Gait Tasks Research Articles

Narrow doorways alter brain connectivity and step patterns in isolated REM sleep behaviour disorder

BackgroundMotor impairments in those with isolated REM sleep behaviour disorder (iRBD) significantly increases the likelihood of developing Lewy body disease (e.g. Parkinson’s disease and Dementia with Lewy Bodies). ObjectiveThis study sought to explore the prodromal process of neurodegeneration by examining the neural signature underlying motor deficits in iRBD patients. MethodsA virtual reality (VR) gait paradigm (which has previously been shown to elicit adaptive changes in gait performance whilst navigating doorways in Parkinson’s Disease - PD) was paired with fMRI to investigate whether iRBD patients demonstrated worsened motor performance and altered connectivity across frontoparietal, motor and basal ganglia networks compared to healthy controls. Forty participants (23 iRBD and 17 healthy controls) completed the virtual reality gait task whilst in the MRI scanner, and an additional cohort of 19 Early PD patients completed the behavioural virtual reality gait task. ResultsAs predicted, iRBD patients demonstrated slower and more variable stepping compared to healthy control participants and demonstrated an exaggerated response when navigating narrow compared to wide doorways, a phenomenon characteristically seen in PD. The iRBD patients also demonstrated less BOLD signal change in the left posterior putamen and right mesencephalic locomotor region, as well as reduced functional connectivity between the frontoparietal network and the motor network, when navigating narrow versus wide doorways compared to healthy control participants. ConclusionsTaken together, this study demonstrates that iRBD patients have altered task-related brain connectivity, which may represent the neural underpinnings of early motor impairments that are evident in iRBD.

Resting-State Cortical Connectivity Underlying Cognitive-Motor Interactions in Gait and Postural Tasks in Young Adults

The purpose of this study is to determine the relationship between intra- and internetwork connectivity and DTC of postural, gait, and cognitive performance in healthy, young adults. Dual-task (DT) deficits persist after return to activity in those recovering from a sports related concussion. However, little is known about the relationship of cortical network function to DT capacity. Current evidence regarding the relationship between network connectivity and dual-task balance and gait performance is limited by focusing on older adults and those with cognitive impairments, using a condensed set of task demands, and neglecting the role of connectivity in the ability to adapt to minimize DT cost (DTC). Twelve adults (7 females; age: 23.41 ± 2.74 years; height: 1.73 ± 0.10 m; weight: 72.66 ± 11.25 kg) volunteered for this study. Participants completed resting-state functional magnetic resonance imaging, as well as single and DT variants of the Concussion Balance Test, Sensory Organization Test, and gait. Functional connectivity within and between the default mode (DMN), salience (SAL), and sensorimotor (SMN) networks were calculated for all subjects. Pearson's correlations were used to assess the association of connectivity to balance and gait speed DTC. Inter-network connectivity between to DMN to the SAL and SMN demonstrated moderate to strong association to DTC of gait speed and postural control during tasks which perturbed sensory environments (r = -0.59 to 0.94, p < 0.05). There was no relationship between connectivity and DTC of cognitive performance during DT (r = -0.50 to 0.54, p > 0.05). Our findings highlight the role of the SAL, SMN, and DMN in cognitive-motor interactions during gait and postural control. Furthermore, functional connectivity underlying DT gait and static postural control performance express inverse relationships, suggesting task-dependent differences in system level processing.

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

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

Healthy Knee Kinematic Phenotypes Identification Based on a Clustering Data Analysis

The purpose of this study is to identify healthy phenotypes in knee kinematics based on clustering data analysis. Our analysis uses the 3D knee kinematics curves, namely, flexion/extension, abduction/adduction, and tibial internal/external rotation, measured via a KneeKG™ system during a gait task. We investigated two data representation approaches that are based on the joint analysis of the three dimensions. The first is a global approach that is considered a concatenation of the kinematic data without any dimensionality reduction. The second is a local approach that is considered a set of 69 biomechanical parameters of interest extracted from the 3D kinematic curves. The data representations are followed by a clustering process, based on the BIRCH (balanced iterative reducing and clustering using hierarchies) discriminant model, to separate 3D knee kinematics into homogeneous groups or clusters. Phenotypes were obtained by averaging those groups. We validated the clusters using inter-cluster correlation and statistical hypothesis tests. The simulation results showed that the global approach is more efficient, and it allows the identification of three descriptive 3D kinematic phenotypes within a healthy knee population.

