Is gait variability reliable in older adults and Parkinson's disease? Towards an optimal testing protocol

Validation of fNIRS measurement of executive demand during walking with and without dual-task in younger and older adults and people with Parkinson's disease

BACKGROUND

Walking with a concurrent cognitive task (dual-task walking) can pose a challenge to some populations due to aging or neurodegenerative disease. These tasks require cognitive resources involving the prefrontal cortex and can be studied using functional near-infrared spectroscopy (fNIRS). An important step in understanding fNIRS measures during such walking tasks is validating that measures reflect the demands of the tasks and not confounding sources or movement artifacts.

AIM

This study aimed to investigate the validity of fNIRS measures of prefrontal cortex activity as an indicator of executive demand during usual walking (single-task) and dual-task walking against clinical and objective measures of motor behavior in young adults, older adults, and people with Parkinson's disease (PD), by evaluating several validation hypotheses.

METHODS

In total, 133 participants were recruited from younger adults (18-50 years, n = 42), older adults (≥60 years, n = 49) and people with PD (≥60 years, n = 42). Activity in the prefrontal cortex during walking with and without an auditory Stroop task was measured with fNIRS. A combined hemoglobin measure (correlation-based signal improvement, CBSI) was calculated for use in a region of interest analysis in the dorsolateral prefrontal cortex (dlPFC). Pre-registered hypotheses regarding convergent validity, discriminant validity and known group validity were tested. An exploratory analysis of different hemoglobin measures was also performed.

RESULTS

Increases in dlPFC activity were found from single- to dual-task walking in the younger adults group and from rest to single-task walking in the older adults and PD groups. In line with hypotheses, a positive relationship was found between between dlPFC activity during dual-task walking and dual-task cost in the younger adults group, as well as a positive relationship to step time variability during single-task walking and a negative relationship to walking speed during single-task walking in the PD group. However, several clinical and gait measures lacked a relationship with dlPFC activity.

CONCLUSION

The fNIRS results point towards the CBSI measure of dlPFC activity being a valid measure of executive demand during both single and dual-task walking. Some relationships between clinical and gait measures and brain activity during walking need further investigation.

Estimation of Gait Parameters in Huntington's Disease Using Wearable Sensors in the Clinic and Free-living Conditions

In Huntington's disease (HD), wearable inertial sensors could capture subtle changes in motor function. However, disease-specific validation of methods is necessary. This study presents an algorithm for walking bout and gait event detection in HD using a leg-worn accelerometer, validated only in the clinic and deployed in free-living conditions. Seventeen HD participants wore shank- and thigh-worn tri-axial accelerometers, and a wrist-worn device during two-minute walk tests in the clinic, with video reference data for validation. Thirteen participants wore one of the thigh-worn tri-axial accelerometers (AP: ActivPAL4) and the wrist-worn device for 7 days under free-living conditions, with proprietary AP data used as reference. Gait events were detected from shank and thigh acceleration using the Teager-Kaiser energy operator combined with unsupervised clustering. Estimated step count (SC) and temporal gait parameters were compared with reference data. In the clinic, low mean absolute percentage errors were observed for stride (shank/thigh: 0.6/0.9%) and stance (shank/thigh: 3.3/7.1%) times, and SC (shank/thigh: 3.1%). Similar errors were observed for proprietary AP SC (3.2%), with higher errors observed for the wrist-worn device (10.9%). At home, excellent agreement was observed between the proposed algorithm and AP software for SC and time spent walking (ICC [Formula: see text]). The wrist-worn device overestimated SC by 34.2%. The presented algorithm additionally allowed stride and stance time estimation, whose variability correlated significantly with clinical motor scores. The results demonstrate a new method for accurate estimation of HD gait parameters in the clinic and free-living conditions, using a single accelerometer worn on either the thigh or shank.

The effect of virtual reality treadmill training on obstacle crossing parameters in older adults

With increased age, walking without tripping requires greater cognitive demand. Therefore, it may be beneficial for training interventions to address and incorporate aspects of cognitive load. The purpose of this study was to compare a semi-immersive virtual reality treadmill training (VRTT) and conventional treadmill training (CTT) on obstacle clearance and trip hazard in older adults. Obstacle clearance parameters were measured with foot-mounted inertial measurement units (IMUs) and a Zeno pressure walkway. All data were processed and analyzed through custom Matlab scripts. Obstacle step height mean decreased (p = .003) in the lead limb following both training interventions. Additional significant changes were found in pre- and post-obstacle distance mean following both training interventions. Furthermore, significant correlations were found between demographic, cognitive, and functional mobility assessments and changes in dependent measures. The findings suggest that both the VRTT and CTT interventions may provide a reduction in trip risk in older adults, although through different methods.

The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability

An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen's d, comparing the application's readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89-1) and good-to-excellent reliability (ICC range, 0.77-1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58-1). Only 'step length of the impaired leg' showed poor-to-good validity (range, 0.37-0.84). Cohen's d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability.

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.

Spatiotemporal variability after stroke reflects more than just slow walking velocity

BACKGROUND

Increased spatiotemporal gait variability is considered a clinical biomarker of ageing and pathology, and a predictor of future falls. Nevertheless, it is unclear whether the increased spatiotemporal variability observed in persons with stroke is directly related to the pathology or simply reflects their choice of walking velocity.

RESEARCH QUESTION

Does increased spatiotemporal gait variability directly relate to motor coordination deficits after stroke?

METHODS

Forty persons with stroke participated in this cross-sectional study. Participants performed the lower-extremity motor coordination test (LEMOCOT) on an electronic mat equipped with force sensors. Then, participants walked for 120 s on a computerized treadmill at their comfortable walking velocity. For the LEMOCOT we used the traditional score of in-target touch count and computed the absolute and variable error around the targets. For gait variability, we extracted the standard deviation of step time, step length, step velocity, and step width. Using linear modeling, we tested the correlations of gait variability with the outcome measures from the LEMOCOT, after controlling for walking velocity.

RESULTS

The variability in step time, step length and step width correlated with walking velocity, while the variability in step velocity did not. After controlling for walking velocity, we observed that the LEMOCOT score correlated with the variance in step time, and the variable error in the LEMOCOT correlated with the variance in step length, in step width, and in step velocity. No significant correlation with any of the velocity-controlled step parameters was found for the absolute error in the LEMOCOT.

SIGNIFICANCE

Decreased performance in the LEMOCOT was associated with increased spatiotemporal variability in persons with stroke, regardless of their walking velocity. Our results demonstrate the connection between lower-extremity coordination impairments and deficits in gait function.

The impact of anxiety on gait impairments in Parkinson's disease: insights from sensor-based gait analysis

BACKGROUND

Sensor-based gait analysis provides a robust quantitative tool for assessing gait impairments and their associated factors in Parkinson's disease (PD). Anxiety is observed to interfere with gait clinically, but this has been poorly investigated. Our purpose is to utilize gait analysis to uncover the effect of anxiety on gait in patients with PD.

METHODS

We enrolled 38 and 106 PD patients with and without anxiety, respectively. Gait parameters were quantitively examined and compared between two groups both in single-task (ST) and dual-task (DT) walking tests. Multiple linear regression was applied to evaluate whether anxiety independently contributed to gait impairments.

RESULTS

During ST, PD patients with anxiety presented significantly shorter stride length, lower gait velocity, longer stride time and stance time, longer stance phase, smaller toe-off (TO) and heel-strike (HS) angles than those without anxiety. While under DT status, the differences were diminished. Multiple linear regression analysis demonstrated that anxiety was an independent factor to a serials of gait parameters, particularly ST-TO (B = -2.599, (-4.82, -0.38)), ST-HS (B = -2.532, (-4.71, -0.35)), ST-TO-CV (B = 4.627, (1.71, 7.64)), ST-HS-CV(B = 4.597, (1.66, 7.53)), ST stance phase (B = 1.4, (0.22, 2.58)), and DT stance phase (B = 1.749, (0.56, 2.94)).

CONCLUSION

Our study discovered that anxiety has a significant impact on gait impairments in PD patients, especially exacerbating shuffling steps and prolonging stance phase. These findings highlight the importance of addressing anxiety in PD precision therapy to achieve better treatment outcomes.

Guidelines for balancing the number of trials and the number of subjects to ensure the statistical power to detect variability - Implication for gait studies

Variability is one of the most crucial outcomes in human movement studies: variance and standard deviation of various parameters have been reported in numerous studies. However, in many of these studies, the numbers of trials and subjects have been intuitively determined and not justified with statistical considerations. Here, we investigated the impact of the numbers of trials and subjects on statistical power, based on the assumption that results per trial follow a normal distribution, using mathematical analysis and numerical simulation. An inverse-like relationship was observed between the number of trials and subjects required to ensure the statistical power for detecting differences in variance between subject groups or conditions. For instance, assuming a 1.2-times difference in population variance between pre-and post-training sessions as an alternative hypothesis, our simulation demonstrated that combinations of the number of subjects and trials, such as measuring 100 trials from each of 12 subjects under each condition, or measuring 20 trials from each of 60 subjects, can guarantee an 80 % of statistical power. Planning research based on such mathematical considerations will enable meaningful statistical interpretations in studies focusing on movement variability, such as gait studies.

