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

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.

The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review

Gait, balance, and coordination are important in the development of chronic disease, but the ability to accurately assess these in the daily lives of patients may be limited by traditional biased assessment tools. Wearable sensors offer the possibility of minimizing the main limitations of traditional assessment tools by generating quantitative data on a regular basis, which can greatly improve the home monitoring of patients. However, these commercial sensors must be validated in this context with rigorous validation methods. This scoping review summarizes the state-of-the-art between 2010 and 2020 in terms of the use of commercial wearable devices for gait monitoring in patients. For this specific period, 10 databases were searched and 564 records were retrieved from the associated search. This scoping review included 70 studies investigating one or more wearable sensors used to automatically track patient gait in the field. The majority of studies (95%) utilized accelerometers either by itself (N = 17 of 70) or embedded into a device (N = 57 of 70) and/or gyroscopes (51%) to automatically monitor gait via wearable sensors. All of the studies (N = 70) used one or more validation methods in which “ground truth” data were reported. Regarding the validation of wearable sensors, studies using machine learning have become more numerous since 2010, at 17% of included studies. This scoping review highlights the current state of the ability of commercial sensors to enhance traditional methods of gait assessment by passively monitoring gait in daily life, over long periods of time, and with minimal user interaction. Considering our review of the last 10 years in this field, machine learning approaches are algorithms to be considered for the future. These are in fact data-based approaches which, as long as the data collected are numerous, annotated, and representative, allow for the training of an effective model. In this context, commercial wearable sensors allowing for increased data collection and good patient adherence through efforts of miniaturization, energy consumption, and comfort will contribute to its future success.

How groove in music affects gait

Rhythmic auditory stimulation (RAS) is a gait intervention in which gait-disordered patients synchronise footsteps to music or metronome cues. Musical 'groove', the tendency of music to induce movement, has previously been shown to be associated with faster gait, however, why groove affects gait remains unclear. One mechanism by which groove may affect gait is that of beat salience: music that is higher in groove has more salient musical beats, and higher beat salience might reduce the cognitive demands of perceiving the beat and synchronizing footsteps to it. If groove's effects on gait are driven primarily by the impact of beat salience on cognitive demands, then groove's effects might only be present in contexts in which it is relevant to reduce cognitive demands. Such contexts could include task parameters that increase cognitive demands (such as the requirement to synchronise to the beat), or individual differences that may make synchronisation more cognitively demanding. Here, we examined whether high beat salience can account for the effects of high-groove music on gait. First, we increased the beat salience of low-groove music to be similar to that of high-groove music by embedding metronome beats in low and high-groove music. We examined whether low-groove music with high beat salience elicited similar effects on gait as high-groove music. Second, we examined the effect of removing the requirement to synchronise footsteps to the beat (i.e., allowing participants to walk freely with the music), which is thought to remove the cognitive demand of synchronizing movements to the beat. We tested two populations thought to be sensitive to the cognitive demands of synchronisation, weak beat-perceivers and older adults. We found that increasing the beat salience of low-groove music increased stride velocity, but strides were still slower than with high-groove music. Similarly, removing the requirement to synchronise elicited faster, less variable gait, and reduced bias for stability, but high-groove music still elicited faster strides than low-groove music. These findings suggest that beat salience contributes to groove's effect on gait, but it does not fully account for it. Despite reducing task difficulty by equalizing beat salience and removing the requirement to synchronise, high-groove music still elicited faster, less variable gait. Therefore, other properties of groove also appear to play a role in groove's effect on gait.

Changes in Metabolic Activity and Gait Function by Dual-Task Cognitive Game-Based Treadmill System in Parkinson's Disease: Protocol of a Randomized Controlled Trial

Balance and gait impairments, and consequently, mobility restrictions and falls are common in Parkinson’s disease (PD). Various cognitive deficits are also common in PD and are associated with increased fall risk. These mobility and cognitive deficits are limiting factors in a person’s health, ability to perform activities of daily living, and overall quality of life. Community ambulation involves many dual-task (DT) conditions that require processing of several cognitive tasks while managing or reacting to sudden or unexpected balance challenges. DT training programs that can simultaneously target balance, gait, visuomotor, and cognitive functions are important to consider in rehabilitation and promotion of healthy active lives. In the proposed multi-center, randomized controlled trial (RCT), novel behavioral positron emission tomography (PET) brain imaging methods are used to evaluate the molecular basis and neural underpinnings of: (a) the decline of mobility function in PD, specifically, balance, gait, visuomotor, and cognitive function, and (b) the effects of an engaging, game-based DT treadmill walking program on mobility and cognitive functions. Both the interactive cognitive game tasks and treadmill walking require continuous visual attention, and share spatial processing functions, notably to minimize any balance disturbance or gait deviation/stumble. The ability to “walk and talk” normally includes activation of specific regions of the prefrontal cortex (PFC) and the basal ganglia (site of degeneration in PD). The PET imaging analysis and comparison with healthy age-matched controls will allow us to identify areas of abnormal, reduced activity levels, as well as areas of excessive activity (increased attentional resources) during DT-walking. We will then be able to identify areas of brain plasticity associated with improvements in mobility functions (balance, gait, and cognition) after intervention. We expect the gait-cognitive training effect to involve re-organization of PFC activity among other, yet to be identified brain regions. The DT mobility-training platform and behavioral PET brain imaging methods are directly applicable to other diseases that affect gait and cognition, e.g., cognitive vascular impairment, Alzheimer’s disease, as well as in aging.

The Association Between Clinical Characteristics and Motor Symptom Laterality in Patients With Parkinson's Disease

Background and Purpose: The unilateral onset and persistent asymmetry of motor symptoms are important characteristics of Parkinson's disease (PD). By using scales and wearable sensors, this study explored whether motor symptom laterality could affect non-motor symptom and gait performance.

Methods: A total of 130 right-handed patients with PD were enrolled in our study and were divided into two groups according to the side of predominant motor symptom presentation by using the Unified Parkinson's Disease Rating Scale part III. We measured the non-motor symptoms with the Non-motor symptoms Scale, sleep quality with the Parkinson's Disease Sleep Scale and Pittsburgh sleep quality index, cognitive function with the Mini-mental State Examination and Montreal Cognitive Assessment, quality of life with the Parkinson's Disease Questionnaire-39, and the severity of anxiety and depression with the Hamilton Anxiety Scale and Hamilton Depression Scale, respectively. All participants underwent the instrumented stand and walk test, and gait data were collected using a set of JiBuEn gait analysis system.

Results: We observed that left-dominant symptom PD patients (LPD) were associated with a greater impairment of sleep quality than right-dominant symptom PD patients (RPD). We found no difference between LPD and RPD in terms of gait performance. However, compared with the severe asymmetry RPD patients (RPD-S), severe asymmetry LPD patients (LPD-S) showed a shorter stride length and decreased range of motion of hip joints.

Conclusions: In this study, LPD was associated with a more severe sleep-related dysfunction than RPD. In addition, LPD-S exhibited more gait impairments than RPD-S. Considering that motor symptom laterality may affect the non-motor symptom and gait performance, it should be taken into account when evaluating and treating PD patients.

Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson's disease

BACKGROUND

Deep brain stimulation (DBS) is a treatment option for Parkinson's disease patients when medication does not sufficiently manage their symptoms. DBS can be a highly effect therapy, but only after a time-consuming trial-and-error stimulation parameter adjustment process that is susceptible to clinician bias. This trial-and-error process will be further prolonged with the introduction of segmented electrodes that are now commercially available. New approaches to optimizing a patient's stimulation parameters, that can also handle the increasing complexity of new electrode and stimulator designs, is needed.

METHODS

To improve DBS parameter programming, we explored two semi-automated optimization approaches: a Bayesian optimization (BayesOpt) algorithm to efficiently determine a patient's optimal stimulation parameter for minimizing rigidity, and a probit Gaussian process (pGP) to assess patient's preference. Quantified rigidity measurements were obtained using a robotic manipulandum in two participants over two visits. Rigidity was measured, in 5Hz increments, between 10-185Hz (total 30-36 frequencies) on the first visit and at eight BayesOpt algorithm-selected frequencies on the second visit. The participant was also asked their preference between the current and previous stimulation frequency. First, we compared the optimal frequency between visits with the participant's preferred frequency. Next, we evaluated the efficiency of the BayesOpt algorithm, comparing it to random and equal interval selection of frequency.

RESULTS

The BayesOpt algorithm estimated the optimal frequency to be the highest tolerable frequency, matching the optimal frequency found during the first visit. However, the participants' pGP models indicate a preference at frequencies between 70-110 Hz. Here the stimulation frequency is lowest that achieves nearly maximal suppression of rigidity. BayesOpt was efficient, estimating the rigidity response curve to stimulation that was almost indistinguishable when compared to the longer brute force method.