To Study the Effect of Smartphone Multitasking on Dynamic Balance in Young Adults

The objectives of this research was to see how using smartphone functions during gait affected dynamicbalance. From a university, a sample of 100 subjects was taken. Four types of gait tasks were given:General Gait (to walk without any task); Task Gait 1 (to walk while chatting through text); Task Gait2 (to walk while web surfing and hearing music) and Task Gait 3 (to walk while playing an onlinemultiplayer videogame). The conditions were the same for all the experiments. The subjects usedearphones for listening to music and having conversation during games. The sequence of tasks wasnot done in systematic manner. The Timed Up and Go (TUG) test was used to assess dynamic balance.After three repetitions of the tasks, the mean of the measured values was analysed. In the TUG tests,there were statistically significant unfavourable differences. Use of smartphone features during walkingaffects dynamic balance of a person. As a result, when ambulating, using various features of a cellphone may result in falls and injuries.

An inertial sensor-based algorithm for turning detection during gait.

Patients with Parkinson's disease (PD) can be divided into two subtypes based on clinical features, namely tremor-dominant (TD) and postural instability and gait difficulty (PIGD). Detection of PIGD symptoms is crucial for early diagnosis of PD and timely clinical intervention. However, patients at the early stage may not exhibit obvious motor dysfunctions during normal straight walking leading to difficulties in PD identification. Researchers have found that patients would show significant motor deteriorations in turning due to their cognition limitation. Therefore, turning detection is essential for quantitative motion analysis in the gait assessment of PD patients. In this study, we proposed a novel inertial-sensor-based algorithm for turning detection. Ten healthy young participants were enrolled in the experiment where they were required to walk along a 7-meter pathway with two 180 degree turns at their comfortable walking speed. Five inertial sensors were attached to the upper trunk, the shank and the foot of both legs. The algorithm performance was validated using an optical motion capture system for reference and two sensor combination options (upper trunk and shank sensors, upper trunk and foot sensors) were compared. The results showed that the proposed algorithm achieved accuracy over 98% for identifying the turning state of both legs. The integration of the upper trunk and foot sensors had no significant effect on the detection accuracy compared to that with the use of the upper trunk and shank sensors. Our algorithm has the potential to be implemented in the motion analysis model for complicated gait tasks, which has great potential in the early diagnosis of PIGD.

Cortical activation during gait adaptability in people with Parkinson’s disease

BackgroundPeople with Parkinson’s disease (PD) have difficulties adapting their gait. While underlying neural mechanisms involving the prefrontal cortex (PFC) have been studied across various complex walking tasks, less is known about the premotor cortex (PMC) and supplementary motor area (SMA), key cortical regions for motor planning. This study compared frontal cortical regions activation patterns using functional near-infrared spectroscopy (fNIRS), between people with PD and healthy controls (HC) during gait adaptability tasks. MethodsForty-nine people with PD (mean (SD) age: 69.5 (7.9) years) and 21 HC (69.0 (5.9) years) completed a simple walk and three randomly presented gait adaptability tasks: (i) stepping on targets, (ii) avoiding obstacles and (iii) negotiating both targets and obstacles. Cortical activity in the dorsolateral PFC (DLPFC), SMA and PMC were recorded using fNIRS. Step length, velocity and accuracy and cortical activity were contrasted between the groups and walking conditions. ResultsCompared with the HC, the PD group exhibited greater PMC activation and walked significantly slower and took shorter steps in all conditions. A statistically significant group by condition interaction indicated an increase in DLPFC cortical activation in the HC participants when undertaking the obstacle avoidance task compared with the simple walk but no increase in cortical activation in the PD group when undergoing this more challenging gait task. ConclusionsOur findings suggest people with PD have little or no DLPFC, SMA and PMC capacity beyond what they need for simple walking and in consequence need to slow their gait velocity to meet the demands of target stepping and obstacle avoidance tasks. Such behavioral and neural patterns appear consistent with concepts of compensatory over-activation and capacity limitation.

Does Energy Drink Provokes Gait Modifications in Young Healthy Adults?

