep quality in gait performance while multitasking in younger populations.

Bilateral Asymmetry of Spatiotemporal Running Gait Parameters in U14 Athletes at Different Speeds.

The assessment of leg asymmetries is gaining scientific interest due to its potential impact on performance and injury development. Athletes around puberty exhibit increased gait variability due to a non-established running pattern. This study aims to describe the asymmetries in the spatiotemporal running parameters in developmentally aged athletes. Forty athletes under 14 (U14) (22 females and 18 males) were assessed running on a treadmill at constant speeds of 12 and 14 km·h-1 for 3 min. Step length, step frequency, along with contact (CT) and flight time, both in absolute values and as a percentage of step time, were recorded using a RunScribe sensor attached to the laces of each shoe. U14 runners exhibited high bilateral symmetry in the spatiotemporal parameters of running, with mean asymmetry values (1-5.7%) lower than the intra-limb coefficient of variation (1.7-9.6%). Furthermore, bilateral asymmetries did not vary between the two speeds. An individual-based interpretation of asymmetries identified subjects with consistent asymmetries at both speeds, particularly in terms of CT and contact ratio (%, CT/step time). This study confirms the high symmetry of pubertal runners and paves the way for the application of portable running assessment technology to detect asymmetries on an individual basis.