CONCLUSIONS

These results provide preliminary evidence of the feasibility to use BayesOpt for determining the optimal frequency, while pGP patient's preferences include more difficult to measure outcomes. Both novel approaches can shorten DBS programming and can be expanded to include multiple symptoms and parameters.

Validity of Hip and Ankle Worn Actigraph Accelerometers for Measuring Steps as a Function of Gait Speed during Steady State Walking and Continuous Turning

This study aimed to investigate the accuracy and reliability of hip and ankle worn Actigraph GT3X+ (AG) accelerometers to measure steps as a function of gait speed. Additionally, the effect of the low frequency extension filter (LFEF) on the step accuracy was determined. Thirty healthy individuals walked straight and walked with continuous turns in different gait speeds. Number of steps were recorded with a hip and ankle worn AG, and with a Stepwatch (SW) activity monitor positioned around the right ankle, which was used as a reference for step count. The percentage agreement, interclass correlation coefficients and Bland–Altmann plots were determined between the AG and the reference SW across gait speeds for the two walking conditions. The ankle worn AG with the default filter was the most sensitive for step detection at >0.6 m/s, whilst accurate step detection for gait speeds < 0.6 m/s were only observed when applying the LFEF. The hip worn AG with the default filter showed poor accuracy (12–78%) at gait speeds < 1.0 m/s whereas the accuracy increased to >87% for gait speeds < 1.0 m/s when applying the LFEF. Ankle worn AG was the most sensitive to measure steps at a vast range of gait speeds. Our results suggest that sensor placement and filter settings need to be taken into account to provide accurate estimates of step counts.

Characteristics of Gait Variability in the Elderly While Walking on a Treadmill with Gait Speed Variation

Gait variability (GV), which is a variable for predicting mobility issues and risk of falling in elderly people, is defined as the fluctuation in spatiotemporal characteristics from one step to the next in walking. The goal of this study was to analyze the age- and sex-related spatiotemporal variability characteristics of elderly individuals using the measurements taken while walking on a treadmill for one minute based on gait speed variation. Gait testing was conducted on 225 healthy male and female individuals aged 60–79 years who were able to walk and move on their own and, specifically, walk on a treadmill for one minute. The test was performed at three speed conditions—the preferred speed of the participant, 20% higher than the preferred speed, and 20% lower than the preferred speed—and data were recorded using shoe-type data loggers. The different age groups and sex could be distinguished using the coefficient of variance (CV) of the double support phase and gait asymmetry (GA) at the preferred speed, and CVs of stride length and stance phase at faster speed. The results indicated that the values of GV obtained from the test were used to determine the variation in gait characteristics of elderly individuals.

Mild Gait Impairment and Its Potential Diagnostic Value in Patients with Early-Stage Parkinson's Disease

Methods

32 patients with early-stage PD and 30 healthy control subjects (HC) were enrolled. All participants completed the instrumented stand and walk test, and gait data was collected using wearable sensors.

Results

We observed increased variability of stride length (SL) (P < 0.001), stance phase time (StPT) (P = 0.004), and swing phase time (SwPT) (P = 0.011) in PD. There were decreased heel strike (HS) (P = 0.001), range of motion of knee (P = 0.036), and hip joints (P < 0.001) in PD. In symmetry analysis, no difference was found in any of the assessed gait parameters between HC and PD. Only total steps (AUC = 0.763, P < 0.001), SL (AUC = 0.701, P = 0.007), SL variability (AUC = 0.769, P < 0.001), StPT variability (AUC = 0.712, P = 0.004), and SwPT variability (AUC = 0.688, P = 0.011) had potential diagnostic value. When these five gait parameters were combined, the predictive power was found to increase, with the highest AUC of 0.802 (P < 0.001).

Conclusions

Patients with early-stage PD presented increased variability but still symmetrical gait pattern. Some specific gait parameters can be applied to diagnose early-stage PD which may increase diagnosis accuracy. Our findings are helpful to improve patient's quality of life.

Gait Analysis of Old Individuals with Mild Parkinsonian Signs and Those Individuals' Gait Performance Benefits Little from Levodopa

Background and Purpose

Gait analysis and the effects of levodopa on the gait characteristics in Mild parkinsonian signs (MPS) are rarely published. The present research aimed to (1) analyze the gait characteristics in MPS; (2) explore the effects of levodopa on the gait performance of MPS.

Methods

We enrolled 22 inpatients with MPS and 20 healthy control subjects (HC) from Nanjing Brain Hospital. The Unified Parkinson’s Disease Rating Scale was used to evaluate motor symptoms. Acute levodopa challenge test was performed to explore the effects of levodopa on the gait performance of MPS. The instrumented stand and walk test was conducted for each participant and the JiBuEn gait analysis system was used to collect gait data.

Results

For spatiotemporal parameters: Compared with HC, the state before taking levodopa/benserazide in MPS group (meds-off) demonstrated a decrease in stride length (SL) (p≤0.001), an increase in SL variability (p≤0.001), and swing phase time variability (p=0.016). Compared with meds-off, the state after 1 hour of taking levodopa/benserazide in MPS group (meds-on) exhibited an increase in SL (p≤0.001), a decrease in SL variability (p≤0.001). For kinematic parameters: Compared with HC, meds-off demonstrated a decrease in heel strike angle (p=0.008), range of motion (ROM) of knee joint (p=0.011) and ROM of hip joint (p=0.007). Compared with meds-off, meds-on exhibited an increase in HS (p≤0.001). Bradykinesia and rigidity scores were significantly correlated with gait parameters.

Conclusion

Although the clinical symptoms of the MPS group are mild, their gait damage is obvious and they exhibited a decreased SL and joints movement, and a more variable gait pattern. Levodopa had little effect on the gait performance of those individuals.

Dual-Task Effects During a Motor-Cognitive Task in Parkinson's Disease: Patterns of Prioritization and the Influence of Cognitive Status

People with Parkinson’s disease (PD) experience greater difficulties during dual task (DT) walking compared to healthy controls, but factors explaining the variance in DT costs remain largely unknown. Additionally, as cognitive impairments are common in PD it is important to understand whether cognitive status influences the strategies used during DT paradigms. The study aimed to (1) explore DT costs on gait and cognition during DT walking, (2) investigate factors associated with DT costs, and (3) to investigate to what extent patterns of DT costs and prioritization differed according to cognitive status. A total of 93 people with Parkinson’s disease were examined when walking in single and DT conditions. Information regarding demographics, PD severity, mobility, and cognitive and affective symptoms was collected, and an extensive neuropsychological test battery was used to classify whether participants had mild cognitive impairment (PD MCI) or not (PD non-MCI). Dual task costs were observed across all gait domains except asymmetry. Cognitive status was associated with DT costs on both gait and cognition. Nonmotor experiences of daily living were further associated with DT cost on cognition, and TUG-cog associated with DT cost on gait. People with PD MCI had larger DT costs on gait than PD non-MCI. Strategies differed according to cognitive status, whereby PD MCI used a posture-second strategy, and PD non-MCI used a posture-first strategy. Once verified in future studies, these results can inform clinicians and researchers when tailoring DT training paradigms to the specific characteristics of people with PD.

Cholinergic Basal Forebrain Volumes Predict Gait Decline in Parkinson's Disease

BACKGROUND

Gait disturbance is an early, disabling feature of Parkinson's disease (PD) that is typically refractory to dopaminergic medication. The cortical cholinergic system, originating in the nucleus basalis of Meynert of the basal forebrain, has been implicated. However, it is not known if degeneration in this region relates to a worsening of disease-specific gait impairment.

OBJECTIVE

To evaluate associations between sub-regional cholinergic basal forebrain volumes and longitudinal progression of gait impairment in PD.

METHODS

99 PD participants and 47 control participants completed gait assessments via an instrumented walkway during 2 minutes of continuous walking, at baseline and for up to 3 years, from which 16 spatiotemporal characteristics were derived. Sub-regional cholinergic basal forebrain volumes were measured at baseline via MRI and a regional map derived from post-mortem histology. Univariate analyses evaluated cross-sectional associations between sub-regional volumes and gait. Linear mixed-effects models assessed whether volumes predicted longitudinal gait changes.

RESULTS

There were no cross-sectional, age-independent relationships between sub-regional volumes and gait. However, nucleus basalis of Meynert volumes predicted longitudinal gait changes unique to PD. Specifically, smaller nucleus basalis of Meynert volume predicted increasing step time variability (P = 0.019) and shortening swing time (P = 0.015); smaller posterior nucleus portions predicted shortening step length (P = 0.007) and increasing step time variability (P = 0.041).