Energy drinks have become increasingly popular among young adults and athletes in the last few years. Despite their popularity, little research has substantiated the claims of the positive effects on physical performance of popular energy drinks. Most current research focuses on caffeine alone, but does not often look at how mixing it with other psychoactive substances might alter its effects. Purpose: This study aimed to determine the alterations of gait tasks after consumption of three popular energy drinks on young healthy adults. Methods: Fifteen women and five men were recruited, screened, and signed informed consent to participate in this study. All participants were healthy young adults with no apparent comorbidities that might have been impacted by the consumption of energy drinks. Motion analysis was conducted using Movement Lab TM sensors placed at key anatomical points. Subjects were asked for two bouts of gait tasks pre-energy drink consumption, and then repeat the same tasks after energy drink consumption. Results: There were no significant modifications in gait, however, observable trends were detected in postural gait parameters following the consumption of a Rockstar energy drink. Conclusion: We infer that the trends observed could be attributed to the specific key ingredients used in Rockstar and might have caused gait deviations post consumption. Further studies should focus on Rockstar alone and its specific key ingredients of caffeine, guarana, ginseng, and milk thistle to determine their influence on gait deviations.

Development and Evaluation of a Prosthetic Ankle Emulator With an Artificial Soleus and Gastrocnemius

Abstract In individuals with transtibial limb loss, a contributing factor to mobility-related challenges is the disruption of biological calf muscle function due to transection of the soleus and gastrocnemius. Powered prosthetic ankles can restore primary function of the mono-articular soleus muscle, which contributes to ankle plantarflexion. In effect, a powered ankle acts like an artificial soleus (AS). However, the biarticular gastrocnemius connection that simultaneously contributes to ankle plantarflexion and knee flexion torques remains missing, and there are currently no commercially available prosthetic ankles that incorporate an artificial gastrocnemius (AG). The goal of this work is to describe the design of a novel emulator capable of independently controlling artificial soleus and gastrocnemius behaviors for transtibial prosthesis users during walking. To evaluate the emulator's efficacy in controlling the artificial gastrocnemius behaviors, a case series walking study was conducted with four transtibial prosthesis users. Data from this case series showed that the emulator exhibits low resistance to the user's leg swing, low hysteresis during passive spring emulation, and accurate force tracking for a range of artificial soleus and gastrocnemius behaviors. The emulator presented in this paper is versatile and can facilitate experiments studying the effects of various artificial soleus and gastrocnemius dynamics on gait or other movement tasks. Using this system, it is possible to address existing knowledge gaps and explore a wide range of artificial soleus and gastrocnemius behaviors during gait and potentially other activities of daily living.

Analysis of gait synchrony and balance in neurodevelopmental disorders using computer vision techniques.

Gait tasks are commonly administered during motor assessments of children with neurodevelopmental disorders (NDDs). Gait analyses are often conducted in laboratory settings using costly and cumbersome experiments. In this paper, we propose a computational pipeline using computer vision techniques as an ecological and precise method to quantify gait in children with NDDs with challenging behaviors. We analyzed videos of 15 probands (PB) and 12 typically developing (TD) siblings, engaged in a preferred-pace walking task, using pose estimation software to track points of interest on their bodies over time. Analyzing the extracted information revealed that PB children had significantly less whole-body gait synchrony and poorer balance compared to their TD siblings. Our work offers a cost-effective method while preserving the validity of its results. This remote approach increases access to more diverse and distant cohorts and thus lowers barriers to research participation, further enriching our understanding of motor outcomes in NDDs.

Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition

Computer interfaces with visual biofeedback (BF) capabilities in robot-assisted gait training applications can help design subject-specific therapies, define tasks based on the patient's condition, and increase the training outcomes. This study presents the use of an open-source real-time computer interface as a subject-specific visual BF and monitoring tool during gait. The interface is used in combination with a low-cost Wearable integrated Sensor System for Data Acquisition (WiSSDA), which consists of a 3-D printed lower extremity exoskeleton equipped with rotary encoders and pressure-sensitive insoles that measure biometric data during the gait cycle. The system obtains the lower extremities’ joint kinematics in the sagittal plane and estimates the vertical component of the foot contact forces and the foot center of pressure. Experimental tests were performed to evaluate different gait parameters using the computer interface as visual BF to guide the subject with reference boundaries of kinematic and kinetic parameters as target trajectories. The results were used to evaluate the interface's performance for specific gait tasks. The results demonstrated the capabilities of the computer interface combined with WiSSDA for robot-assisted gait training applications using BF; providing an open-source, portable, and ambulatory device that can be used in outdoor environments. The proposed system can help bring gait rehabilitation outside the laboratory environment, eliminating the need for stationary equipment.