Slowing gait during turning: how volition of modifying walking speed affects the gait pattern in healthy adults

Background

Turning during walking and volitionally modulating walking speed introduces complexity to gait and has been minimally explored.

Research question

How do the spatiotemporal parameters vary between young adults walking at a normal speed and a slower speed while making 90°, 180°, and 360° turns?

Methods

In a laboratory setting, the spatiotemporal parameters of 10 young adults were documented as they made turns at 90°, 180°, and 360°. A generalized linear model was utilized to determine the effect of both walking speed and turning amplitude.

Results

Young adults volitionally reducing their walking speed while turning at different turning amplitudes significantly decreased their cadence and spatial parameters while increasing their temporal parameters. In conditions of slower movement, the variability of certain spatial parameters decreased, while the variability of some temporal parameters increased.

Significance

This research broadens the understanding of turning biomechanics in relation to volitionally reducing walking speed. Cadence might be a pace gait constant synchronizing the rhythmic integration of several inputs to coordinate an ordered gait pattern output. Volition might up-regulate or down-regulate this pace gait constant (i.e., cadence) which creates the feeling of modulating walking speed.

Reliability of patient-specific gait profiles with inertial measurement units during the 2-min walk test in incomplete spinal cord injury

Most established clinical walking tests assess specific aspects of movement function (velocity, endurance, etc.) but are generally unable to determine specific biomechanical or neurological deficits that limit an individual's ability to walk. Recently, inertial measurement units (IMU) have been used to collect objective kinematic data for gait analysis and could be a valuable extension for clinical assessments (e.g., functional walking measures). This study assesses the reliability of an IMU-based overground gait analysis during the 2-min walk test (2mWT) in individuals with spinal cord injury (SCI). Furthermore, the study elaborates on the capability of IMUs to distinguish between different gait characteristics in individuals with SCI. Twenty-six individuals (aged 22-79) with acute or chronic SCI (AIS: C and D) completed the 2mWT with IMUs attached above each ankle on 2 test days, separated by 1 to 7 days. The IMU-based gait analysis showed good to excellent test-retest reliability (ICC: 0.77-0.99) for all gait parameters. Gait profiles remained stable between two measurements. Sensor-based gait profiling was able to reveal patient-specific gait impairments even in individuals with the same walking performance in the 2mWT. IMUs are a valuable add-on to clinical gait assessments and deliver reliable information on detailed gait pathologies in individuals with SCI.Trial registration: NCT04555759.

Minimal clinically important differences of spatiotemporal gait variables in Parkinson disease

BACKGROUND

Assessment of gait function in People with Parkinson Disease (PwPD) is an important tool for monitoring disease progression in PD. While comprehensive gait analysis has become increasingly popular, only one study, Hass et al. (2014), has established minimal clinically important differences (MCID) for one spatiotemporal variable (velocity) in PwPD.

RESEARCH QUESTION

What are the MCIDs for velocity and additional spatiotemporal variables, including mean, variability, and asymmetry of step length, time, and width?

METHODS

As part of a larger clinic-based initiative, 382 medicated, ambulatory PwPD walked on an instrumented walkway during routine clinical visits. Distribution and anchor-based methods (Unified Parkinson's Disease Rating Scale-III, Modified Hoehn and Yahr, and the mobility subsection of the Parkinson Disease Questionnaire) were used to calculate MCIDs for variables of interest in a cross-sectional approach.

RESULTS

Distribution measures for all variables are presented. Of nine gait variables, four were significantly associated with every anchor and pooled to the following values: velocity (8.2 cm/s), step length mean (3.6 cm), step length variability (0.7%), and step time variability (0.67%).

SIGNIFICANCE

The finalized MCID for velocity (8.2 cm/s) was nearly half of the MCID of 15 cm/s reported by Hass et al., potentially due to differences in calculations. These results allow for evaluations of effectiveness of interventions by providing values that are specific to changes in gait for PwPD. Alterations of methodology including different versions of clinical or walking assessments, and/or different calculation and selection of gait variables necessitate careful reasoning when using presented MCIDs.

Alprazolam Reduces Freezing of Gait (FOG) and Improves FOG-Related Gait Deficiencies

Background

Freezing of gait (FOG) is an intractable motor symptom in Parkinson's disease (PD) that increases fall risk and impairs the quality of life. FOG has been associated with anxiety, with experimental support for the notion that anxiety itself provokes FOG. We investigated the effect of acute anxiety reduction via alprazolam on FOG in PD.

Methods

In ten patients with PD, FOG, and normal cognition, we administered 0.25 mg alprazolam in one session and placebo in another, in counterbalanced order. At each session, on separate days, patients walked on a pressure-sensitive walkway. Using Oculus Rift virtual-reality goggles, patients walked along a plank that appeared to be (a) level with the floor, in the low-anxiety condition or (b) raised high above the ground, in the high-anxiety conditions. In this way, we assessed the impacts of anxiety and alprazolam (i.e., anxiety reduction) on FOG frequency and other gait parameters.

Results

FOG events appeared only in the high-anxiety conditions. Alprazolam significantly reduced subjective and objective measures of anxiety, as well as the prevalence of FOG (p = 0.05). Furthermore, alprazolam improved swing time (p < 0.05) and gait variability in all conditions, particularly during the elevated plank trials. Interpretation. Our results suggest that (1) anxiety induces FOG, and (2) alprazolam concomitantly reduces anxiety and FOG. Alprazolam further improved gait stability (i.e., swing time and gait variability). These findings reveal that anxiety triggers FOG in PD. Treating anxiety can reduce FOG and improve gait stability, potentially offering new therapeutic avenues for this intractable and disabling symptom in PD.

Vertical Ground Reaction Forces in Parkinson's Disease: A Speed-Matched Comparative Analysis with Healthy Subjects

This study aimed to investigate and compare the vertical Ground Reaction Forces (vGRFs) of patients with Parkinson's Disease (PwPD) and healthy subjects (HS) when the confounding effect of walking speed was absent. Therefore, eighteen PwPD and eighteen age- and linear walking speed-matched HS were recruited. Using plantar pressure insoles, participants walked along linear and curvilinear paths at self-selected speeds. Interestingly, PwPD exhibited similar walking speed to HS during curvilinear trajectories (p = 0.48) and similar vGRF during both linear and curvilinear paths. In both groups, vGRF at initial contact and terminal stance was higher during linear walking, while vGRF at mid-stance was higher in curvilinear trajectories. Similarly, the time to peak vGRF at each phase showed no significant group differences. The vGRF timing variability was different between the two groups, particularly at terminal stance (p < 0.001). In conclusion, PwPD and HS showed similar modifications in vGRF and a similar reduction in gait speed during curvilinear paths when matched for linear walking speed. This emphasized the importance of considering walking speed when assessing gait dynamics in PwPD. This study also suggests the possibility of the variability of specific temporal measures in differentiating the gait patterns of PwPD versus those of HS, even in the early stages of the disease.

Exploring shared neural substrates underlying cognition and gait variability in adults without dementia

BACKGROUND

High gait variability is associated with neurodegeneration and cognitive impairments and is predictive of cognitive impairment and dementia. The objective of this study was to identify cortical or subcortical structures of the brain shared by gait variability measured using a body-worn tri-axial accelerometer (TAA) and cognitive function.

METHODS

This study is a part of a larger population-based cohort study on cognitive aging and dementia. The study included 207 participants without dementia, with a mean age of 72.6, and 45.4% of them are females. We conducted standardized diagnostic interview including a detailed medical history, physical and neurological examinations, and laboratory tests for cognitive impairment. We obtained gait variability during walking using a body-worn TAA along and measured cortical thickness and subcortical volume from brain magnetic resonance (MR) images. We cross-sectionally investigated the cortical and subcortical neural structures associated with gait variability and the shared neural substrates of gait variability and cognitive function.

RESULTS

Higher gait variability was associated with the lower cognitive function and thinner cortical gray matter but not smaller subcortical structures. Among the clusters exhibiting correlations with gait variability, one that included the inferior temporal, entorhinal, parahippocampal, fusiform, and lingual regions in the left hemisphere was also associated with global cognitive and verbal memory function. Mediation analysis results revealed that the cluster's cortical thickness played a mediating role in the association between gait variability and cognitive function.

CONCLUSION

Gait variability and cognitive function may share neural substrates, specifically in regions related to memory and visuospatial navigation.