CONCLUSIONS

This is the first study to demonstrate that degeneration of the cortical cholinergic system predicts longitudinal progression of gait impairments in PD. Measures of this degeneration may therefore provide a novel biomarker for identifying future mobility loss and falls. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A Multifactorial Model of Multiple Sclerosis Gait and Its Changes Across Different Disability Levels

OBJECTIVE

Mobility assessment is critical in the clinical management of people with Multiple Sclerosis (pwMS). Instrumented gait analysis provides a plethora of metrics for quantifying concurrent factors contributing to gait deterioration. However, a gait model discriminating underlying features contributing to this deterioration is lacking in pwMS. This study aimed at developing and validating such a model.

METHODS

The gait of 24 healthy controls and 114 pwMS with mild, moderate, or severe disability was measured with inertial sensors on the shanks and lower trunk while walking for 6 minutes along a hospital corridor. Twenty out of thirty-six initially explored metrics computed from the sensor data met the quality criteria for exploratory factor analysis. This analysis provided the sought model, which underwent a confirmatory factor analysis before being used to characterize gait impairment across the three disability groups.

RESULTS

A gait model consisting of five domains (rhythm/variability, pace, asymmetry, and forward and lateral dynamic balance) was revealed by the factor analysis, which was able to highlight gait abnormalities across the disability groups: significant alterations in rhythm/variability-, asymmetry-, and pace-based features were present in the mild group, but these were more profound in the moderate and severe groups. Deterioration in dynamic balance-based features was only noted in pwMS with a moderate and severe disability.

CONCLUSION

A conceptual model of gait for disease-specific mobility assessment in pwMS was successfully developed and tested.

SIGNIFICANCE

The new model, built with metrics that represent gait impairment in pwMS, highlighted clinically relevant changes across different disability levels, including those with no clinically observable walking disability. This shows the clear potential as a monitoring biomarker in pwMS.

Abnormal Gait Detection Using Wearable Hall-Effect Sensors

Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury.

REM Sleep Without Atonia and Gait Impairment in People with Mild-to-Moderate Parkinson's Disease

BACKGROUND

Subtle gait deficits can be seen in people with idiopathic rapid eye movement (REM) sleep behavior disorder (RBD), a prodromal stage of Parkinson's disease (PD) and related alpha-synucleinopathies. It is unknown if the presence and level of REM sleep without atonia (RSWA, the electromyographic hallmark of RBD) is related to the severity of gait disturbances in people with PD.

OBJECTIVE

We hypothesized that gait disturbances in people with mild-to-moderate PD would be greater in participants with RSWA compared to those without RSWA and matched controls, and that gait impairment would correlate with measures of RSWA.

METHODS

Spatiotemporal characteristics of gait were obtained from 41 people with PD and 21 age-matched controls. Overnight sleep studies were used to quantify muscle activity during REM sleep and group participants with PD into those with RSWA (PD-RSWA+, n = 22) and normal REM sleep muscle tone (PD-RSWA-, n = 19). Gait characteristics were compared between groups and correlated to RSWA.

RESULTS

The PD-RSWA+ group demonstrated significantly reduced gait speed and step lengths and increased stance and double support times compared to controls, and decreased speed and cadence and increased stride velocity variability compared to PD-RSWA- group. Larger RSWA scores were correlated with worse gait impairment in the PD group.

CONCLUSION

The presence and level of muscle tone during REM sleep is associated with the severity of gait disturbances in PD. Pathophysiological processes contributing to disordered gait may occur earlier and/or progress more rapidly in people with PD and RBD.

Upper and Lower Limb Movement Kinematics in Aging FMR1 Gene Premutation Carriers

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a neurodegenerative disorder associated with a premutation cytosine-guanine-guanine (CGG) trinucleotide repeat expansion of the FMR1 gene. FXTAS is estimated to be the most common single-gene form of ataxia in the aging population. Gait ataxia and intention tremor are the primary behavioral symptoms of FXTAS, though clinical evaluation of these symptoms often is subjective, contributing to difficulties in reliably differentiating individuals with FXTAS and asymptomatic premutation carriers. This study aimed to clarify the extent to which quantitative measures of gait and upper limb kinematics may serve as biobehavioral markers of FXTAS degeneration. Nineteen premutation carriers (aged 46-77 years), including 9 with possible, probable, or definite FXTAS and 16 sex- and IQ-matched healthy controls, completed tests of non-constrained walking and reaching while both standing (static reaching) and walking (dynamic reaching) to quantify gait and upper limb control, respectively. For the non-constrained walking task, participants wore reflective markers and walked at their preferred speed on a walkway. During the static reaching task, participants reached and lifted boxes of different sizes while standing. During the dynamic reaching task, participants walked to reach and lift the boxes. Movement kinematics were examined in relation to clinical ratings of neuromotor impairments and CGG repeat length. During non-constrained walking, individuals with FXTAS showed decreased stride lengths and stride velocities, increased percentages of double support time, and increased variabilities of cadence and center of mass relative to both asymptomatic premutation carriers and controls. While individuals with FXTAS did not show any static reaching differences relative to the other two groups, they showed multiple differences during dynamic reaching trials, including reduced maximum reaching velocity, prolonged acceleration time, and jerkier movement of the shoulder, elbow, and hand. Gait differences during non-constrained walking were associated with more severe clinically rated posture and gait symptoms. Reduced maximum reaching velocity and increased jerkiness during dynamic reaching were each related to more severe clinically rated kinetic dysfunction and overall neuromotor symptoms in FMR1 premutation carriers. Our findings suggest kinematic alterations consistent with gait ataxia and upper limb bradykinesia are each selectively present in individuals with FXTAS, but not asymptomatic aging premutation carriers. Consistent with neuropathological and magnetic resonance imaging (MRI) studies of FXTAS, these findings implicate cerebellar and basal ganglia degeneration associated with neuromotor decline. Our results showing associations between quantitative kinematic differences in FXTAS and clinical ratings suggest that objective assessments of gait and reaching behaviors may serve as critical and reliable targets for detecting FXTAS risk and monitoring progression.

Effects of virtual reality environments on overground walking in people with Parkinson disease and freezing of gait

BACKGROUND

Freezing of gait (FoG) is a common target of rehabilitative interventions for people with Parkinson disease (PD). Virtual reality (VR) holds potential for advancing research and clinical management of FoG through flexible creation of FoG-provoking environments that are not easily or safely replicated in the clinic.

OBJECTIVE

The aim of this study was to investigate whether VR environments that replicate FoG-provoking situations would exacerbate gait impairments associated with FoG compared to unobstructed VR and physical laboratory environments.

METHODS

Gait characteristics (pace, rhythm, variability, asymmetry, and postural control domains) and festination were measured using motion capture while people with PD walked in VR environments based on FoG-provoking situations (doorway, hallway, and crowd environments) compared to unobstructed VR and physical laboratory environments. The effect of VR environments was assessed using one-way repeated measures ANOVAs with planned contrasts.

RESULTS

Ten participants (mean age 74.1 years, 3 females, Hoehn and Yahr stage 2-3) with PD who self-reported FoG participated. Gait speed and step length were reduced in all VR environments compared to the physical laboratory. Step width was wider, step length was more variable, and festination was more common for some of the VR environments compared to the physical laboratory environment. Compared to the unobstructed virtual laboratory environment, step length was more variable in VR crowd and doorway environments.

CONCLUSIONS

The exacerbation of gait impairments that are characteristic precursors of FoG in FoG-provoking VR environments supports the potential utility of VR technology in the assessment and treatment of gait impairments in PD.Implications for rehabilitationFreezing increases fall risk and reduces quality of life in Parkinson disease (PD).Virtual reality (VR) can simulate visuospatial environments that provoke freezing.Immersive VR doorway, hallway, and crowd environments were developed.Gait speed slowed when people with PD walked overground in all VR environments.Step variability and festination increased in freeze-provoking environments.

Short-Term Effects of Single-Session Split-Belt Treadmill Training on Dual-Task Performance in Parkinson's Disease and Healthy Elderly

Background: Dual-tasking is challenging for people with Parkinson's disease and freezing of gait (PD+FOG) and can exacerbate freezing episodes and falls. Split-belt treadmill training (SBT) is a novel tool to train complex gait and may improve dual-task (DT) walking and turning.

Objective: To investigate the single-session effects of SBT on DT walking and DT turning performance in PD+FOG and older adults (OA), compared to regular treadmill training.

Methods: Forty-five PD+FOG and 36 OA participated in a single training session (30 min). They were randomized into one of four training groups: (A) SB75—steady belt speed ratio 0.75:1; (B) SB50—steady belt speed ratio 0.5:1; (C) SBCR—changing belt speed ratios between 0.75:1 and 0.5:1; and (D) Tied-Belt (TBT). Over-ground straight-line gait and an alternating turning in place task combined with a cognitive dual-task (DT) (auditory Stroop) were assessed pre- and post-training, and the following day (retention). Constrained longitudinal data analysis was used to investigate the training effects for all participants and for PD+FOG alone.