Brain Activity in the Prefrontal Cortex during Cognitive Tasks and Dual Tasks in Community-Dwelling Elderly People with Pre-Frailty: A Pilot Study for Early Detection of Cognitive Decline.

We aimed to detect brain abnormalities during cognitive and motor tasks in older individuals with pre-frailty, as this could prevent dementia. Sixty elderly participants (mean age: 76.3 years; 27 healthy and 33 with pre-frailty) were included, and their motor function, cognitive function, and dual-task abilities (gait with calculation and while carrying a ball) were evaluated. Total hemoglobin (t-Hb) was measured using functional near-infrared spectroscopy (fNIRS) during tasks and resting periods. The pre-frailty group had a slightly lower gait speed than the healthy group, but there was no significant difference in cognitive function. In the pre-frailty group, the t-Hb values during the normal gait and cognitive tasks were higher than the resting value in the right prefrontal cortex, while in the healthy group, only the word frequency task (WFT) was higher. Furthermore, in the WFT, the t-Hb values were significantly lower in the pre-frailty group than in the healthy group. The results showed that pre-frail subjects had lower brain activation during the WFT in the right prefrontal cortex and excessive activity during walking, even without a noticeable cognitive decline. The differences in cerebral blood flow under the pre-frailty conditions may be a clue to detecting cognitive decline earlier.

Exploring Test-Retest Reliability and Longitudinal Stability of Digital Biomarkers for Parkinson Disease in the m-Power Data Set: Cohort Study.

BackgroundDigital biomarkers (DB), as captured using sensors embedded in modern smart devices, are a promising technology for home-based sign and symptom monitoring in Parkinson disease (PD).ObjectiveDespite extensive application in recent studies, test-retest reliability and longitudinal stability of DB have not been well addressed in this context. We utilized the large-scale m-Power data set to establish the test-retest reliability and longitudinal stability of gait, balance, voice, and tapping tasks in an unsupervised and self-administered daily life setting in patients with PD and healthy controls (HC).MethodsIntraclass correlation coefficients were computed to estimate the test-retest reliability of features that also differentiate between patients with PD and healthy volunteers. In addition, we tested for longitudinal stability of DB measures in PD and HC, as well as for their sensitivity to PD medication effects.ResultsAmong the features differing between PD and HC, only a few tapping and voice features had good to excellent test-retest reliabilities and medium to large effect sizes. All other features performed poorly in this respect. Only a few features were sensitive to medication effects. The longitudinal analyses revealed significant alterations over time across a variety of features and in particular for the tapping task.ConclusionsThese results indicate the need for further development of more standardized, sensitive, and reliable DB for application in self-administered remote studies in patients with PD. Motivational, learning, and other confounders may cause variations in performance that need to be considered in DB longitudinal applications.

A Dual-Task Paradigm Using the Oral Trail Making Test While Walking to Study Cognitive-Motor Interactions in Older Adults.

Objective: With aging, gait becomes more dependent on executive functions, especially on switching abilities. Therefore, cognitive-motor dual-task (DT) paradigms should study the interferences between gait and switching tasks. This study aimed to test a DT paradigm based on a validated cognitive switching task to determine whether it could distinguish older-old adults (OO) from younger-old adults (YO).Methods: Sixty-five healthy older participants divided into 29 younger-old (<70 years) and 36 older-old (≥70 years) age groups were evaluated in three single-task (ST) conditions as follows: a cognitive task including a processing speed component [Oral Trail Making Test part A (OTMT-A)], a cognitive task including a switching component [Oral Trail Making Test part B (OTMT-B)], and a gait evaluation at normal speed. They were also evaluated under two DT conditions, i.e., one associating gait with OTMT-A and the other associating gait with OTMT-B. Cognitive and gait performances were measured. The comparison of cognitive and gait performances between condition, logistic regression, and receiver operating characteristic (ROC) analyses were performed.Results: The cognitive and gait performances were differently affected by the different conditions (i.e., ST, DT, OTMT-A, and OTMT-B). The OTMT-B produced higher interference on gait and cognitive performances. Moreover, a higher number of errors on the OTMT-B performed while walking was associated with the older-old age group.Conclusion: Using validated cognitive flexibility tasks, this DT paradigm confirms the high interference between switching tasks and gait in older age. It is easily implemented, and its sensitivity to age may highlight its possible usefulness to detect cognitive or motor declines.

