Higher Gait Variability Research Articles

INCREASED TEMPORAL GAIT VARIABILITY OVER TIME IS RELATED TO FUTURE DEMENTIA

Abstract Age-related brain changes affect the timing and coordination of gait. High gait variability may stem from impaired brain motor control and has been associated with compromised cognition and cognitive impairment. Whether increased gait variability over time is associated with future MCI or dementia is unknown. In the Baltimore Longitudinal Study of Aging, we used age-, sex-, and race-adjusted linear mixed-effects models to examine whether changes in gait variability were associated with future MCI or dementia in participants aged 65+. Gait characteristics were quantified by 3D motion analysis. Independent of baseline gait speed and compared to cognitively normal participants (n=387), those who developed dementia (n=24) had greater rates of increase in gait cycle time variability, stance time variability, and swing time variability (but not mean performance) before the symptom onset (all p<0.05). Further adjustment for concurrent assessment of visuospatial ability or manual dexterity attenuated these associations. Adjustments for verbal memory, psychomotor speed, attention, or executive function did not attenuate these associations. Rates of changes in these gait variability measures were not statistically different between cognitively normal participants (n=387) and those who developed MCI (n=41). Baseline gait variability measures were not different across groups. These findings suggest that longitudinal trajectories of gait variability, not one-time assessment, provide the additional predictive value of future dementia over and beyond gait speed. Mechanisms may include compromised visuospatial ability or manual dexterity. Future neuroimaging studies are warranted to understand neural substrates connecting increased gait variability and dementia risk.

Gait Parameters can Reflect Cognitive Performance in Older Adults with Cerebral Small Vessel Disease: A Cross-sectional Research.

Cerebral small vessel disease (CSVD) is a common chronic progressive disease. It remains unclear whether high gait variability is a marker of cognitive cortical dysfunction. This study included 285 subjects (aged from 60 to 85 years, 60.3% female) including 37 controls, 179 presented as Fazekas II, and 69 presented as Fazekas III. The severity of white matter hyperintensities was assessed by the Fazekas Rating Scale. Gait parameters were assessed using a vision-based artificial intelligent gait analyzer. Cognitive function was tested by MMSE, MoCA, DST, and VFT. Three gait parameters including gait speed, gait length, and swing time were associated with cognitive performance in patients with CSVD. Gait speed was associated with cognitive performance, including MMSE (β 0.200; 95%CI 1.706-6.018; p <.001), MoCA (β 0.183; 95%CI 2.047-7.046; p <.001), DST (order) (β 0.204; 95%CI 0.563-2.093; p =.001) and VFT (β 0.162; 95%CI 0.753-4.865; p =.008). Gait length was associated with cognitive performance, including MMSE (β 0.193; 95%CI 3.475-12.845; p =.001), MoCA (β 0.213; 95%CI 6.098-16.942; p <.001), DST (order) (β 0.224; 95%CI 1.056-4.839; P <.001) and VFT (β 0.149; 95%CI 1.088- 10.114; p =.015). Swing time was associated with cognitive performance, including MMSE (β - 0.242; 95%CI -2.639 to -0.974; p<.001), MoCA (β -0.211; 95%CI -2.989 to -1.034; p <.001) and DST (reverse order) (β -0.140; 95%CI -0.568 to -0.049; p =.020). This study revealed that the relationship between gait parameters and cognitive performance in patients with CSVD and the deteriorated gait parameters can reflect cognitive impairment and even dementia in older people with CSVD.

Association between nutritional status and gait performance in Alzheimer's disease.

This study aimed to comprehensively explore the nutrition and gait of AD patients at different stages and the relationship between them. A total of 85 AD patients were consecutively enrolled in this cross-sectional study and divided into the mild cognitive impairment (MCI) due to AD (AD-MCI) and the dementia due to AD (AD-D) groups. Demographic information, nutritional status, and gait performance were compared between the two groups, and the correlation between nutritional status and gait performance was subsequently analyzed by Pearson and Spearman correlation analyses. The AD-D group had lower scores on Mini-Nutritional Assessment (MNA) and MNAm scales, lower levels of urea nitrogen, folic acid, and vitamin B12 in blood, and higher homocysteine level than those in the AD-MCI group (all p < 0.05). The AD-D group had slower step speed, shorter step length, and shorter stride length than those in the AD-MCI group (all p < 0.05). AD patients with decreased scores of MNA and MNAm scales, and declined levels of urea nitrogen and vitamin B12 in blood had reduced gait speed and gait cadence, and prolonged step length time and stride length time, whereas homocysteine showed the almost opposite results (all p < 0.05). In the AD-MCI group, the score of scale was negatively correlated with the coefficient of variation (CV) of stride length, and the folic acid level was negatively correlated with the CV of stride length and cadence (all p < 0.05). AD patients at the dementia stage had worse nutritional status and gait performance than those at the MCI stage, which was associated with worse global cognition and activities of daily living. Poorer nutritional status was associated with higher gait variability in patients at the MCI stage and with poorer gait performance in patients at the dementia stage. Early identification and intervention of patients with nutritional risk or malnutrition may improve gait performance, thus reducing the risk of falling and cognitive decline, as well as the mortality.