Results: DT gait speed improved at post-training for all groups (p < 0.001). However, SBT (SB50 and SBCR) led to larger post-training improvements compared to TBT, which were still visible at retention (SB50). For mean DT turning speed and Stroop response time while walking, only SBT groups showed significant improvements at post-training or retention. DT stride length, peak DT turning speed, and Stroop performance index while walking also showed larger gains in SBT compared to TBT. Results for PD+FOG alone showed similar effects although with smaller effect sizes.

Conclusions: A single session of SBT in PD+FOG and OA showed larger short-term effects on DT walking and turning compared to TBT. Cognitive DT performance was also improved in SBT, likely due to reduced cortical control of gait. These results illustrate the potential for SBT to improve DT during complex gait and possibly reduce fall risk in clinical and healthy populations.

Gait Progression Over 6 Years in Parkinson's Disease: Effects of Age, Medication, and Pathology

Background: Gait disturbance is an early, cardinal feature of Parkinson's disease (PD) associated with falls and reduced physical activity. Progression of gait impairment in Parkinson's disease is not well characterized and a better understanding is imperative to mitigate impairment. Subtle gait impairments progress in early disease despite optimal dopaminergic medication. Evaluating gait disturbances over longer periods, accounting for typical aging and dopaminergic medication changes, will enable a better understanding of gait changes and inform targeted therapies for early disease. This study aimed to describe gait progression over the first 6 years of PD by delineating changes associated with aging, medication, and pathology. Methods: One-hundred and nine newly diagnosed PD participants and 130 controls completed at least two gait assessments. Gait was assessed at 18-month intervals for up to 6 years using an instrumented walkway to measure sixteen spatiotemporal gait characteristics. Linear mixed-effects models assessed progression. Results: Ten gait characteristics significantly progressed in PD, with changes in four of these characteristics attributable to disease progression. Age-related changes also contributed to gait progression; changes in another two characteristics reflected both aging and disease progression. Gait impairment progressed irrespective of dopaminergic medication change for all characteristics except step width variability. Conclusions: Discrete gait impairments continue to progress in PD over 6 years, reflecting a combination of, and potential interaction between, disease-specific progression and age-related change. Gait changes were mostly unrelated to dopaminergic medication adjustments, highlighting limitations of current dopaminergic therapy and the need to improve interventions targeting gait decline.

People with Parkinson disease with and without freezing of gait respond similarly to external and self-generated cues

BACKGROUND

Gait deficits in Parkinson disease (PD), including freezing of gait (FOG), can be among the most debilitating symptoms. Rhythmic auditory cueing has been used to alleviate some gait symptoms. However, different cue types, such as externally-generated and self-generated cues, affect gait variability differently. The differential effects of these cue types on people with PD with FOG (PD + FOG), who often have higher gait variability, and those with PD without FOG (PD-FOG) is unknown. Given the relationship of gait variability to fall risk, this is an important area to address.

RESEARCH QUESTION

This study aims to 1) confirm the association between falls and gait variability measures in PD-FOG, PD + FOG and age-matched Controls; 2) investigate the effects of different cue types on gait variability in PD-FOG and PD + FOG; and 3) determine whether baseline gait characteristics are associated with response to cues.

METHODS

This cross-sectional study investigated PD-FOG (n = 24), PD + FOG (n = 20), and Controls (n = 24). Gait trials were collected during use of externally-generated and self-generated cues for all participants. Gait variability measures were the primary outcomes to assess the effects of rhythmic auditory cues.

RESULTS

Logistic regression models showed increased gait variability was associated with falls across groups. Repeated measures ANOVAs showed externally-generated cues increased gait variability, whereas self-generated cues did not, for all groups. Pearson's correlations showed participants with higher baseline gait variability had greater reduction in gait variability with rhythmic auditory cueing.

SIGNIFICANCE

Higher gait variability is associated with falls. This study demonstrates that PD + FOG are capable of using self-generated cues without increasing gait variability measures, thereby stabilizing gait. People with higher baseline gait variability are likely to experience the largest reductions in variability with the addition of external cues.

Highly challenging balance and gait training for individuals with Parkinson's disease improves pace, rhythm and variability domains of gait - A secondary analysis from a randomized controlled trial

OBJECTIVE

Evaluate immediate and long-term effects of highly challenging balance and gait training on pace-, rhythm-, variability-, asymmetry-, and postural control domains of gait for individuals with Parkinson's disease (PD).

DESIGN

Randomized controlled trial - a secondary analysis.

SETTING

University hospital setting.

PARTICIPANTS

One-hundred older adults with mild to moderate PD (Hoehn & Yahr 2 and 3).

INTERVENTION

Training group (n = 51): 10 weeks (3 times/week) of intensive balance and gait training, incorporating dual tasks. Control group (n = 49): care as usual.

MAIN OUTCOME MEASURES

Spatiotemporal gait variables collected during normal and fast walking on a pressure-sensitive mat. A linear mixed model was used to evaluate training effects post intervention and at the 6 and 12 month follow-up.

RESULTS

Immediate training effects in the pace domain of gait were increased step velocity (normal speed: 8.2 cm/s, P = 0.04; fast: 10.8 cm/s, P < 0.01), increased step length (normal speed: 3 cm, P = 0.05; fast: 2.3 cm, P = 0.05) and reduced swing time variability (fast speed: -2.5 ms, P = 0.02). In the rhythm domain reduced step time (fast speed: -19.3 ms, P = 0.02), stance time (normal: -24.3 ms, P = 0.01; fast: -29.6 ms, P = 0.02) and swing time (fast speed: -8.7 ms, P = 0.04) was seen. Relative to the variability domain, the training decreased step time variability (fast: -2.8 ms, P = 0.02) and stance time variability (fast: -3.9 ms, P = 0.02). No training effects were retained at 6 months.

CONCLUSIONS

Highly challenging balance and gait training improved pace, rhythm and variability aspects of PD gait in the short-term, but effects are not retained long-term.

TRIAL REGISTRATION NUMBER

NCT01417598.

Turning Detection During Gait: Algorithm Validation and Influence of Sensor Location and Turning Characteristics in the Classification of Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder resulting in a range of mobility deficits affecting gait, balance and turning. In this paper, we present: (i) the development and validation of an algorithm to detect turns during gait; (ii) a method to extract turn characteristics; and (iii) the classification of PD using turn characteristics. Thirty-seven people with PD and 56 controls performed 180-degree turns during an intermittent walking task. Inertial measurement units were attached to the head, neck, lower back and ankles. A turning detection algorithm was developed and validated by two raters using video data. Spatiotemporal and signal-based characteristics were extracted and used for PD classification. There was excellent absolute agreement between the rater and the algorithm for identifying turn start and end (ICC ≥ 0.99). Classification modeling (partial least square discriminant analysis (PLS-DA)) gave the best accuracy of 97.85% when trained on upper body and ankle data. Balanced sensitivity (97%) and specificity (96.43%) were achieved using turning characteristics from the neck, lower back and ankles. Turning characteristics, in particular angular velocity, duration, number of steps, jerk and root mean square distinguished mild-moderate PD from controls accurately and warrant future examination as a marker of mobility impairment and fall risk in PD.

Novel, clinically applicable method to measure step-width during the swing phase of gait

OBJECTIVE

Step-width during walking is an indicator of stability and balance in patients with neurological disorders, and development of objective tools to measure this clinically would be a great advantage. The aim of this study was to validate an in-house-developed gait analysis system (Striton), based on optical and inertial sensors and a novel method for stride detection, for measuring step-width during the swing phase of gait and temporal parameters.

APPROACH

The step-width and stride-time measurements were validated in an experimental setup, against a 3D motion capture system and on an instrumented walkway. Further, test-retest and day-to-day variability were evaluated, and gait parameters were collected from 87 elderly persons (EP) and four individuals with idiopathic normal pressure hydrocephalus (iNPH) before/after surgery.

MAIN RESULTS

Accuracy of the step-width measurement was high: in the experimental setup mean error was 0.08 ± 0.25 cm (R = 1.00) and against the 3D motion capture system 0.04 ± 1.12 cm (R = 0.98). Test-retest and day-to-day measurements were equal within ±0.5 cm. Mean difference in stride time was -0.003 ± 0.008 s between Striton and the instrumented walkway. The Striton system was successfully applied in the clinical setting on individuals with iNPH, which had larger step-width (6.88 cm, n = 4) compared to EP (5.22 cm, n = 87).