Task dependent changes in mechanical and biomechanical measures result from manipulating stiffness settings in a prosthetic foot

BackgroundAdaptation of lower limb function to different gait tasks is inherently not as effective among individuals with lower limb amputation as compared to able-bodied individuals. Varying stiffness of a prosthetic foot may be a way of facilitating gait tasks that require larger ankle joint range of motion. MethodsThree stiffness settings of a novel prosthetic foot design were tested for level walking at three speeds as well as for 7,5° incline and decline walking. Outcome measures, describing ankle range of motion and ankle dynamic joint stiffness were contrasted across the three stiffness settings. Standardized mechanical tests were done for the hindfoot and forefoot. FindingsDorsiflexion angle was incrementally increased with a softer foot and a faster walking speed / higher degree of slope. The concurrent dynamic joint stiffness exhibited a less systematic change, especially during INCLINE and DECLINE walking. The small difference seen between the stiffness settings for hindfoot loading limits analysis for the effects of stiffness during weight acceptance, however, a stiffer foot significantly restricted plantarflexion during DECLINE. InterpretationsVarying stiffness settings within a prosthetic foot does have an effect on prosthetic foot dynamics, and differences are task dependent, specifically in parameters involving kinetic attributes. When considering the need for increased ankle range of motion while performing more demanding gait tasks, a foot that allows the users themselves to adjust stiffness according to the task at hand may be of benefit for active individuals, possibly enhancing the user's satisfaction and comfort during various daily activities.

Metrics for quantifying cognitive factors that may underlie individual variation in exoskeleton use

Individual differences in adaptation to exoskeletons have been observed, but are not well understood. Kinematic, kinetic, and physiologic factors are commonly used to assess these systems. Parameters from experimental psychology and gait literature wereadapted to probe the lower extremity perception-cognition-action loop using measures of reaction times, gait task performance, and gait strategy. Parameters were measured in 15 subjects via two tasks: (1) a modified Simon task and (2) a speed-achievement task with secondary go/no-go cues on a self-paced treadmill. Outcome metrics were assessed for significantly different intra- versus inter-subject variability. Reaction time measures from the modified Simon task, as well two speed-achievement metrics and one gait-strategy characteristic we re found to show significant differenc es in intra- versus inter-subject variability. These results suggest that select cognitive factors may differentiate between individuals and be potential predictors for individual variation during exoskeleton system operation.

Comparing sagittal plane kinematics and kinetics of gait and stair climbing between hypermobile and non-hypermobile people; a cross-sectional study

BackgroundJoint Hypermobility Syndrome (JHS) presents with a range of symptoms including widespread joint hypermobility and chronic arthralgia. The study objective was to investigate whether impairments in JHS are due to hypermobility or another factor of JHS by identifying impairments in gait and stair-climbing tasks; an activity that is demanding and so may better show differences between the cohorts.MethodsSixty-eight adults participated; 23 JHS, 23 Generalised Joint Hypermobility (GJH), and 22 Normal Flexibility (NF). Inclusion criteria for JHS participants were a positive classification using the Brighton Criteria, for GJH a Beighton Score ≥ 4, and for NF a Beighton Score < 4 with no hypermobile knees. Participants were recorded with a 10-camera Vicon system whilst they performed gait and stair-climbing. Temporal-spatial, and sagittal plane kinematic and kinetic outcome measures were calculated and input to statistical analyses by statistical parametric mapping (SPM).ResultsDuring the gait activity JHS had significantly greater stride time and significantly lower velocity than NF, and significantly greater stride time, lower velocity, and lower stride length than GJH. SPM analysis showed no significant differences between groups in gait kinematics. There were significant differences between groups for gait moments and powers; people with JHS tended to have lower moments and generate less power at the ankle, and favour power generation at the knee. A similar strategy was present in stair ascent. During stair descent people with JHS showed significantly more hip flexion than people with NF.ConclusionsAs there was only one significant difference between GJH and NF we conclude that impairments cannot be attributed to hypermobility alone, but rather other factor(s) of JHS. The results show that both gait and stair-climbing is impaired in JHS. Stair-climbing results indicate that JHS are using a knee-strategy and avoiding use of the ankle, which may be a factor for clinicians to consider during treatment.