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has an imbalanced nature. Moreover, we designed a deep learning model that combines a convolution-based feature extractor and deep neural network blocks, the LSTM block, and the transformer encoder block, followed by a position-wise feedforward layer. We found that combining the input sequence with the convolution-learned features of different kernels tends to increase the performance of the fall-detection model. Last, we analyzed that the sensor signals collected by both accelerometer and gyroscope sensors can be leveraged to develop an effective classifier that can accurately detect falls, especially differentiating falls from near-falls. Furthermore, we also used data from sixteen different body parts and compared them to determine the better sensor position for fall-detection methods. We found that the shank is the optimal position for placing our sensors, with an F1 score of 0.97, and this could help other researchers collect high-quality fall datasets.

Evaluation of Compensation Strategies for Gait Impairment in Patients With Parkinson Disease.

Compensation strategies are essential in Parkinson disease (PD) gait rehabilitation. However, besides external cueing, these strategies have rarely been investigated systematically. We aimed to perform the following: (1) establish the patients' perspective on the efficacy and usability of 5 different compensation strategies; (2) quantify the efficacy of these strategies on spatiotemporal gait parameters; and (3) explore associations between the effects of specific strategies and patient characteristics. We recruited persons with PD and self-reported disabling gait impairments for this laboratory-based, within-subject study. Clinimetrics included the following: questionnaires (New Freezing of Gait Questionnaire, Vividness of Movement Imagery Questionnaire, Goldsmiths Musical Sophistication Index), cognitive assessments (Attentional Network Test and Montreal Cognitive Assessment [MoCA], Brixton), and physical examinations (Movement Disorders Society Unified Parkinson's Disease Rating Scale [MDS-UPDRS III], Mini-Balance Evaluation Systems Test, tandem gait, and rapid turns test). Gait assessment consisted of six 3-minute trials of continuous walking around a 6-m walkway. Trials comprised the following: (1) baseline gait; (2) external cueing; (3) internal cueing; (4) action observation; (5) motor imagery; and (6) adopting a new walking pattern. Spatiotemporal gait parameters were acquired using 3-dimensional motion capture analysis. Strategy efficacy was determined by the change in gait variability compared with baseline gait. Associated patient characteristics were explored using regression analyses. A total of 101 participants (50 men; median [range] age: 66 [47-91] years) were included. The effects of the different strategies varied greatly among participants. While participants with higher baseline variability showed larger improvements using compensation strategies, participants without freezing of gait, with lower MDS-UPDRS III scores, higher balance capacity, and better performance in orienting attention also showed greater improvements in gait variability. Higher MoCA scores were associated with greater efficacy of external cueing. Our findings support the use of compensation strategies in gait rehabilitation for PD but highlight the importance of a personalized approach. Even patients with high gait variability are able to improve through the application of compensation strategies, but certain levels of cognitive and functional reserve seem necessary to optimally benefit from them.

Quantitative Three-Dimensional Gait Evaluation in Patients With Glucose Transporter 1 Deficiency Syndrome

BackgroundOf the patients with glucose transporter 1 deficiency syndrome (GLUT1-DS), 90% have a pathologic gait. Ataxic-spastic and ataxic gaits are seen in 35% of patients each. A ketogenic diet and modified Atkins diet (MAD) are effective therapy in GLUT1-DS in terms of both the seizures and movement disorder. A three-dimensional gait analysis (3DGA) system can be used to evaluate gait quantitatively using spatiotemporal data and gait kinematics. We performed 3DGA in three ambulatory patients with GLUT1-DS to evaluate the characteristics of their gait pathology, and we compared the gait variables before and after enhancing the MAD in one patient. MethodsAfter examination by pediatric neurologists and pediatric orthopedic surgeons, 3DGA was performed. We assessed walking speed, step length, step width, gait variability, Gait Deviation Index (GDI), Gait Profile Score (GPS), and Gait Variable Score (GVS). ResultsAll three patients had a low GDI and high GPS, comprehensive indices of gait pathology. The unstable gait pattern featured a wide step width in one patient and high gait variability in two patients. In the sagittal plane, the patients had increased GVSs in the knee and ankle joints due to excessive knee flexion or extension and excessive ankle plantarflexion. In the horizontal plane, the patients had increased GVSs in the pelvis, hips, and foot due to excessive rotation during walking. After enhancing the MAD, GDI, GPS, and GVSs improved. Conclusions3DGA has potential for quantifying the characteristics of gait pathology and its improvement with dietary therapy in patients with GLUT1-DS.