A global bibliometric and visualized analysis of gait analysis and artificial intelligence research from 1992 to 2022

Gait is an important basic function of human beings and an integral part of life. Many mental and physical abnormalities can cause noticeable differences in a person's gait. Abnormal gait can lead to serious consequences such as falls, limited mobility and reduced life satisfaction. Gait analysis, which includes joint kinematics, kinetics, and dynamic Electromyography (EMG) data, is now recognized as a clinically useful tool that can provide both quantifiable and qualitative information on performance to aid in treatment planning and evaluate its outcome. With the assistance of new artificial intelligence (AI) technology, the traditional medical environment has undergone great changes. AI has the potential to reshape medicine, making gait analysis more accurate, efficient and accessible. In this study, we analyzed basic information about gait analysis and AI articles that met inclusion criteria in the WoS Core Collection database from 1992-2022, and the VosViewer software was used for web visualization and keyword analysis. Through bibliometric and visual analysis, this article systematically introduces the research status of gait analysis and AI. We introduce the application of artificial intelligence in clinical gait analysis, which affects the identification and management of gait abnormalities found in various diseases. Machine learning (ML) and artificial neural networks (ANNs) are the most often utilized AI methods in gait analysis. By comparing the predictive capability of different AI algorithms in published studies, we evaluate their potential for gait analysis in different situations. Furthermore, the current challenges and future directions of gait analysis and AI research are discussed, which will also provide valuable reference information for investors in this field.

On the variability and dependence of human leg stiffness across strides during running and some consequences for the analysis of locomotion data

Typically, animal locomotion studies involve consecutive strides, which are frequently assumed to be independent with parameters that do not vary across strides. This assumption is often not tested. However, failing in particular to account for dependence across strides may cause an incorrect estimate of the uncertainty of the measurements and thereby lead to either missing (overestimating variance) or over-evaluating (underestimating variance) biological signals. In turn, this impacts replicability of the results because variability is accounted for differently across experiments. In this paper, we analyse the changes of a couple of measures of human leg stiffness across strides during running experiments, using a publicly available dataset. A major finding of this analysis is that the time series of these measurements of stiffness show autocorrelation even at large lags and so there is dependence between individual strides, even when separated by many intervening strides. Our results question the practice in biomechanics research of using each stride as an independent observation or of sub-selecting strides at small lags. Following the outcome of our analysis, we strongly recommend caution in doing so without first confirming the independence of the measurements across strides and without confirming that sub-selection does not produce spurious results.

Gait characteristics related to fall risk in patients with cerebral small vessel disease

Background

Falls and gait disturbance are significant clinical manifestations of cerebral small vessel disease (CSVD). However, few relevant studies are reported at present. We aimed to investigate gait characteristics and fall risk in patients with CSVD.

Methods

A total of 119 patients with CSVD admitted to the Department of Neurology at Tianjin Huanhu Hospital between 17 August 2018 and 7 November 2018 were enrolled in this study. All patients underwent cerebral magnetic resonance imaging scanning and a 2-min walking test using an OPAL wearable sensor and Mobility Lab software. Relevant data were collected using the gait analyzer test system to further analyze the time-space and kinematic parameters of gait. All patients were followed up, and univariate and multivariate logistic regression analyses were conducted to analyze the gait characteristics and relevant risk factors in patients with CSVD at an increased risk of falling.

Results

All patients were grouped according to the presence or absence of falling and fear of falling and were divided into a high-fall risk group (n = 35) and a low-fall risk group (n = 72). Logistic multivariate regression analysis showed that the toe-off angle [odds ratio (OR) = 0.742, 95% confidence interval (CI) 0.584-0.942, p < 0.05], toe-off angle coefficient of variation (CV) (OR = 0.717, 95% CI: 0.535-0.962, p < 0.05), stride length CV (OR = 1.256, 95% CI: 1.017-1.552, p < 0.05), and terminal double support CV (OR = 1.735, 95% CI: 1.271-2.369, p < 0.05) were statistically significant (p < 0.05) and were independent risk factors for high-fall risk in patients with CSVD.

Conclusion

CSVD patients with seemingly normal gait and ambulation independently still have a high risk of falling, and gait spatiotemporal-kinematic parameters, gait symmetry, and gait variability are important indicators to assess the high-fall risk. The decrease in toe-off angle, in particular, and an increase in related parameters of CV, can increase the fall risk of CSVD patients.

Developmental changes in straight gait in childhood

BACKGROUND

Understanding typical gait development is critical in developing suitable physical therapy methods for gait disorders. This study investigated the developmental changes and controlling mechanisms of straight gait.

METHODS

We conducted an experimental procedure among 90 participants, including 76 typically developing children and 14 healthy adults. The children were divided according to age into 3-4, 5-6, 7-8, and 9-10-year age groups. We created two indices to quantify straight gait using the extrapolated center of mass (XCOM; goal index, XCOMG and actual progress index, XCOMP), which were calculated and compared between the groups. Stepwise multiple regression was used to examine the effects of each gait variable on XCOMG and XCOMP. To eliminate the effects of multicollinearity, correlation coefficients were calculated for all gait variables.

RESULTS

Both XCOMG and XCOMP decreased gradually with age and were significantly larger in the 3-4 and 5-6 year groups than in the adult group. Multiple regression analysis showed that step velocity, step width, and the coefficiente of variation (CV) of the step width had independent coefficients of variation for the XCOMG, and the symmetry index of step time, step width, and the CV of the step width had independent CV for the XCOMP. These variables were selected as significant variables. The results showed that meandering gait was more pronounced at younger ages. Furthermore, straight gait observed in adulthood was achieved by the age of 7.

CONCLUSION

Pace (step velocity) and stability (step width and CV of step width) may contribute to XCOMG, which assesses the ability to proceed in the direction of the target. Stability and symmetry may contribute to XCOMP, which assesses the ability to walk straight in one's own direction of progress. Physical therapists could apply these indices in children to assess their ability to walk straight.

The contribution of walking speed versus recent stroke to temporospatial gait variability

BACKGROUND

Inconsistent results have been reported for temporospatial gait variability after stroke. Given the large differences in gait speed across stroke subjects and relative to healthy controls, it is not clear which changes in temporospatial gait variability can be ascribed to the walking speed during gait evaluation versus the consequences of stroke.

RESEARCH QUESTIONS

Does temporospatial gait variability differ between (1) stroke subjects grouped in clinically-relevant functional ambulation classes, (2) the paretic and non-paretic legs within each class, and (3) stroke and healthy subjects after controlling for gait speed?

METHODS

Stroke subjects were evaluated at their comfortable speed < 2 months post-onset and classified into the household (<40 cm/s, n = 38), limited-community (40-80 cm/s, n = 35), and full-community (>80 cm/s, n = 14) walkers. Coefficients of variation (CVs) for paretic and non-paretic stance, initial double-support, and single-support times, step length, step cadence, and step width were compared across the stroke ambulation classes and between the two legs. For the parameters with significantly different CVs between stroke subjects and 33 age-matched controls walking at very-slow and free speeds, a 1-way ANCOVA was used with the gait speed as a covariate.

RESULTS

For most step parameters, CVs were greater in slower stroke ambulation classes except for the smaller step width CV. The differences between the paretic and non-paretic legs emerged in slower walkers only. After controlling for the gait speed, CVs of stroke subjects no longer significantly differed from controls walking at very-slow speed. With controls walking at free speed, however, CVs for the paretic and non-paretic single-support times and the non-paretic step time remained significantly different.

SIGNIFICANCE

Gait is more variable at slower speeds both in stroke subjects and healthy controls. After accounting for the free gait speed, the increased variability of only a few temporal parameters may be attributed to a recent stroke.

Effects of Brain Pathologies on Spatiotemporal Gait Parameters in Patients with Mild Cognitive Impairment

BACKGROUND

Impaired gait can precede dementia. The associations between gait parameters and brain pathologies are therefore of interest.

OBJECTIVE

To explore how different brain pathologies (i.e., vascular and Alzheimer's) are associated with specific gait parameters from various gait components in persons with mild cognitive impairment (MCI), who have an increased risk of developing dementia.

METHODS

This cross-sectional study included 96 patients with MCI (mean 72, ±7.5 years; 52% women). Gait was evaluated by using an electronic walkway, GAITRite®. Four gait parameters (step velocity variability; step length; step time; stance time asymmetry) were used as dependent variables in multivariable linear regression analyses. Independent variables included Alzheimer's disease pathologies (amyloid-β and tau) by using PET imaging and white matter hyperintensities (WMH) by using MRI. Covariates included age, sex, comorbidities (and intracranial volume in analyses that includedWMH).