Deep neural network approach for estimating the three-dimensional human center of mass using joint angles

Human body center of mass location plays an essential role in physical therapy, especially in investigating a subject’s capability to maintain balance. However, its estimation can be a very complex, costly, and time-consuming process. To overcome the complexities and reduce the hardware cost, we proposed a deep neural network model to map the measurements of body joint angles to the 3-D center of mass position. We used an inertial measurement units-based motion-capture system (Xsens MVN Awinda) to record the joint angles and center of mass positions of 22 healthy subjects. We divided the subjects into two groups and assigned them either squat or gait tasks. Then, recorded data were merged and fed to the model to increase its generalizability. We evaluated five different input combinations to assess the effect of each input on the accuracy and generalizability of the model. The accuracy and generalizability of the models were evaluated by root-mean-square errors and comparing the differences in errors for different datasets, respectively. Root-mean-square errors ranged from 4.11 mm to 18.39 mm on both training and testing datasets for different models. Besides, adding anthropometric measurements and a Boolean parameter specifying the type of motion contributed significantly to the generalizability of the model. Also, adding unnecessary joint angles had adverse effects on the network’s estimations. This study showed that by using deep neural networks, the center of mass estimations could be achieved with high accuracy, and a 17 sensors motion-capture system can be replaced with only five sensors, thus reducing the cost and complexity of the process.

The effect of the degree of dual-task interference on gait, dual-task cost, cognitive ability, balance, and fall efficacy in people with stroke: A cross-sectional study.

This study was conducted to investigate the effects of the degree of dual-task (DT) interference on gait, dual-task cost (DTC), cognitive ability, balance, and fall efficacy in people with stroke.In this cross-sectional study, people with chronic stroke (N = 36) performed a DT gait assessment (gait and cognitive task). During the evaluation, DT interference in motor and cognition was evaluated simultaneously. Thus, the group with severe interference in both tasks (mutual interference) was compared with the group with mild interference in either.The main effects for the degree of motor interference were observed on gait performance, DTC in motor, time up and go, and trail-making test B. In the cognitive interference, the main effects were observed on correct response rate, DTC in cognition, time up and go, and trail-making test B. An interaction effect was observed in the trail-making test B.The degree of motor interference affected gait, balance ability, and executive function (EF), and the degree of cognitive interference influenced the correct response rate in the DT condition, balance ability, and EF. Furthermore, mutual interference led to a significant reduction in EF in people with stroke.

Comparison of Laboratory and Daily-Life Gait Speed Assessment during ON and OFF States in Parkinson's Disease.

Accurate assessment of Parkinson’s disease (PD) ON and OFF states in the usual environment is essential for tailoring optimal treatments. Wearables facilitate measurements of gait in novel and unsupervised environments; however, differences between unsupervised and in-laboratory measures have been reported in PD. We aimed to investigate whether unsupervised gait speed discriminates medication states and which supervised tests most accurately represent home performance. In-lab gait speeds from different gait tasks were compared to home speeds of 27 PD patients at ON and OFF states using inertial sensors. Daily gait speed distribution was expressed in percentiles and walking bout (WB) length. Gait speeds differentiated ON and OFF states in the lab and the home. When comparing lab with home performance, ON assessments in the lab showed moderate-to-high correlations with faster gait speeds in unsupervised environment (r = 0.69; p < 0.001), associated with long WB. OFF gait assessments in the lab showed moderate correlation values with slow gait speeds during OFF state at home (r = 0.56; p = 0.004), associated with short WB. In-lab and daily assessments of gait speed with wearables capture additional integrative aspects of PD, reflecting different aspects of mobility. Unsupervised assessment using wearables adds complementary information to the clinical assessment of motor fluctuations in PD.