Bi-Anodal Transcranial Direct Current Stimulation Combined With Treadmill Walking Decreases Motor Cortical Activity in Young and Older Adults

Background: Walking in the “real world” involves motor and cognitive processes. In relation to this, declines in both motor function and cognition contribute to age-related gait dysfunction. Transcranial direct current stimulation (tDCS) and treadmill walking (STW) have potential to improve gait, particularly during dual-task walking (DTW); walking whilst performing a cognitive task. Our aims were to analyze effects of combined anodal tDCS + STW intervention on cortical activity and gait during DTW.Methods: Twenty-three young adults (YA) and 21 older adults (OA) were randomly allocated to active or sham tDCS stimulation groups. Participants performed 5-min of mixed treadmill walking (alternating 30 s bouts of STW and DTW) before and after a 20-min intervention of active or sham tDCS + STW. Anodal electrodes were placed over the left prefrontal cortex (PFC) and the vertex (Cz) using 9 cm2 electrodes at 0.6 mA. Cortical activity of the PFC, primary motor cortex (M1), premotor cortex (PMC), and supplementary motor area (SMA) bilaterally were recorded using a functional near-infrared spectroscopy (fNIRS) system. Oxygenated hemoglobin (HbO2) levels were analyzed as indicators of cortical activity. An accelerometer measured gait parameters. We calculated the difference between DTW and STW for HbO2 and gait parameters. We applied linear mixed effects models which included age group (YA vs. OA), stimulation condition (sham vs. active), and time (pre- vs. post-intervention) as fixed effects. Treadmill belt speed was a covariate. Partial correlation tests were also performed.Results: A main effect of age group was observed. OA displayed higher activity bilaterally in the PFC and M1, unilaterally in the right PMC and higher gait variability than YA. M1 activity decreased in both YA and OA following active tDCS + STW. There was no overall effect of tDCS + STW on PFC activity or gait parameters. However, negative correlations were observed between changes in left PFC and stride length variability following active tDCS + STW intervention.Conclusion: Increased activity in multiple cortical areas during DTW in OA may act as a compensatory mechanism. Reduction in M1 activity following active tDCS + STW with no observed gait changes suggests improved neural efficiency.

Assessing a Sensory-Motor-Cognition Triad in Amnestic Mild Cognitive Impairment With Dichotic Listening While Walking: A Dual-Task Paradigm.

A contemporary topic in aging research relates to the significance of cognitive changes proper to mild cognitive impairment (MCI) to higher risk of falls and gait deteriorations. The present study addresses this question in the amnestic type of MCI (aMCI) by examining a triad of interrelated comorbidities occurring in the MCI condition: attentional impairments, hearing loss and gait disturbances. To this end, we applied a dichotic listening (DL) test during over-ground walking. DL assesses spontaneous and lateralized auditory attention in three conditions (i.e., free report or Non-forced (NF), Forced-Right (FR) ear and Forced-Left (FL) ear). Earlier reports suggest that this dual-task paradigm evoke asymmetric gait effects on healthy controls, which are moderated by degree of hearing loss. Therefore, the aim of the present study was to evaluate the effects of DL on bilateral (data from both limbs) and lateralized (each limb separately) gait outcomes in a group of forty-three aMCI participants (mean = 71.19) and fifty-two healthy older controls (mean = 70.90) by using hearing loss as a covariate in all analyses. Results showed the aMCI group presented overall compromised gait parameters, especially higher gait variability in all DL conditions during lateralized attentional control. These findings were observed bilaterally, and no lateralized effects on gait were observed. Only after controlling for hearing acuity, gait asymmetries on step length variability emerged almost exclusively in healthy controls. It was concluded that hearing loss in the aMCI group together with higher attentional impairments preclude aMCI individuals to properly execute DL and therefore, they do not display gait asymmetries. The present data demonstrate that varied demands on attentional control dependent on hearing acuity affects gait negatively in healthy older adults and aMCI individuals in very different ways. The appearance of asymmetric effects seems to be a perturbation related to normal aging, while the lack of asymmetries but exaggerated gait variability characterizes aMCI. The present findings show the intricate interplay of sensory, cognitive, and motor deteriorations in different group of older adults, which stresses the need of addressing co-occurring comorbidities behind gait perturbations in individuals prone to develop a dementia state.

Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study.

IntroductionGait impairment is common in neurodegenerative disorders. Specifically, gait variability—the stride‐to‐stride fluctuations in distance and time—has been associated with neurodegeneration and cognitive impairment. However, quantitative comparisons of gait impairments across the cognitive spectrum of dementias have not been systematically investigated.MethodsOlder adults (N = 500) with subjective cognitive impairment, Parkinson disease (PD), mild cognitive impairment (MCI), PD‐MCI, Alzheimer's disease (AD), PD‐dementia, Lewy body dementia, and frontotemporal dementia, as well cognitive normal controls, who were assessed for their gait and cognitive performance.ResultsFactor analyses grouped 11 quantitative gait parameters and identified four independent gait domains: rhythm, pace, variability, and postural control, for group comparisons and classification analysis. Among these domains, only high gait variability was associated with lower cognitive performance and accurately discriminated AD from other neurodegenerative and cognitive conditions.DiscussionOur findings indicate that high gait variability is a marker of cognitive‐cortical dysfunction, which can help to identify Alzheimer's disease dementia.

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

BackgroundGait 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 questionThis 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. MethodsThis 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. ResultsLogistic 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. SignificanceHigher 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.

Digital assessment of falls risk, frailty, and mobility impairment using wearable sensors

Falls are among the most frequent and costly population health issues, costing $50bn each year in the US. In current clinical practice, falls (and associated fall risk) are often self-reported after the “first fall”, delaying primary prevention of falls and development of targeted fall prevention interventions. Current methods for assessing falls risk can be subjective, inaccurate, have low inter-rater reliability, and do not address factors contributing to falls (poor balance, gait speed, transfers, turning). 8521 participants (72.7 ± 12.0 years, 5392 female) from six countries were assessed using a digital falls risk assessment protocol. Data consisted of wearable sensor data captured during the Timed Up and Go (TUG) test along with self-reported questionnaire data on falls risk factors, applied to previously trained and validated classifier models. We found that 25.8% of patients reported a fall in the previous 12 months, of the 74.6% of participants that had not reported a fall, 21.5% were found to have a high predicted risk of falls. Overall 26.2% of patients were predicted to be at high risk of falls. 29.8% of participants were found to have slow walking speed, while 19.8% had high gait variability and 17.5% had problems with transfers. We report an observational study of results obtained from a novel digital fall risk assessment protocol. This protocol is intended to support the early identification of older adults at risk of falls and inform the creation of appropriate personalized interventions to prevent falls. A population-based approach to management of falls using objective measures of falls risk and mobility impairment, may help reduce unnecessary outpatient and emergency department utilization by improving risk prediction and stratification, driving more patients towards clinical and community-based falls prevention activities.

Cumulative Blood Pressure Exposure During Young Adulthood and Mobility and Cognitive Function in Midlife.

High blood pressure (BP) is a known risk factor for mobility and cognitive impairment in older adults. This study tested the association of cumulative BP exposure from young adulthood to midlife with gait and cognitive function in midlife. Furthermore, we tested whether these associations were modified by cerebral white matter hyperintensity (WMH) burden. We included 191 participants from the CARDIA study (Coronary Artery Risk Development in Young Adults), a community-based cohort of young individuals followed over 30 years. Cumulative BP was calculated as the area under the curve (mm Hg×years) from baseline up to year 30 examination. Gait and cognition were assessed at the year 30 examination. Cerebral WMH was available at year 30 in a subset of participants (n=144) who underwent magnetic resonance imaging. Multiple linear regression models were used to assess the association of cumulative BP exposure with gait and cognition. To test effect modification by WMH burden, participants were stratified at the median of WMH and tested for interaction. Higher cumulative systolic and diastolic BPs were associated with slower walking speed (both P=0.010), smaller step length (P=0.011 and 0.005, respectively), and higher gait variability (P=0.018 and 0.001, respectively). Higher cumulative systolic BP was associated with lower cognitive performance in the executive (P=0.021), memory (P=0.015), and global domains (P=0.010), and higher cumulative diastolic BP was associated with lower cognitive performance in the memory domain (P=0.012). All associations were independent of socio-demographics and vascular risk factors (body mass index, smoking, diabetes mellitus and total cholesterol). The association between cumulative BP and gait was moderated by WMH burden (interaction P<0.05). However, the relation between cumulative BP and cognitive function was not different based on the WMH burden (interaction P>0.05). Exposure to higher BP levels from young to midlife is associated with worse gait and cognitive performance in midlife. Furthermore, WMH moderates the association of cumulative BP exposure with gait, but not with cognitive function in midlife. The mechanisms underpinning the impact of BP exposure on brain structure and function must be investigated in longitudinal studies using a life course approach.