SIGNIFICANCE

We conclude that Striton is a valid, reliable and wearable system for quantitative assessment of step-width and temporal parameters during gait. Initial measurements indicate that the newly defined step-width parameter differs between EP and patients with iNPH and before/after surgery. Thus, there is potential for clinical applicability in patients with reduced gait stability.

Working memory is a core executive function supporting dual-task locomotor performance across childhood and adolescence

Most daily-life ambulatory tasks involve dual tasking, for example, talking while walking. In children, the evidence supporting the effects of age on dual tasking is confounded by the difficulty of the cognitive task and lack of adjustment to suit individual cognitive abilities. To address this issue, the current study examined the effects of age, cognitive load, and executive functioning on the degree of dual-task gait interference across childhood and adolescence. We tested 120 typically developing children aged 6-11 years, adolescents aged 12-16 years, and young adults aged 18-25 years. Participants were asked to walk while performing a visuospatial working memory task at two levels of cognitive load (easy and difficult) adjusted to suit each participant's cognitive ability. Spatiotemporal characteristics and intra-individual variability of gait were measured using a GAITRite electronic walkway. Irrespective of the cognitive load level, children aged 6 to 11 years showed greater dual-task gait interference for selective spatiotemporal gait characteristics; however, the younger children showed a trade-off pattern in gait variability whereby they prioritized gait stability at the expense of cognitive performance. Our results also showed that age and working memory capacity were significant predictors of dual-task interference for a range of complementary gait parameters in the combined sample. Importantly, working memory capacity was part of a moderating relationship between age and dual-task gait interference. These findings emphasize the importance of dual-task prioritization strategies in younger children and highlight the role of individual differences in working memory capacity in performance in dual-task gait situations.

Portable accelerometers for the evaluation of spatio-temporal gait parameters in people with Parkinson's disease: an integrative review

PURPOSE

The progression of Parkinson's disease causes an increase in motor dysfunctions, which makes it necessary to evaluate and monitor these changes. This integrative review aimed to gather studies - without any language restrictions - on the use, advantages and disadvantages of portable accelerometers for the evaluation of spatio-temporal gait parameters in people with Parkinson's disease published between 2014 and 2019.

METHODS

Articles were selected from the PubMed, Web of Science and Science Direct databases by combining descriptors from the Health Sciences Descriptors (DeCS) and Medical Subject Headings (MeSH) - "accelerometry", "accelerometer", "ActiGraph", "gait", "gait analysis", "gait rehabilitation", "walking inertial sensors", "Parkinson disease", "Parkinson" and "Parkinson's disease" - using OR and AND. The adapted Critical Appraisal Skill Program was used to analyze the methodological quality.

RESULTS

All the studies used portable wearable and wireless triaxial accelerometers. Among all types of accelerometers discussed, commercial wearable devices not based on smartphones and prototypes of wearable devices based and not based on smartphones can be pointed out. There was no standardization for the protocols of use, but the sensors were more often attached to the lower back (L3/L4/L5 vertebrae). The advantages included lower cost, possibility of use in outdoor environments and less complexity of data reading for non-specialized users. However, they still seem to show reduced precision and accuracy.

CONCLUSIONS

Due to the still insufficient number of articles published on the subject, we consider the need for further research, which should detail protocols of evaluation, advantages and disadvantages in stages of disease.

Wearable sensors can reliably quantify gait alterations associated with disability in people with progressive multiple sclerosis in a clinical setting

Gait disability in people with progressive multiple sclerosis (MS) is difficult to quantify using existing clinical tools. This study aims to identify reliable and objective gait-based biomarkers to monitor progressive multiple sclerosis (MS) in clinical settings. During routine clinical visits, 57 people with secondary progressive MS and 24 healthy controls walked for 6 minutes wearing three inertial motion sensors. Fifteen gait measures were computed from the sensor data and tested for between-session reliability, for differences between controls and people with moderate and severe MS disability, and for correlation with Expanded Disability Status Scale (EDSS) scores. The majority of gait measures showed good to excellent between-session reliability when assessed in a subgroup of 23 healthy controls and 25 people with MS. These measures showed that people with MS walked with significantly longer step and stride durations, reduced step and stride regularity, and experienced difficulties in controlling and maintaining a stable walk when compared to controls. These abnormalities significantly increased in people with a higher level of disability and correlated with their EDSS scores. Reliable and objective gait-based biomarkers using wearable sensors have been identified. These biomarkers may allow clinicians to quantify clinically relevant alterations in gait in people with progressive MS within the context of regular clinical visits.

Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis

BACKGROUND

Inertial measurement units (IMUs) offer the ability to measure walking gait through a variety of biomechanical outcomes (e.g., spatiotemporal, kinematics, other). Although many studies have assessed their validity and reliability, there remains no quantitive summary of this vast body of literature. Therefore, we aimed to conduct a systematic review and meta-analysis to determine the i) concurrent validity and ii) test-retest reliability of IMUs for measuring biomechanical gait outcomes during level walking in healthy adults.

METHODS

Five electronic databases were searched for journal articles assessing the validity or reliability of IMUs during healthy adult walking. Two reviewers screened titles, abstracts, and full texts for studies to be included, before two reviewers examined the methodological quality of all included studies. When sufficient data were present for a given biomechanical outcome, data were meta-analyzed on Pearson correlation coefficients (r) or intraclass correlation coefficients (ICC) for validity and reliability, respectively. Alternatively, qualitative summaries of outcomes were conducted on those that could not be meta-analyzed.

RESULTS

A total of 82 articles, assessing the validity or reliability of over 100 outcomes, were included in this review. Seventeen biomechanical outcomes, primarily spatiotemporal parameters, were meta-analyzed. The validity and reliability of step and stride times were found to be excellent. Similarly, the validity and reliability of step and stride length, as well as swing and stance time, were found to be good to excellent. Alternatively, spatiotemporal parameter variability and symmetry displayed poor to moderate validity and reliability. IMUs were also found to display moderate reliability for the assessment of local dynamic stability during walking. The remaining biomechanical outcomes were qualitatively summarized to provide a variety of recommendations for future IMU research.

CONCLUSIONS

The findings of this review demonstrate the excellent validity and reliability of IMUs for mean spatiotemporal parameters during walking, but caution the use of spatiotemporal variability and symmetry metrics without strict protocol. Further, this work tentatively supports the use of IMUs for joint angle measurement and other biomechanical outcomes such as stability, regularity, and segmental accelerations. Unfortunately, the strength of these recommendations are limited based on the lack of high-quality studies for each outcome, with underpowered and/or unjustified sample sizes (sample size median 12; range: 2-95) being the primary limitation.

Deep Learning Techniques for Improving Digital Gait Segmentation

Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously limited to specialist centres and equipment (e.g., instrumented walkway). In this study, we present a novel method based on dilated convolutions for an accurate detection of gait events (initial and final foot contacts) from wearable inertial sensors. A rich dataset has been used to validate the method, featuring 71 people with Parkinson's disease (PD) and 67 healthy control subjects. Multiple sensors have been considered, one located on the fifth lumbar vertebrae and two on the ankles. The aims of this study were: (i) to apply deep learning (DL) techniques on wearable sensor data for gait segmentation and quantification in older adults and in people with PD; (ii) to validate the proposed technique for measuring gait against traditional gold standard laboratory reference and a widely used algorithm based on wavelet transforms (WT); (iii) to assess the performance of DL methods in assessing high-level gait characteristics, with focus on stride, stance and swing related features. The results showed a high reliability of the proposed approach, which achieves temporal errors considerably smaller than WT, in particular for the detection of final contacts, with an inter-quartile range below 70 ms in the worst case. This study showes encouraging results, and paves the road for further research, addressing the effectiveness and the generalization of data-driven learning systems for accurate event detection in challenging conditions.

Does the Presence of Cognitive Impairment Exacerbate the Risk of Falls in People with Peripheral Neuropathy? An Application of Body-Worn Inertial Sensors to Measure Gait Variability

People with peripheral neuropathy (PN) are at risk of falling. Many people with PN have comorbid cognitive impairment, an independent risk factor of falls, which may further increase the risk of falling in people with PN. However, the negative synergic effect of those factors is yet to be reported. We investigated whether the presence of cognitive impairment exacerbates the risk of falls in people with PN by measuring gait variability during single-task walking and dual-task walking. Forty-four adults with PN were recruited. Based on the Montreal Cognitive Assessment (MoCA) scores, 19 and 25 subjects were cognitively impaired and intact, respectively. We measured coefficients of variation of gait speed, stride length, and stride time using validated body-worn sensors. During single-task walking, no between-group differences were observed (all p > 0.05). During dual-task walking, between-group differences were significant for gait variability for gait speed and stride length (51.4% and 71.1%, respectively; p = 0.014 and 0.011, respectively). MoCA scores were significantly correlated with gait variability for gait speed (r = 0.319, p = 0.035) and stride length (r = 0.367, p = 0.014) during dual-task walking. Our findings suggest that the presence of cognitive impairment exacerbates the risk of falls in people with PN.