RESULTS

Increased tau-PET (Braak I-IV region of interest [ROI]) was associated with step velocity variability (standardized regression coefficient, β= 0.383, p < 0.001) and step length (β= 0.336, p < 0.001), which remained significant when using different Braak ROIs (I-II, III-IV, V-VI). The associations remained significant when adjusting for WMH (p < 0.001). When also controlling for gait speed, tau was no longer significantly (p = 0.168) associated with an increased step length. No significant associations between gait and Aβ-PET load or WMH were identified.

CONCLUSIONS

The results indicate that one should pay specific attention to assess step velocity variability when targeting single task gait in patients with MCI. Future studies should address additional gait variability measures and dual tasking in larger cohorts.

Spatiotemporal parameters during turning gait maneuvers of different amplitudes in young and elderly healthy adults: A descriptive and comparative study

BACKGROUND

Turning during walking adds complexity to gait and has been little investigated until now. Research question What are the differences in spatiotemporal parameters between young and elderly healthy adults performing quarter-turns (90°), half-turns (180°) and full-turns (360°)?

METHODS

The spatiotemporal parameters of 10 young and 10 elderly adults were recorded in a laboratory while turning at 90°, 180° and 360°. Two-way mixed ANOVA were performed to determine the effect of age and turning amplitude.

RESULTS

Elderly were slower and needed more steps and time to perform turns of larger amplitude than young adults. Cadence did not differ across age or across turning amplitude. Generally, in the elderly, the spatial parameters were smaller and the temporal parameters enhancing stability (i.e., double-support phase and stance/cycle ratio) were larger, especially for turns of larger amplitudes. In elderly adults, the variability of some spatial parameters was decreased, whereas the variability of some temporal parameters was increased. Stride width of the external leg showed the most substantial difference between groups. Most parameters differed between turning at 90° and turning at larger amplitudes (180°, 360°). Significance This study extends the characterization of turning biomechanics with respect to ageing. It also suggested paying particular attention to the turning amplitude. Finally, the age-related differences may pave the way for new selective rehabilitation protocols in the elderly.

Acute effects of virtual reality treadmill training on gait and cognition in older adults: A randomized controlled trial

INTRODUCTION

Everyday walking often involves walking with divided attention (i.e., dual-tasking). Exercise interventions for older adults should mimic these simultaneous physical and cognitive demands. This proof-of-concept study had a two-fold purpose: 1) identify acute cognitive and gait benefits of a single session of virtual reality treadmill training (VRTT), relative to conventional treadmill training (CTT), and 2) identify differences between those who reduced dual-task costs (i.e., responders) on gait or cognition and those who did not, after the session.

METHODS

Sixty older adults were randomized to complete a single 30-minute session of VRTT (n = 30, 71.2±6.5 years, 22 females) or CTT (n = 30, 72.0±7.7 years, 21 females). Pre- and post-exercise session, participants performed single-task walking, single-task cognitive, and dual-task walking trials while gait and cognition were recorded. Gait variables were gait speed and gait speed variability. Cognition variables were response reaction time, response accuracy, and cognitive throughput. Dual-task effects (DTE) on gait and cognition variables were also calculated.

RESULTS

Post-exercise, there were no group differences (all p>0.05). During single- and dual-task trials, both groups walked faster (single-task: F(1, 58) = 9.560, p = 0.003; dual-task: F(1, 58) = 19.228, p<0.001), responded more quickly (single-task: F(1, 58) = 5.054, p = 0.028; dual-task: F(1, 58) = 8.543, p = 0.005), and reduced cognitive throughput (single-task: F(1, 58) = 6.425, p = 0.014; dual-task: F(1, 58) = 28.152, p<0.001). Both groups also exhibited reduced DTE on gait speed (F(1, 58) = 8.066, p = 0.006), response accuracy (F(1, 58) = 4.123, p = 0.047), and cognitive throughput (F(1, 58) = 6.807, p = 0.012). Gait responders and non-responders did not differ (all p>0.05), but cognitive responders completed fewer years of education (t(58) = 2.114, p = 0.039) and better information processing speed (t(58) = -2.265, p = 0.027) than cognitive non-responders.

CONCLUSIONS

The results indicate that both VRTT and CTT may acutely improve gait and cognition. Therefore, older adults will likely benefit from participating in either type of exercise. The study also provides evidence that baseline cognition can impact training effects on DTE on cognition.

Single- and dual-task gait performance and their diagnostic value in early-stage Parkinson's disease

Background

Gait parameters are considered potential diagnostic markers of Parkinson's disease (PD). We aimed to 1) assess the gait impairment in early-stage PD and its related factors in the single-task (ST) and dual-task (DT) walking tests and 2) evaluate and compare the diagnostic value of gait parameters for early-stage PD under ST and DT conditions.

Methods

A total of 97 early-stage PD patients and 41 healthy controls (HC) were enrolled at Hwa Mei hospital. Gait parameters were gathered and compared between the two groups in the ST and DT walking test, controlling for covariates. Utilizing the receiver operating characteristic curve, diagnostic parameters were investigated.

Results

In the ST walking test, significantly altered gait patterns could be observed in early-stage PD patients in all domains of gait, except for asymmetry (P < 0.05). Compared to the ST walking test, the early-stage PD group performed poorly in the DT walking test in the pace, rhythm, variability and postural control domain (P < 0.05). Older, heavier subjects, as well as those with lower height, lower level of education and lower gait velocity, were found to have a poorer gait performance (P < 0.05). Stride length (AUC = 0.823, sensitivity, 68.0%; specificity, 85.4%; P < 0.001) and heel strike angle (AUC = 0.796, sensitivity, 71.1%; specificity, 80.5%; P < 0.001) could distinguish early-stage PD patients from HCs with moderate accuracy, independent of covariates. The diagnostic accuracy of gait parameters under ST conditions were statistically noninferior to those under DT conditions(P>0.05). Combining all gait parameters with diagnostic values under ST and DT walking test, the predictive power significantly increased with an AUC of 0.924 (sensitivity, 85.4%; specificity, 92.7%; P < 0.001).

Conclusion

Gait patterns altered in patients with early-stage PD but the gait symmetry remained preserved. Stride length and heel strike angle were the two most prominent gait parameters of altered gait in early-stage of PD that could serve as diagnostic markers of early-stage PD. Our findings are helpful to understand the gait pattern of early-stage PD and its related factors and can be conducive to the development of new diagnostic tools for early-stage PD.

Objective gait assessment in individuals with knee osteoarthritis using inertial sensors: A systematic review and meta-analysis

BACKGROUND

Objective assessment of gait using inertial sensors has shown promising results for functional evaluations in individuals with knee osteoarthritis (OA). However, the large number of possible outcome measures calls for a systematic evaluation of most relevant parameters to be used for scientific and clinical purposes.

AIM

This systematic review and meta-analysis aimed to identify gait parameters derived from inertial sensors that reflect gait deviations in individuals with knee OA compared to healthy control subjects (HC).

METHODS

A systematic search was conducted in five electronic databases (Medline, Embase, Web of Science, CINAHL, IEEE) to identify eligible articles. Risk of bias was assessed using a modified version of the Downs and Black scale. Data regarding study population, experimental procedures, and biomechanical outcomes were extracted. When a gait parameter was reported by a sufficient number of studies, a random-effects meta-analysis was conducted using the inverse variance method.

RESULTS

Twenty-three articles comparing gait between 411 individuals with knee OA and 507 HC were included. Individuals with knee OA had a lower gait speed than HC (standardized mean difference = -1.65), driven by smaller strides with a longer duration. Stride time variability was slightly higher in individuals with knee OA than in HC. Individuals with knee OA walked with a lower range of motion of the knee during the swing phase, less lumbar motion in the coronal plane, and a lower foot strike and toe-off angle compared to HC.

SIGNIFICANCE

This review shows that inertial sensors can detect gait impairments in individuals with knee OA. Large standardized mean differences found on spatiotemporal parameters support their applicability as sensitive endpoints for mobility in individuals with knee OA. More advanced measures, including kinematics of knee and trunk, may reveal gait adaptations that are more specific to knee OA, but compelling evidence was lacking.

Gait Analysis with Wearables Is a Potential Progression Marker in Parkinson's Disease

Gait disturbance is a prototypical feature of Parkinson's disease (PD), and the quantification of gait using wearable sensors is promising. This study aimed to identify gait impairment in the early and progressive stages of PD according to the Hoehn and Yahr (H-Y) scale. A total of 138 PD patients and 56 healthy controls (HCs) were included in our research. We collected gait parameters using the JiBuEn gait-analysis system. For spatiotemporal gait parameters and kinematic gait parameters, we observed significant differences in stride length (SL), gait velocity, the variability of SL, heel strike angle, and the range of motion (ROM) of the ankle, knee, and hip joints between HCs and PD patients in H-Y Ⅰ-Ⅱ. The changes worsened with the progression of PD. The differences in the asymmetry index of the SL and ROM of the hip were found between HCs and patients in H-Y Ⅳ. Additionally, these gait parameters were significantly associated with Unified Parkinson's Disease Rating Scale and Parkinson's Disease Questionnaire-39. This study demonstrated that gait impairment occurs in the early stage of PD and deteriorates with the progression of the disease. The gait parameters mentioned above may help to detect PD earlier and assess the progression of PD.