Repetitive Motor Control Deficits Most Consistent Predictors of Conversion to Freezing of Gait in Parkinson's Disease: A Prospective Cohort Study

BACKGROUND

The onset of freezing of gait (FOG) represents a turning point in the lives of patients with Parkinson's disease (PD). FOG increases fall risk and is associated with worse physical and mental health related quality of life, thus increasing disease burden. Moreover, therapeutic studies aiming to ameliorate freezing have had limited success. In a step towards pre-emptive therapy to delay or prevent the onset of FOG, this prospective cohort study set out to uncover clinical markers of conversion to FOG.

OBJECTIVE

Investigate clinical markers of conversion to FOG.

METHODS

Sixty PD patients without FOG were followed up for two years and underwent extensive clinical testing each year. FOG classification was made with the New Freezing of Gait Questionnaire. Clinical predictors of conversion to FOG were investigated using univariate analysis and through building a multivariable model using all measured components.

RESULTS

Twelve patients developed FOG during the study (Incidence: 11.5% per year). Due to the large number of predictors, univariate analyses did not survive multiple comparison correction, precluding strong inference on any one predictor. Overall, the effect sizes suggested that motor deficits including difficulties with repetitive movement scaling (AUC: 0.71), coordination (AUC: 0.73) and consistency (AUC: 0.76) as well as gait asymmetry (AUC: 0.79) and variability (AUC: 0.71) were most predictive of conversion. Further, converters reported more subjective cognitive difficulty (AUC: 0.74), although their measured performance was similar to non-converters. Multivariable analyses further showed that the two components most consistently selected in the predictive model were: 1) an MDS-UPDRS component with worse axial motor, hand use and non-motor symptoms; and 2) finger tapping abnormalities.

CONCLUSION

Conversion to FOG was predicted mainly by objective and clinical measures of motor dyscontrol, as non-motor disturbances were surfacing. Although based on a small cohort with limited converters, this novel finding informs future studies aimed at FOG prevention.

Double obstacles increase gait asymmetry during obstacle crossing in people with Parkinson's disease and healthy older adults: A pilot study

Gait asymmetry during unobstructed walking in people with Parkinson’s disease (PD) has been well documented. However, under complex situations, such as environments with double obstacles, gait asymmetry remains poorly understood in PD. Therefore, the aim of this study was to analyze inter-limb asymmetry while crossing a single obstacle and double obstacles (with different distances between them) in people with PD and healthy older adults. Nineteen people with PD and 19 healthy older people performed three conditions: (i) walking with one obstacle (Single); (ii) walking with two obstacles with a 50 cm distance between them (Double-50); (iii) walking with two obstacles with a 108 cm distance between them (Double-108). The participants performed the obstacle crossing with both lower limbs. Asymmetry Index was calculated. We found that people with PD presented higher leading and trailing toe clearance asymmetry than healthy older people. In addition, participants increased asymmetry in the Double-50 compared to Single condition. It can be concluded that people with PD show higher asymmetry during obstacle crossing compared to healthy older people, independently of the number of obstacles. In addition, a challenging environment induces asymmetry during obstacle crossing in both people with PD and healthy older people.

The association between dual-task walking and counting responses and cognitive function and disability after severe head injury: A preliminary study

Adverse outcomes after severe head injury (SHI) can be difficult to detect in primary care and other settings where there is not specialist expertise for interpretation. Walking and counting dual-task (DT) measures are strongly associated with cognitive impairment and dementia and this preliminary study investigates whether performance on DT walking and counting tasks are associated with cognitive function and disability in 125 participants who sustained a SHI on average 26 years before. Single Task (ST) walking (speed over 6 metres) and ST counting (Serial 3s) and DT performance of concurrent walking and Serial 3s were compared with neuropsychological, wellbeing and disability tests for strength of association. The strongest correlations were between ST Correct Cognitive Responses (CCRs) and MMSE (rho = 0.435), DT CCRs and Short-term Memory Binding Tests (STMBT) binding accuracy (rho = 0,409) and DT CCRs and STROOP (rho = 0.420), but associations were less strong with disability. Developing this test, as a cost-efficient screening tool for triage to onward referral for neuropsychological assessment, holds promise, but requires further research.

The effects of dual-task in patients with Parkinson's disease performing cognitive-motor paradigms

Patients with Parkinson's disease (PD) exhibit impaired dual-task (DT) performance. A recent meta-analysis confirmed that dual tasking severely affects walking performance in PD patients. However, one report indicated that a cycling DT paradigm has facilitative effects on cognition. We investigated the effects of dual tasking by using walking and cycling as motor tasks and revealed the clinical determinants associated with DT performance. Twenty-seven eligible participants were enrolled for clinical, cognitive-walking, and cognitive-cycling DT paradigm investigations. The mean age and age at onset of the patients were 59.87 ± 6.3 and 53.11 ± 8.4 years, respectively. Both the off- and on-state akinesia subscores were worse on the more-affected side than on the less-affected side. However, the DT effects on the cycling and gait outcomes on both the more-affected and the less-affected side showed no significant differences. The DT effect on the two motor tasks and cognitive performance during a concurrent walking task declined. Nevertheless, the DT effect on cognition improved during cycling. The present study also revealed that the levodopa equivalent daily dosage was highly associated with cognitive-cycling performance and that the akinesia subscore was the most relevant factor that contributed to cognitive-walking performance. In conclusion, DT facilitation or interference might be mediated by the type of motor task applied. The cognitive-cycling DT paradigm had a facilitative effect on cognition. Cycling exercise may diminish motor dysfunction has been investigated. We suggest that cognitive-cycling DT training is a potential adjuvant therapeutic strategy for patients with PD to promote motor and cognitive functions.

Can Quantitative Gait Analysis Be Used to Guide Treatment of Patients with Different Subtypes of Parkinson's Disease?

PURPOSE

Gait impairment is a common clinical symptom of patients with Parkinson's disease (PD). Detecting specific gait parameters' changes in order to guide clinical intervention is at present lacking. The present study aimed to (1) quantify gait impairments in different PD subtypes and (2) explore whether the results of quantitative gait analysis are beneficial to clinical treatment.

PATIENTS AND METHODS

We enrolled 86 patients with PD (48 men, and 38 women) from the Department of Geriatrics of the Affiliated Brain Hospital of Nanjing Medical University. Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn-Yahr Scale were used to evaluate the motor symptoms of PD. All patients stopped anti-Parkinsonian medication for 24 hours (72 hours for controlled release medicine). The patients were divided into two subtypes, namely, postural instability gait difficulty (PIGD; n=56) and tremor dominant (TD; n=30) subtypes according to UPDRS. All patients completed the instrumented stand and walk test, and a set of JiBuEn gait analysis system was used in gait data collection.

RESULTS

We observed a shorter stride length (p=0.021), a longer stride time (p=0.036), a faster cadence (p=0.036), and a more variable stride length (p=0.012) in the PIGD group compared with the TD group. In addition, compared with the TD group, we found that the toe-off angle (p=0.005) and the range of motion of ankle joint (p=0.009) decreased in the PIGD group.

CONCLUSION

Our study demonstrated that the gait performance of patients with PIGD is worse than those with TD from the perspective of quantitative gait analysis. We extended previous research and found the PIGD group exhibited severe gait impairments in some specific spatiotemporal and kinematic gait parameters. The different manifestations of these gait impairments may guide in choosing appropriate treatment of patients with different PD subtypes.

Is a Wearable Sensor-Based Characterisation of Gait Robust Enough to Overcome Differences Between Measurement Protocols? A Multi-Centric Pragmatic Study in Patients with Multiple Sclerosis

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context.

Comparison of Walking Protocols and Gait Assessment Systems for Machine Learning-Based Classification of Parkinson's Disease

Early diagnosis of Parkinson's diseases (PD) is challenging; applying machine learning (ML) models to gait characteristics may support the classification process. Comparing performance of ML models used in various studies can be problematic due to different walking protocols and gait assessment systems. The objective of this study was to compare the impact of walking protocols and gait assessment systems on the performance of a support vector machine (SVM) and random forest (RF) for classification of PD. 93 PD and 103 controls performed two walking protocols at their normal pace: (i) four times along a 10 m walkway (intermittent walk-IW), (ii) walking for 2 minutes on a 25 m oval circuit (continuous walk-CW). 14 gait characteristics were extracted from two different systems (an instrumented walkway-GAITRite; and an accelerometer attached at the lower back-Axivity). SVM and RF were trained on normalized data (accounting for step velocity, gender, age and BMI) and evaluated using 10-fold cross validation with area under the curve (AUC). Overall performance was higher for both systems during CW compared to IW. SVM performed better than RF. With SVM, during CW Axivity significantly outperformed GAITRite (AUC: 87.83 ± 7.81% vs. 80.49 ± 9.85%); during IW systems performed similarly. These findings suggest that choice of testing protocol and sensing system may have a direct impact on ML PD classification results and highlight the need for standardization for wide scale implementation.

Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson's Disease: A Comprehensive Machine Learning Approach

Parkinson's disease (PD) is the second most common neurodegenerative disease; gait impairments are typical and are associated with increased fall risk and poor quality of life. Gait is potentially a useful biomarker to help discriminate PD at an early stage, however the optimal characteristics and combination are unclear. In this study, we used machine learning (ML) techniques to determine the optimal combination of gait characteristics to discriminate people with PD and healthy controls (HC). 303 participants (119 PD, 184 HC) walked continuously around a circuit for 2-minutes at a self-paced walk. Gait was quantified using an instrumented mat (GAITRite) from which 16 gait characteristics were derived and assessed. Gait characteristics were selected using different ML approaches to determine the optimal method (random forest with information gain and recursive features elimination (RFE) technique with support vector machine (SVM) and logistic regression). Five clinical gait characteristics were identified with RFE-SVM (mean step velocity, mean step length, step length variability, mean step width, and step width variability) that accurately classified PD. Model accuracy for classification of early PD ranged between 73-97% with 63-100% sensitivity and 79-94% specificity. In conclusion, we identified a subset of gait characteristics for accurate early classification of PD. These findings pave the way for a better understanding of the utility of ML techniques to support informed clinical decision-making.

Revealing the optimal thresholds for movement performance: A systematic review and meta-analysis to benchmark pathological walking behaviour

In order to address whether increased levels of movement output variability indicate pathological performance, we systematically reviewed and synthesized meta-analysis data on healthy and pathological motor behavior. After screening up to 24'000 reports from four databases, 85 studies were included containing 2409 patients and 2523 healthy asymptomatic controls. The optimal thresholds of variability with uncertainty boundaries (in % Coefficient of Variation ± Standard Error) were estimated in 7 parameters: stride time (2.34 ± 0.21), stride length (2.99 ± 0.37), step length (3.34 ± 0.84), swing time (2.94 ± 0.60), step time (3.35 ± 0.23), step width (15.87 ± 1.86), and dual-limb support time (6.08 ± 2.83). All spatio-temporal parameters exhibited a positive effect size (pathology led to increased variability) except step width variability (Effect Size = -0.21). By objectively benchmarking thresholds for pathological motor variability also presented through a case-study, this review provides access to movement signatures to understand neurological changes in an individual that are apparent in movement variability. The comprehensive evidence presented now qualifies stride time variability as a movement biomarker, endorsing its applicability as a viable outcome measure in clinical trials.

Proposal of a new conceptual gait model for patients with Parkinson's disease based on factor analysis

BACKGROUND

Gait impairment is a risk factor for falls in patients with Parkinson's disease (PD). Gait can be conveniently assessed by electronic walkways, but there is need to select which spatiotemporal gait variables are useful for assessing gait in PD. Existing models for gait variables developed in healthy subjects and patients with PD show some methodological shortcomings in their validation through exploratory factor analysis (EFA), and were never confirmed by confirmatory factor analysis (CFA). The aims of this study were (1) to create a new model of gait for PD through EFA, (2) to analyze the factorial structure of our new model and compare it with existing models through CFA.

RESULTS

From the 37 variables initially considered in 250 patients with PD, 10 did not show good-to-excellent reliability and were eliminated, while further 19 were eliminated after correlation matrix and Kaiser-Meyer-Olkin measure. The remaining eight variables underwent EFA and three factors emerged: pace/rhythm, variability, and asymmetry. Structural validity of our new model was then examined with CFA, using the structural equation modeling. After some modifications, suggested by the Modification Indices, we obtained a final model that showed an excellent fit. In contrast, when the structure of previous models of gait was analyzed, no model achieved convergence with our sample of patients.

CONCLUSIONS

Our model for spatiotemporal gait variables of patients with PD is the first to be developed through an accurate EFA and confirmed by CFA. It contains eight gait variables divided into three factors and shows an excellent fit. Reasons for the non-convergence of other models could be their inclusion of highly inter-correlated or low-reliability variables or could be possibly due to the fact that they did not use more recent methods for determining the number of factors to extract.

Upper body accelerations as a biomarker of gait impairment in the early stages of Parkinson's disease

BACKGROUND

Changes in upper body (UB) motion during gait may be a marker of incipient pathology, intervention response and disease progression in Parkinson's disease (PD), which if independent from the lower body motion, might provide an improved assessment of gait.

RESEARCH QUESTION

This study aimed to test this hypothesis and establish whether variables calculated from accelerations measured on the UB are unique from spatiotemporal characteristics and can contribute to an improved classification of PD gait.

METHODS

Data was obtained from 70 people with PD (69.2 ± 9.9 y.o.

, UPDRS III

36.9 ± 12.3) and 64 age-matched controls (71.6 ± 6.8 y.o.). Spatiotemporal characteristics were measured using a pressure sensitive mat (GAITRite). Head and pelvis accelerations were synchronously measured with wearable inertial sensors (Opal, APDM). Pearson's product-moment correlations were calculated between 49 selected variables from UB accelerations (representing magnitude, smoothness, regularity, symmetry and attenuation) and 16 traditional spatiotemporal characteristics (representing pace, variability, rhythm, asymmetry and postural control). Univariate and multivariate regression analysis was used to test the variables ability to classify PD gait.

RESULTS

The variables were mostly unique from each other (67% of variables recorded an r < 0.3). Univariate and multivariate analysis showed that UB variables were moderately better at classifying PD gait than the spatiotemporal characteristics (Univariate: 0.70 to 0.81, Multivariate: 0.88 to 0.91 AUC).

SIGNIFICANCE

This study showed for the first time that, if aiming at objective and optimal sensitive biomarkers for PD, UB variables should be measured in conjunction with spatiotemporal characteristics to obtain a more holistic assessment of PD gait for use in a clinical or free-living environment.

Avoiding Virtual Obstacles During Treadmill Gait in Parkinson's Disease

Falls often occur due to spontaneous loss of balance, but tripping over an obstacle during gait is also a frequent cause of falls (Sheldon, 1960; Stolze et al., 2004). Obstacle avoidance requires that appropriate modifications of the ongoing cyclical movement be initiated and completed in time. We evaluated the available response time to avoid a virtual obstacle in 26 Parkinson’s disease (PD) patients (in the off-medication state) and 26 controls (18 elderly and 8 young), using a virtual obstacle avoidance task during visually cued treadmill walking. To maintain a stable baseline of stride length and visual attention, participants stepped on virtual “stepping stones” projected onto a treadmill belt. Treadmill speed and stepping stone spacing were matched to overground walking (speed and stride length) for each individual. Unpredictably, a stepping stone changed color, indicating that it was an obstacle. Participants were instructed to try to step short to avoid the obstacle. By using an obstacle that appeared at a precise instant, this task probed the time interval required for processing new information and implementing gait cycle modifications. Probability of successful avoidance of an obstacle was strongly associated with the time of obstacle appearance, with earlier-appearing obstacles being more easily avoided. Age was positively correlated (p < 0.001) with the time required to successfully avoid obstacles. Nonetheless, the PD group required significantly more time than controls (p = 0.001) to achieve equivalent obstacle-avoidance success rates after accounting for the effect of age. Slowing of gait adaptability could contribute to high fall risk in elderly and PD. Possible mechanisms may include disturbances in motor planning, movement execution, or disordered response inhibition.

Characteristics for gait parameters of community-dwelling elderly Japanese with lower cognitive function

Objectives

Recent studies reported that several gait parameters were associated with lower cognitive function or cognitive decline, however, known gait parameters were limited and no study has used large-scale data. We identified the characteristics for gait parameters of community-dwelling elderly Japanese with lower cognitive function.

Methods

1,240 community-dwelling adults (mean [SD] age, 77.2 [4.8] years; women, 59.4%) aged 70 or older participated in geriatric health assessments in 2016. We measured comprehensive gait parameters using resistive pressure platform. Cognition was assessed by Mini-Mental State Examination (MMSE).

Results

There are possible correlations between gait measures (gait speed, stride length, step length, step width, average foot pressure, double support duration, and single support duration) and CVs (CV of stride length, step length, average foot pressure, and single support duration) with MMSE score, respectively. After adjustment for important confounders, multiple regression models showed that gait speed (β = .080, p = 0.006), stride length (β = .123, p<0.001), step length (β = .123, p<0.001), average foot pressure (β = .060, p = 0.040), double support duration (β = -.082, p = 0.004), single support duration (β = .086, p = 0.003), CV of stride length (β = -.091, p<0.001), CV of step length (β = -.090, p<0.001), and CV of single support duration (β = -.058, p = 0.037) had significant association with MMSE score, respectively.