Association of Muscle Mass, Muscle Strength, and Muscle Function with Gait Ability Assessed Using Inertial Measurement Unit Sensors in Older Women

Aging-related muscle atrophy is associated with decreased muscle mass (MM), muscle strength (MS), and muscle function (MF) and may cause motor control, balance, and gait pattern impairments. This study determined associations of three speed-based gait variables with loss of MM, MS, and MF in older women. Overall, 432 older women aged ≥65 performed appendicular skeletal muscle, handgrip strength, and five times sit-to-stand test to evaluate MM, MS, and MF. A gait test was performed at three speeds by modifying the preferred walking speed (PWS; slower walking speed (SWS); faster-walking speed (FWS)) on a straight 19 m walkway. Stride length (SL) at PWS was significantly associated with MM. FWS and coefficient of variance (CV) of double support phase (DSP) and DSP at PWS showed significant associations with MS. CV of step time and stride time at SWS, FWS, and single support phase (SSP) at PWS showed significant associations with MF. SL at PWS, DSP at FWS, CV of DSP at PWS, stride time at SWS, and CV of SSP at PWS showed significant associations with composite MM, MS, and MF variables. Our study indicated that gait tasks under continuous and various speed conditions are useful for evaluating MM, MS, and MF.

Does cognitive loading interfere with walking control?

BACKGROUND

Cognitive-motor interference is a common method used to investigate the cognitive demands of human walking. Using this methodology, consistent effects emerge: under cognitive load, walking velocity decreases, while spatio-temporal variability of walking increases. These effects are often interpreted as indicative of an interference in the ability to control gait. However, walking velocity is highly correlated with most gait parameters; thus, the increase in variability does not necessarily reflect reduced control, but rather a constant signal-to-noise ratio.

METHODS

To investigate the effect of cognitive loading on gait variability, we retrospectively analysed 3721 records of healthy young adults, walking with and without a concurrent cognitive task, on a treadmill.

RESULTS

Stride duration and length increased under cognitive load, while the variability of these parameters decreased. Further, these effects were different between participants starting to walk without cognitive loading and those starting to walk with cognitive loading.

CONCLUSIONS

Dual tasking is more likely to divert the focus of attention away from the walking task, causing a shift of balance between automatic and conscious control, as opposed to interference per-se.

Analysing Gait Patterns in Degenerative Lumbar Spine Disease Using Inertial Wearable Sensors: An Observational Study

OBJECTIVE

Using a chest-based inertial wearable sensor, we examined the quantitative gait patterns associated with lumbar disc herniation (LDH), lumbar spinal stenosis (LSS), and chronic mechanical low back pain (CMLBP). 'Pathological gait signatures' were reported as statistically significant group difference (%) from the 'normative' gait values of an age-matched control population.

METHODS

A sample of patients presenting to the Prince of Wales Private Hospital (Sydney, Australia) with primary diagnoses of LDH, LSS, or CMLBP were recruited. Spatial, temporal, asymmetry, and variability metrics were compared with age-matched (±2 years) control participants recruited from the community. Participants were fitted at the sternal angle with an inertial measurement unit, MetaMotionC, and walked unobserved (at a self-selected pace) for 120 m along an obstacle-free, carpeted hospital corridor.

RESULTS

LDH, CMLBP, and LSS groups had unique pathological signatures of gait impairment. The LDH group (n = 33) had marked asymmetry in terms of step length, step time, stance, and single-support asymmetry. The LDH group also involved gait variability with increased step length variation. However, distinguishing the CMLBP group (n = 33) was gait variability in terms increased single-support time variation. The gait of participants with LSS (n = 22) was both asymmetric and variable in step length.

CONCLUSIONS

Wearable sensor-based accelerometry was found to be capable of detecting the gait abnormalities present in patients with LDH, LSS, and CMLBP, when compared to age-matched controls. Objective and quantitative patterns of gait deterioration uniquely varied between these subtypes of lumbar spine disease. With further testing and validation, gait signatures may aid clinical identification of gait-altering pathologies.

Treadmill training and physiotherapy similarly improve dual task gait performance: a randomized-controlled trial in Parkinson's disease

Motor-cognitive dual tasks are used to investigate the interplay between gait and cognition. Dual task walking in patients with Parkinson’s disease (PD) results in decreased gait speed and more importantly in an increased fall risk. There is evidence that physical training may improve gait during dual task challenge. Physiotherapy and treadmill walking are known to improve single task gait. The aim of this study was to investigate the impact of individualized physiotherapy or treadmill training on gait during dual task performance. 105 PD patients were randomly assigned to an intervention group (physiotherapy or treadmill). Both groups received 10 individual interventional sessions of 25 min each and additional group therapy sessions for 14 days. Primary outcome measure was the dual task gait speed. Secondary outcomes were additional gait parameters during dual task walking, UPDRS-III, BBS and walking capacity. All gait parameters were recorded using sensor-based gait analysis. Gait speed improved significantly by 4.2% (treadmill) and 8.3% (physiotherapy). Almost all secondary gait parameters, UPDRS-III, BBS, and walking capacity improved significantly and similarly in both groups. However, interaction effects were not observed. Both interventions significantly improved gait in patients with mild to moderate PD. However, treadmill walking did not show significant benefits compared to individualized physiotherapy. Our data suggest that both interventions improve dual task walking and therefore support safe and independent walking. This result may lead to more tailored therapeutic preferences.

Walking orientation randomness metric (WORM) score: pilot study of a novel gait parameter to assess walking stability and discriminate fallers from non-fallers using wearable sensors

Background

Musculoskeletal disorders can contribute to injurious falls and incur significant societal and healthcare burdens. Identification of fallers from non-fallers through wearable-based gait analysis can facilitate timely intervention to assist mobility and prevent falls whilst improving care and attention for high fall-risk patients. In this study, we use wearable sensor-based gait analysis to introduce a novel variable to assess walking stability in fallers and non-fallers – the Walking Orientation Randomness Metric. The WORM score quantifies the stability, or ‘figure-of-eight’ motion of a subject’s trunk during walking as an indicator of a falls-predictive (pathological) gait.

Methods

WORM is calculated as the ‘figure-of-eight’ oscillation mapped out in the transverse-plane by the upper body’s centre-point during a walking bout. A sample of patients presenting to the Prince of Wales Hospital (Sydney, Australia) with a primary diagnosis of “falls for investigation” and age-matched healthy controls (non-fallers) from the community were recruited. Participants were fitted at the sternal angle with the wearable accelerometer, MetaMotionC (Mbientlab Inc., USA) and walked unobserved (at self-selected pace) for 5-50 m along an obstacle-free, carpeted hospital corridor.

Results

Participants comprised of 16 fallers (mean age: 70 + 17) and 16 non-fallers (mean age: 70 + 9) based on a recent fall(s) history. The (median) WORM score was 17-fold higher (p < 0.001) in fallers (3.64 cm) compared to non-fallers (0.21 cm). ROC curve analyses demonstrate WORM can discriminate fallers from non-fallers (AUC = 0.97). Diagnostic analyses (cut-off > 0.51 cm) show high sensitivity (88%) and specificity (94%).

Conclusion

In this pilot study we have introduced the WORM score, demonstrating its discriminative performance in a preliminary sample size of 16 fallers. WORM is a novel gait metric assessing walking stability as measured by truncal way during ambulation and shows promise for objective and clinical evaluation of fallers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05211-1.

Gait‐Related Metabolic Covariance Networks at Rest in Parkinson's Disease

Background

Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted.

Objective

The aim of this study was to identify neural networks of discrete gait impairments in PD.

Methods

Fifty‐five participants with early‐stage PD and 20 age‐matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [¹⁸F]‐2‐fluoro‐2‐deoxyglucose‐positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD.

Results

In PD, we identified two metabolic gait‐related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity.

Conclusions

We have identified two novel gait‐related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Overground versus treadmill walking in Parkinson's disease: Relationship between speed and spatiotemporal gait metrics

BACKGROUND

Treadmills provide a safe and convenient way to study the gait of people with Parkinson's disease (PD), but outcome measures derived from treadmill gait may differ from overground walking.

OBJECTIVE

To investigate how the relationships between gait metrics and walking speed vary between overground and treadmill walking in people with PD and healthy controls.

METHODS

We compared 29 healthy controls to 27 people with PD in the OFF-medication state. Subjects first walked overground on an instrumented gait walkway, then on an instrumented treadmill at 85%, 100% and 115% of their overground walking speed. Average stride length and cadence were computed for each subject in both overground and treadmill walking.

RESULTS

Stride length and cadence both differed between overground and treadmill walking. Regressions of stride length and cadence on gait speed showed a log-log relationship for both overground and treadmill gait in both PD and control groups. The difference between the PD and control groups during overground gait was maintained for treadmill gait, not only when treadmill speed matched overground speed, but also with ± 15% variation in treadmill speed from that value.

SIGNIFICANCE

These results show that the impact of PD on stride length and cadence and their relationship to gait speed is preserved in treadmill as compared to overground walking. We conclude that a treadmill protocol is suitable for laboratory use in studies of PD gait therapeutics.

Analysing gait patterns in degenerative lumbar spine diseases: a literature review

OBJECTIVES

To collate the current state of knowledge and explore differences in the spatiotemporal gait patterns of degenerative lumbar spine diseases: lumbar spinal stenosis (LSS), lumbar disc herniation (LDH) and low back pain (LBP).

BACKGROUND

LBP is common presenting complaint with degenerative lumbar spine disease being a common cause. In particular, the gait patterns of LSS, LDH and mechanical-type (facetogenic and discogenic) LBP is not established.

METHODS

A search of the literature was conducted to determine the changes in spatial and temporal gait metrics involved with each type of degenerative lumbar spine disease. A search of databases including Medline, Embase and PubMed from their date of inception to April 18th, 2021 was performed to screen, review and identify relevant studies for qualitative synthesis. Seventeen relevant studies were identified for inclusion in the present review. Of these, 5 studies investigated gait patterns in LSS, 10 studies investigated LBP and 2 studies investigated LDH. Of these, 4 studies employed wearable accelerometry in LSS (2 studies) and LBP (2 studies).

CONCLUSIONS

Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. LSS is characterised by asymmetry and variability. Spatiotemporal gait deterioration in gait velocity, cadence with increased double-support duration and gait variability are distinguishing features in LDH. LBP involves marginal abnormalities in temporal and spatial gait metrics. Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. Gait asymmetry and variability, may be relevant metrics for distinguishing between the gait profiles of lumbar spine diseases.

Components of gait in people with and without mild cognitive impairment

BACKGROUND

Several objective gait parameters are associated with cognitive impairment, but there is limited knowledge of gait models in people with mild cognitive impairment (MCI).

RESEARCH QUESTION

How can 18 objective gait characteristics be used to define different components of gait in people with MCI (with suspected incipient neurocognitive disorder) and cognitively unimpaired people (CU), respectively?

METHODS

Spatiotemporal gait data were collected by using an electronic walkway (GAITRite®), i.e. assessments in comfortable gait speed. Using cross-sectional gait data, two principal component analyses (PCA) were performed (varimax rotation) to define different components of gait in people with MCI (n = 114) and CU (n = 219), respectively, from the BioFINDER-2 study.

RESULTS

Both PCAs produced four components, here called Variability, Pace/Stability, Rhythm and Asymmetry. Total variance explained was 81.0% (MCI) versus 80.3% (CU). The Variability component explained the largest amount of variance (about 25%) in both groups. The highest loading gait parameter was the same for both groups in three out of four components, i.e. step velocity variability (Variability), mean step length (Pace/Stability) and mean step time (Rhythm). In the asymmetry component, stance time asymmetry (MCI) and swing time asymmetry (CU) loaded the highest.

SIGNIFICANCE

The gait components seem similar in people with and without MCI, although there were some differences. This study may aid the identification of gait variables that represent different components of gait. Gait parameters such as step velocity variability, mean step length, mean step time as well as swing and stance time asymmetry could serve as interesting core variables of different gait components in future research in people with MCI (with suspected incipient neurocognitive disorder) and CU. However, the selection of gait variables depends on the purpose. It needs to be noted that assessment of variability measures requires more advanced technology than is usually used in the clinic.

Exploring Inertial-Based Wearable Technologies for Objective Monitoring in Sports-Related Concussion: A Single-Participant Report

OBJECTIVE

Challenges remain in sports-related concussion (SRC) assessment to better inform return to play. Reliance on self-reported symptoms within the Sports Concussion Assessment Tool means that there are limited data on the effectiveness of novel methods to assess a player's readiness to return to play. Digital methods such as wearable technologies may augment traditional SRC assessment and improve objectivity in making decisions regarding return to play.

METHODS

The participant was a male university athlete who had a recent history of SRC. The single-participant design consisted of baseline laboratory testing immediately after SRC, free-living monitoring, and follow-up supervised testing after 2 months. The primary outcome measures were from traditional assessment (eg, Sports Concussion Assessment Tool and 2-minute instrumented walk/gait test; secondary outcome measures were from remote (free-living) assessment with a single wearable inertial measurement unit (eg, for gait and sleep).

RESULTS

The university athlete (age = 20 years, height = 175 cm, weight = 77 kg [176.37 lb]) recovered and returned to play 20 days after SRC. Primary measures returned to baseline levels after 12 days. However, supervised (laboratory-based) wearable device assessment showed that gait impairments (increased step time) remained even after the athlete was cleared for return to play (2 months). Similarly, a 24-hour remote gait assessment showed changes in step time, step time variability, and step time asymmetry immediately after SRC and at return to play (1 month after SRC). Remote sleep analysis showed differences in sleep quality and disturbance (increased movement between immediately after SRC and once the athlete had returned to play [1 month after SRC]).

CONCLUSION

The concern about missed or delayed SRC diagnosis is growing, but methods to objectively monitor return to play after concussion are still lacking. This report showed that wearable device assessment offers additional objective data for use in monitoring players who have SRC. This work could better inform SRC assessment and return-to-play protocols.

IMPACT

Digital technologies such as wearable technologies can yield additional data that traditional self-report approaches cannot. Combining data from nondigital (traditional) and digital (wearable) methods may augment SRC assessment for improved return-to-play decisions.

LAY SUMMARY

Inertia-based wearable technologies (eg, accelerometers) may be useful to help augment traditional, self-report approaches to sports-related concussion assessment and management by better informing return-to-play protocols.

[Assessment of mobility-Geriatric assessment instruments for mobility impairments and perspectives of instrumentation]

Mobility and its limitations play an important role in the quality of life of geriatric patients and influence activity and participation. The assessment of mobility is therefore of particular importance for treatment and treatment planning in geriatric patients. There is a variety of assessment tools that cannot be used in every patient group, e.g. due to floor effects. This article provides an overview of common assessment tools and facilitates the evaluation and use of these tools. Special consideration is given to performance-oriented aspects and current technical developments such as wearables.

Smart Eyeglasses: A Valid and Reliable Device to Assess Spatiotemporal Parameters during Gait

The study aims to determine the validity and reproducibility of step duration and step length parameters measured during walking in healthy participants using an accelerometer embedded in smart eyeglasses. Twenty young volunteers participated in two identical sessions comprising a 30 s gait assessment performed at three different treadmill speeds under two conditions (i.e., with and without a cervical collar). Spatiotemporal parameters (i.e., step duration and step length normalized by the lower limb length) were obtained with both the accelerometer embedded in smart eyeglasses and an optoelectronic system. The relative intra- and inter-session reliability of step duration and step length computed from the vertical acceleration data were excellent for all experimental conditions. An excellent absolute reliability was observed for the eyeglasses for all conditions and concurrent validity between systems was observed. An accelerometer incorporated in smart eyeglasses is accurate to measure step duration and step length during gait.

Virtual reality doorway and hallway environments alter gait kinematics in people with Parkinson disease and freezing

BACKGROUND

Many people with Parkinson disease (PD) experience freezing of gait (FoG), a transient gait disturbance associated with increased fall risk and reduced quality of life. Head-mounted virtual reality (VR) systems allow overground walking and can create immersive simulations of physical environments that induce FoG.

RESEARCH QUESTION

For people with PD who experience FoG (PD+FoG), are kinematic gait changes observed in VR simulations of FoG-provoking environments?

METHODS

In a cross-sectional experiment, people with PD+FoG walked at their self-selected speed in a physical laboratory and virtual laboratory, doorway, and hallway environments. Motion analysis assessed whole-body kinematics, including lower extremity joint excursions, swing phase toe clearance, trunk flexion, arm swing, sagittal plane inclination angle, and spatiotemporal characteristics. One-way repeated measures analysis of variance was conducted to examine the effects of environment on gait variables, with planned contrasts between laboratory environments and the virtual doorway and hallway.

RESULTS

Twelve participants with PD+FoG (mean age [standard deviation]=72.8 [6.5] years, disease duration=8.8 [8.9] years, 3 females) completed the protocol. The environment had significant and widespread effects on kinematic and spatiotemporal variables. Compared to the physical laboratory, reduced joint excursions were observed in the ankle, knee, and hip when walking in the virtual doorway and in the knee and hip when walking in the virtual hallway. In both the virtual doorway and hallway compared to the physical laboratory, peak swing phase toe clearance, arm swing, and inclination angle were reduced, and walking was slower, with shorter, wider steps.