Conclusions

Our findings suggest that person with lower cognitive function tend to have unsteady gait such as erratic length and time of one step, in addition to decreasing the vertical displacement of the center of gravity and slower speed.

A Home-Based, Music-Cued Movement Program Is Feasible and May Improve Gait in Progressive Supranuclear Palsy

Objectives: To understand the benefits and feasibility of using supervised, home-based, music-cued training to improve gait speed and stability in community-dwelling people with Progressive Supranuclear Palsy.

Design: Feasibility trial incorporating a single group repeated-measures design.

Setting: Human movement laboratory and participants' homes.

Interventions:Two training sessions per week, conducted by experienced physiotherapists over 4 weeks. Each home training session consisted of a range of activities in standing or walking, with, and without auditory cues. Rhythmic auditory cues were played via a portable digital music player and consisted of metronome beats and individually chosen, commercially available rhythmic music tracks.

Main Outcome Measures: Spatiotemporal gait measures were recorded using an 8 m long GAITRite® mat. Participants walked without cues at self-selected comfortable pace. The Progressive Supranuclear Palsy and Unified Parkinson's Disease Rating Scales were administered at baseline. Addenbrooke's Cognitive Examination-III, Geriatric Depression Scale, Assessment of Personal Music Preference Scale, and Physiological Profile Assessment were administered at baseline and retest.

Results: At baseline, two of the five community-dwelling participants with Progressive Supranuclear Palsy walked with normal speed and low gait variability. Of the remainder who walked with slower, more variable patterns, two walked faster at retest, one by a clinically meaningful amount. Four participants reduced their timing variability at retest and three reduced step length variability. All participants reported high satisfaction levels with the program.

Conclusions: When delivered at home with the support of caregivers, music-cued gait training can provide a feasible approach to improving disorders of gait stability in people with this rare, degenerative condition. Movement to music is engaging and enjoyable which can facilitate adherence to therapy.

Clinical Trial Registration : ANZCTR 12616000851460. http://www.anzctr.org.au/

The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control

Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions-including Parkinson's disease, ataxia, and dementia-we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel 'big data' approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.

Less Is More - Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings

Background: Gait variability is an established marker of gait function that can be assessed using sensor-based approaches. In clinical settings, spatial constraints and patient condition impede the execution of longer distance walks for the recording of gait parameters. Turning paradigms are often used to overcome these constraints and commercial gait analysis systems algorithmically exclude turns for gait parameters calculations. We investigated the effect of turns in sensor-based assessment of gait variability.

Methods: Continuous recordings from 31 patients with movement disorders (ataxia, essential tremor and Parkinson’s disease) and 162 healthy elderly (HE) performing level walks including 180° turns were obtained using an inertial sensor system. Accuracy of the manufacturer’s algorithm of turn-detection was verified by plotting stride time series. Strides before and after turn events were extracted and compared to respective average of all strides. Coefficient of variation (CoV) of stride length and stride time was calculated for entire set of strides, segments between turns and as cumulative values. Their variance and congruency was used to estimate the number of strides required to reliably assess the magnitude of stride variability.

Results: Non-detection of turns in 5.8% of HE lead to falsely increased CoV for these individuals. Even after exclusion of these, strides before/after turns tended to be spatially shorter and temporally longer in all groups, contributing to an increase of CoV at group level and widening of confidence margins with increasing numbers of strides. This could be attenuated by a more generous turn excision as an alternative approach. Correlation analyses revealed excellent consistency for CoVs after at most 20 strides in all groups. Respective stride counts were even lower in patients using a more generous turn excision.

Conclusion: Including turns to increase continuous walking distance in spatially confined settings does not necessarily improve the validity and reliability of gait variability measures. Specifically with gait pathology, perturbations of stride characteristics before/after algorithmically excised turns were observed that may increase gait variability with this paradigm. We conclude that shorter distance walks of around 15 strides suffice for reliable and valid recordings of gait variability in the groups studied here.

Cognitive function impacts gait, functional mobility and falls in fragile X-associated tremor/ataxia syndrome

BACKGROUND

Executive function and information processing speed deficits occur in fragile X premutation carriers (PMC) with and without fragile X-associated tremor/ataxia syndrome (FXTAS). Gait is negatively impacted by cognitive deficits in many patient populations resulting in increased morbidity and falls but these relationships have not been studied in FXTAS.

RESEARCH QUESTION

We sought to investigate the associations between executive function and information processing speed and gait, turning and falls in PMC with and without FXTAS compared to healthy controls.

METHODS

Global cognition and the cognitive domains of information processing speed, attention, response inhibition, working memory and verbal fluency were tested with a neuropsychological test battery in 18 PMC with FXTAS, 15 PMC without FXTAS, and 27 controls. An inertial sensor based instrumented Timed Up and Go was employed to test gait, turns and functional mobility.

RESULTS

Lower information processing speed was significantly associated with shorter stride length, reflecting slower gait speed, in PMC with FXTAS (p = 0.0006) but not PMC without FXTAS or controls. Lower response inhibition was also significantly associated with slower turn-to-sit times in PMC with FXTAS (p = 0.034) but not in those without FXTAS or controls. Lower information processing speed (p = 0.012) and working memory (p = 0.004), were significantly correlated with a greater number of self-reported falls in the past year in FXTAS participants.

SIGNIFICANCE

This is the first study demonstrating that worse executive function and slower information processing speed is associated with reduced gait speed and functional mobility, as well as with a higher retrospective fall history in participants with FXTAS. This information may be important in the design of cognitive and motor interventions for this neurodegenerative disorder.

Patient-reported and performance-based measures of walking in mild-moderate Parkinson's disease

BACKGROUND

Knowledge of the relationships between patient-reported and performance-based walking measures in Parkinson's disease (PD) should inform clinical decision-making. The Walk-12G reliably captures perceived walking difficulties but has not been compared to performance-based walking in laboratory or free-living settings or across different groups.

OBJECTIVES

To investigate the relationship between patient-reported walking difficulties (Walk-12G) and performance-based walking in laboratory and free-living conditions and to determine whether the Walk-12G can distinguish between the subgroups, (i) people with/without PD and (ii) mild/moderate disease stages.

METHODS

Forty-seven people without and 49 people with PD (Hoehn and Yahr stage II and III) were assessed in relation to patient-reported walking difficulties (Walk-12G scale); spatiotemporal gait characteristics (Pace; Rhythm; Asymmetry; Variability; and Postural control) using a laboratory-based electronic walkway; and walking behavior (mean steps/day and minutes of brisk walking/day) using accelerometers in free-living conditions.

RESULTS

The Walk-12G correlated moderately with the spatiotemporal domain step velocity (r = -0.46) and walking behavior, measured as mean steps/day (r = -0.46). Weaker correlations were observed for step length and minutes spent in brisk walking (r = -0.36 and r = -0.35, respectively). Poor correlations were observed for all other spatiotemporal domains. The Walk-12G could distinguish between people with and without PD (Effect size, r = 0.82) and between those at mild/moderate disease stages (r = 0.34).

CONCLUSIONS

Perceived walking difficulties showed weak to moderate associations with performance-based measures of walking in mild-moderate PD. As the strongest associations were observed for step velocity and walking behavior, targeting these specific gait aspects could improve perceived walking difficulties in daily life.

A comparison of a step-initiation task in women with and without urinary incontinence. A case-control study

AIMS

The aim of the study was to objectively determine differences in postural response by women with and without urinary incontinence during a step-initiation task depending on the degree of bladder filling.

METHODS

The study comprised 22 women with stress urinary incontinence and 20 women without urinary incontinence. All women participated in four trials: unperturbed and perturbed (obstacle crossing) transition between platforms, step-up and step-down trials. Velocities of center of pressure displacement, double-support period, time from exit from steady standing until the lead foot resting on the other platform and time from raising the foot from the first platform until gaining quiet standing on the other platform were measured and compared.

RESULTS

No significant differences were noted between the performance of a step-initiation task by incontinent women with full/empty bladder whereas continent women performed differently during unperturbed transition with full/empty bladder. The step-up trial revealed significant intergroup differences. The antero-posterior mean velocity of center of pressure during the empty bladder test was significantly higher in women with stress urinary incontinence (effect size = 1.02). During the same bladder condition the women with stress urinary incontinence performed significantly more slowly in unperturbed (effect size = 1.09) and perturbed (effect size = 0.84) transition compared to control group.

CONCLUSIONS

Our results indicate that women with incontinence performed the step initiation task slowly on the empty bladder tests compare to continent women.