SIGNIFICANCE

Virtual doorway and hallway environments induced kinematic changes commonly associated with FoG episodes, and these kinematic changes are consistent with forward falls that are common during FoG episodes. Combined with the flexibility of emerging VR technology, this research supports the potential of VR applications designed to improve the understanding, assessment, and treatment of FoG.

Self-paced treadmills do not allow for valid observation of linear and nonlinear gait variability outcomes in patients with Parkinson's disease

BACKGROUND

Due to the imposed constant belt speed, motorized treadmills are known to affect linear and nonlinear gait variability outcomes. This is particularly true of patients with Parkinson's Disease where the treadmill can act as an external pacemaker. Self-paced treadmills update the belt speed in response to the subject's walking speed and might, therefore, be a useful tool for measurement of gait variability in this patient population. This study aimed to compare gait variability during walking at self-paced and constant treadmill speeds with overground walking in individuals with PD and individuals with unimpaired gait.

METHODS

Thirteen patients with Parkinson's Disease and thirteen healthy controls walked under three conditions: overground, on a treadmill at a constant speed, and using three self-paced treadmill modes. Gait variability was assessed with coefficient of variation (CV), sample entropy (SampEn), and detrended fluctuation analysis (DFA) of stride time and length. Systematic and random error between the conditions was quantified.

RESULTS

For individuals with PD, error in variability measurement was less during self-paced modes compared with constant treadmill speed for stride time but not for stride length. However, there was substantial error for stride time and length variability for all treadmill conditions. For healthy controls the error in measurement associated with treadmill walking was substantially less.

SIGNIFICANCE

The large systematic and random errors between overground and treadmill walking prohibit meaningful gait variability observations in patients with Parkinson's Disease using self-paced or constant-speed treadmills.

Clinical Features in Parkinson's Disease Patients with Hyperechogenicity in Substantia Nigra: A Cross-Sectional Study

BACKGROUND

Transcranial ultrasound (TCS) can be used to reveal structural changes in the substantia nigra (SN) and is a potential tool for the early diagnosis of Parkinson's disease (PD). This study aimed to explore the relationship between substantia nigra hyperechogenicity (SNH) and the clinical features of PD patients.

METHODS

A total of 96 PD patients were included in our study. All patients were detected by TCS and divided into two groups: PD patients with SNH (PDSN+) and those with normal SN echogenicity (PDSN-). The Unified Parkinson's Disease Rating Scale (UPDRS) and the Hoehn & Yahr stage were used to assess the extent of disease-related disability of the PD patients. Non-motor symptoms were evaluated by using several scales. The instrumented stand and walk test was performed on all subjects, and gait data were gathered using a JiBuEn gait analysis system.

RESULTS

Seventy-five PD patients were successfully assessed by TCS. We found that SNH was associated with a higher UPDRS II scores (p = 0.028). In addition, compared with PDSN- group, the PDSN+ group exhibited more severe gait impairment, including increased variability in stride length (p = 0.042), decreased heel strike angle (p = 0.017), decreased range of motion of hip joints (p = 0.031), and a more asymmetrical walking pattern (p = 0.028).

CONCLUSION

Our study demonstrated that SNH significantly correlated with activities of daily living and gait impairment in Chinese patients with PD, suggesting the formation of SNH might be a dynamic biomarker reflecting disease severity.

OUP accepted manuscript

People with Parkinson’s disease who have elevated muscle activity during rapid eye movement sleep (REM sleep without atonia) typically have a worse motor and cognitive impairment compared with those with normal muscle atonia during rapid eye movement sleep. This study used tract-based spatial statistics to compare diffusion MRI measures of fractional anisotropy, radial, mean and axial diffusivity (measures of axonal microstructure based on the directionality of water diffusion) in white matter tracts between people with Parkinson’s disease with and without rapid eye movement sleep without atonia and controls and their relationship to measures of motor and cognitive function. Thirty-eight individuals with mild-to-moderate Parkinson’s disease and 21 matched control subjects underwent ultra-high field MRI (7 T), quantitative motor assessments of gait and bradykinesia and neuropsychological testing. The Parkinson’s disease cohort was separated post hoc into those with and without elevated chin or leg muscle activity during rapid eye movement sleep based on polysomnography findings. Fractional anisotropy was significantly higher, and diffusivity significantly lower, in regions of the corpus callosum, projection and association white matter pathways in the Parkinson’s group with normal rapid eye movement sleep muscle tone compared with controls, and in a subset of pathways relative to the Parkinson’s disease group with rapid eye movement sleep without atonia. The Parkinson’s disease group with elevated rapid eye movement sleep muscle tone showed significant impairments in the gait and upper arm speed compared with controls and significantly worse scores in specific cognitive domains (executive function, visuospatial memory) compared with the Parkinson’s disease group with normal rapid eye movement sleep muscle tone. Regression analyses showed that gait speed and step length in the Parkinson’s disease cohort were predicted by measures of fractional anisotropy of the anterior corona radiata, whereas elbow flexion velocity was predicted by fractional anisotropy of the superior corona radiata. Visuospatial memory task performance was predicted by the radial diffusivity of the posterior corona radiata. These findings show that people with mild-to-moderate severity of Parkinson’s disease who have normal muscle tone during rapid eye movement sleep demonstrate compensatory-like adaptations in axonal microstructure that are associated with preserved motor and cognitive function, but these adaptations are reduced or absent in those with increased rapid eye movement sleep motor tone.

Proposed objective scoring algorithm for clinical evaluation of walking asymmetry in lumbar disc herniation, based on relevant gait metrics from wearable devices: The Gait Symmetry Index (GSiTM) – Observational study

•

The proposed GSi algorithm aims to objectively evaluate the walking impairment associated with lumbar disc herniation (LDH).

•

GSi is calculated as deviation from mean (age-matched) normative values for gait velocity, step time asymmetry and step length asymmetry.

•

Clinical performance was assessed in a prospective, single surgeon series of 33 lumbar disc herniation (LDH) patients.

•

GSi was lower in LDH participants with significant distribution between surgical and conservative management subgroups.

Validation of shoe-worn Gait Up Physilog®5 wearable inertial sensors in adolescents

BACKGROUND

Gait Up Physilog® wearable inertial sensors are a powerful alternative to traditional laboratory-based gait assessment for children with gait impairment. To build clinician trust in these devices and ultimately facilitate their use outside confined spaces, studies have examined performance of previous versions of Physilog® wearable inertial sensors but predominant focus has been on older adults. Despite their different gait patterns and behavioural/cognitive profiles, there are limited studies in children.

RESEARCH QUESTION

To determine whether key spatiotemporal gait parameters (stride length, time and velocity) collected by shoe-worn Physilog®5 sensors in a hallway assessment protocol are a valid method of gait assessment in typically developing adolescents aged 12-15 years.

METHODS

A total 30 typically developing participants (50 % female) median age 13.7 (interquartile range 2.34) were assessed in an exploratory study whilst walking at self-selected speed over the GAITRite® electronic walkway, concurrently wearing Physilog®5 sensors. Concurrent validity was analysed by Lin's concordance correlation coefficient (CCC), Bland-Altman plots and 95 % limit of agreement. Systematic bias was assessed using 95 % confidence interval of the mean difference.

RESULTS

Mean stride data demonstrated substantial agreement for stride length (CCC = 0.975) and stride velocity (CCC = 0.979) to almost perfect agreement for stride time (CCC > 0.996). Agreement between the technologies for individual stride-to-stride data remained high for stride time (CCC = 0.952); yet reduced for stride length (CCC = 0.868) and stride velocity (CCC = 0.877). Male/female differences in performance of the technology were observed for stride velocity, favouring females.

SIGNIFICANCE

Physilog®5 inertial sensors accurately measure walking in adolescents, with stride time the most accurately detected parameter. This demonstrates that wearables can be used by researchers and clinicians working with adolescent groups as an alternative to fixed systems. These findings will ultimately pave the way to using wearables for assessments with children outside of the laboratory environment.

Validity and Reliability of a Smartphone App for Gait and Balance Assessment

Advances in technology provide an opportunity to enhance the accuracy of gait and balance assessment, improving the diagnosis and rehabilitation processes for people with acute or chronic health conditions. This study investigated the validity and reliability of a smartphone-based application to measure postural stability and spatiotemporal aspects of gait during four static balance and two gait tasks. Thirty healthy participants (aged 20–69 years) performed the following tasks: (1) standing on a firm surface with eyes opened, (2) standing on a firm surface with eyes closed, (3) standing on a compliant surface with eyes open, (4) standing on a compliant surface with eyes closed, (5) walking in a straight line, and (6) walking in a straight line while turning their head from side to side. During these tasks, the app quantified the participants’ postural stability and spatiotemporal gait parameters. The concurrent validity of the smartphone app with respect to a 3D motion capture system was evaluated using partial Pearson’s correlations (r_p) and limits of the agreement (LoA%). The within-session test–retest reliability over three repeated measures was assessed with the intraclass correlation coefficient (ICC) and the standard error of measurement (SEM). One-way repeated measures analyses of variance (ANOVAs) were used to evaluate responsiveness to differences across tasks and repetitions. Periodicity index, step length, step time, and walking speed during the gait tasks and postural stability outcomes during the static tasks showed moderate-to-excellent validity (0.55 ≤ r_p ≤ 0.98; 3% ≤ LoA% ≤ 12%) and reliability scores (0.52 ≤ ICC ≤ 0.92; 1% ≤ SEM% ≤ 6%) when the repetition effect was removed. Conversely, step variability and asymmetry parameters during both gait tasks generally showed poor validity and reliability except step length asymmetry, which showed moderate reliability (0.53 ≤ ICC ≤ 0.62) in both tasks when the repetition effect was removed. Postural stability and spatiotemporal gait parameters were found responsive (p < 0.05) to differences across tasks and test repetitions. Along with sound clinical judgement, the app can potentially be used in clinical practice to detect gait and balance impairments and track the effectiveness of rehabilitation programs. Further evaluation and refinement of the app in people with significant gait and balance deficits is needed.

A pathophysiological model of gait captures the details of the impairment of pace/rhythm, variability and asymmetry in Parkinsonian patients at distinct stages of the disease

Locomotion in people with Parkinson' disease (pwPD) worsens with the progression of disease, affecting independence and quality of life. At present, clinical practice guidelines recommend a basic evaluation of gait, even though the variables (gait speed, cadence, step length) may not be satisfactory for assessing the evolution of locomotion over the course of the disease. Collecting variables into factors of a conceptual model enhances the clinical assessment of disease severity. Our aim is to evaluate if factors highlight gait differences between pwPD and healthy subjects (HS) and do it at earlier stages of disease compared to single variables. Gait characteristics of 298 pwPD and 84 HS able to walk without assistance were assessed using a baropodometric walkway (GAITRite®). According to the structure of a model previously validated in pwPD, eight spatiotemporal variables were grouped in three factors: pace/rhythm, variability and asymmetry. The model, created from the combination of three factor scores, proved to outperform the single variables or the factors in discriminating pwPD from HS. When considering the pwPD split into the different Hoehn and Yahr (H&Y) stages, the spatiotemporal variables, factor scores and the model showed that multiple impairments of gait appear at H&Y stage 2.5, with the greatest difference from HS at stage 4. A contrasting behavior was found for the asymmetry variables and factor, which showed differences from the HS already in the early stages of PD. Our findings support the use of factor scores and of the model with respect to the single variables in gait staging in PD.

Detection of Unsupervised Standardized Gait Tests From Real-World Inertial Sensor Data in Parkinson's Disease

Gait tests as part of home monitoring study protocols for patients with movement disorders may provide valuable standardized anchor-points for real-world gait analysis using inertial measurement units (IMUs). However, analyzing unsupervised gait tests relies on reliable test annotations by the patients requiring a potentially error-prone interaction with the recording system. To overcome this limitation, this work presents a novel algorithmic pipeline for the automated detection of unsupervised standardized gait tests from continuous real-world IMU data. In a study with twelve Parkinson's disease patients, we recorded real-world gait data over two weeks using foot-worn IMUs. During continuous daily recordings, the participants performed series of three consecutive 4×10 -Meters-Walking-Tests ( 4×10 MWTs) at different walking speeds, besides their usual daily-living activities. The algorithm first detected these gait test series using a gait sequence detection algorithm, a peak enhancement pipeline, and subsequence Dynamic Time Warping and then decomposed them into single 4×10 MWTs based on the walking speed. In the evaluation with 419 available gait test series, the detection reached an F1-score of 88.9% and the decomposition an F1-score of 94.0%. A concurrent validity evaluation revealed very good agreement between spatio-temporal gait parameters derived from manually labelled and automatically detected 4×10 MWTs. Our algorithm allows to remove the burden of system interaction from the patients and reduces the time for manual data annotation for researchers. The study contributes to an improved automated processing of real-world IMU gait data and enables a simple integration of standardized tests into continuous long-term recordings. This will help to bridge the gap between supervised and unsupervised gait assessment.

Adaptation of bilateral coordination of gait during split belt walking as reflected by the phase coordination index

BACKGROUND

The Split belt treadmill (SBTM) has recently been used in research and rehabilitation to study and utilize gait adaptations. The Phase coordination index (PCI) is useful in assessing bilateral coordination of gait by quantifying the consistency and accuracy in generating the anti-phased left-right stepping pattern. Recently we proposed that 23 strides are sufficient to reliably characterize PCI values from regular over ground and treadmill walking RESEARCH QUESTION: Can we detect the effect of SBTM on PCI using only 23 gait cycles also from SBTM walking?

METHODS

Young healthy participants (n = 13) with right side motor dominance performed SBTM walking trials. Experiment protocol began by walking in tied belt (TB) mode, followed by an incremental speed increase of one of the belts by 50 % - split belt (SB) mode. This was performed for each side. Two 1-minute segments were analyzed per participant, TB and SB. PCI analysis was carried out upon fewer strides (n = 23) and compared to PCI that was obtained based on all available strides (n = 56 ± 5).

RESULTS

Clear SBTM walking effects on PCI were seen in both experiments, for example, PCI increased from 4.46 ± 1.5 % (TB) to 10.07 ± 3.6 % (SB) for left belt speed increase. Twenty three strides from each trail were sufficient to demonstrate the effect.

SIGNIFICANCE

PCI can be a useful metric to characterize changes in bilateral coordination of gait during SBTM gait adaptations. The fact that 23 strides are sufficient for its reliable estimation, contribute to the continued monitoring through the adaptation process (i.e., by using time windows).

Atypical Gait Cycles in Parkinson's Disease

It is important to find objective biomarkers for evaluating gait in Parkinson's Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (-4% of the gait cycle, p = 0.04). However, they showed a significant increase in atypical gait cycles (+42%, p = 0.006), during both walking straight and turning. A forefoot strike, instead of a "normal" heel strike, characterized the large majority of PD's atypical cycles, whose total percentage was 25.4% on the most-affected and 15.5% on the least-affected side. Moreover, we found a strong correlation between the atypical cycles and the motor clinical score UPDRS-III (r = 0.91, p = 0.002), in the subset of PD patients showing an abnormal number of atypical cycles, while we found a moderate correlation (r = 0.60, p = 0.005), considering the whole PD population. Atypical cycles have proved to be a valid biomarker to quantify subtle gait dysfunctions in PD patients.

Computerized Dual-Task Testing of Gait Visuomotor and Cognitive Functions in Parkinson's Disease: Test-Retest Reliability and Validity

BACKGROUND

Mobility and cognitive impairments in Parkinson's disease (PD) often coexist and are prognostic of adverse health events. Consequently, assessment and training that simultaneously address both gait function and cognition are important to consider in rehabilitation and promotion of healthy aging. For this purpose, a computer game-based rehabilitation treadmill platform (GRP) was developed for dual-task (DT) assessment and training.

OBJECTIVE

The first objective was to establish the test-retest reliability of the GRP assessment protocol for DT gait, visuomotor and executive cognitive function in PD patients. The second objective was to examine the effect of task condition [single task (ST) vs. DT] and disease severity (stage 2 vs. stage 3) on gait, visuomotor and cognitive function.

METHODS

Thirty individuals aged 55 to 70 years, diagnosed with PD; 15 each at Hoehn and Yahr scale stage 2 (PD-2) and 3 (PD-3) performed a series of computerized visuomotor and cognitive game tasks while sitting (ST) and during treadmill walking (DT). A treadmill instrumented with a pressure mat was used to record center of foot pressure and compute the average and coefficient of variation (COV) of step time, step length, and drift during 1-min, speed-controlled intervals. Visuomotor and cognitive game performance measures were quantified using custom software. Testing was conducted on two occasions, 1 week apart.

RESULTS

With few exceptions, the assessment protocol showed moderate to high intraclass correlation coefficient (ICC) values under both ST and DT conditions for the spatio-temporal gait measures (average and COV), as well as the visuomotor tracking and cognitive game performance measures. A significant decline in gait, visuomotor, and cognitive game performance measures was observed during DT compared to ST conditions, and in the PD-3 compared to PD-2 groups.

CONCLUSION

The high to moderate ICC values along with the lack of systematic errors in the measures indicate that this tool has the ability to repeatedly record reliable DT interference (DTI) effects over time. The use of interactive digital media provides a flexible method to produce and evaluate DTI for a wide range of executive cognitive activities. This also proves to be a sensitive tool for tracking disease progression.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, identifier NCT03232996.