SENSOR-BASED ASSESSMENT OF FALLS RISK OF THE TIMED UP AND GO IN REAL-WORLD SETTINGS

Falls are the leading cause of older adult injury and cost $50bn annually. New digital technologies can quantitatively measure falls risk. Objective is to report on a validated wearable sensor-based Timed Up and Go (QTUG) assessment detailing 11 measures of falls risk, frailty and mobility impairment in older adults in six countries in 38 clinical and community settings. Second objective is to generate individual targeted falls prevention programs. 14,611 QTUG records from 8,521 participants (63% female) (72.7±10.7 years) available for analysis. QTUG time was 13.9±7.4 s; gait velocity was 101.9±32.5 cm/s. 25.8% of patients reported falling in previous 12 months; 26.2% of patients were at high fall risk. 21.5% not reporting a fall, were high fall risk. Participants had slow walking speed (29.8%); high gait variability (19.8%); problems with transfers (17.5%). Easily captured and interpreted sensor data is useful in a population-based approach to quantify falls risk stratification.

FRAILTY ASSESSMENT BASED ON THE QUALITY OF DAILY WALKING

Frailty is an increasingly recognized geriatric syndrome resulting in age-related decline in reserve across multiple physiologic systems. An impaired physical function is a prime indicator of frailty. In this study, we aim to implement a body-worn sensor to characterize the quantity and quality of everyday walking, and establish associations between gait impairment and frailty. Daily physical activity was acquired for 48 hours from 125 older adults (≥65 years; 44 non-frail, 60 pre-frail, and 21 frail based on the Fried gold standard) using a tri-axial accelerometer motion-sensor. Continuous purposeful walks (≥60s) without pauses were identified from time-domain acceleration data. Power spectral density (PSD) analysis was performed to define higher gait variability, which was identified by a shorter and wider PSD peak. Association between frailty and gait parameters was assessed using multivariable nominal logistic models with frailty as the dependent variable, and demographic parameters along with the gait parameters as the independent variables. Stride times, PSD gait variability, and total and maximum continuous purposeful walking duration were significantly different between non-frail and pre-frail/frail groups (p<0.05). Using a step-wise model with the above qualitative and quantitative gait parameters as predictors, the pre-frail/frail group (vs. non-frail) was identified with 71.4% sensitivity and 75.4% specificity. Everyday walking characteristics were found to be accurate determinants of frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the stages of frailty. In-home gait analysis is advantageous over clinical gait analysis as it enables cost- and space-effective continuous monitoring.

Cognitive control processes associated with successful gait performance in dual-task walking in healthy young adults.

Growing evidence suggests that the reliance on cognitive control processes during normal walking increases as the locomotor task gets more complex and challenging. The aims of the present study were to explore the (negative) effects of smartphone gaming on gait performance in healthy young adults, and to identify cognitive resources that might help to maintain high gait performance during dual-task walking. Gait speed and gait variability during walking at a self-selected comfortable speed were assessed in 40 healthy, young adults, and compared between single-task and dual-task walking (i.e., concurrent smartphone gaming) in undisturbed, simple and more challenging walking environments (i.e., stepping over an obstacle while walking). Based on single-task performance, dual-tasking costs were computed and linked to higher-level cognitive control processes, which were assessed for each individual. Cognitive function testing encompassed tests on the mental representation of the gait, working memory capacity, inhibitory control and cognitive flexibility. Our data revealed that gaming on a smartphone while walking strongly affected participants' gait performance (i.e., up to 26.8% lower gait speed and 60.2% higher gait variability), and decrements in gait performance were related to higher cognitive control processes. Cognitive resources that were associated with performance decrements in dual-task walking include response inhibition, cognitive flexibility, working memory, and a well-structured mental representation of the gait. From that, it appears that even in healthy young adults better cognitive resources may help to maintain high gait performance in situations, in which we have to deal with dual- or multi-task demands (e.g., using a smartphone) while walking.

Age-related changes in attention control and their relationship with gait performance in older adults with high risk of falls

BackgroundFalls are the leading cause of injury-related deaths in the elderly worldwide. Both gait impairment and cognitive decline have been shown to constitute major fall risk factors. However, further investigations are required to establish a more precise link between the influence of age on brain systems mediating executive cognitive functions and their relationship with gait disturbances, and thus help define novel markers and better guide remediation strategies to prevent falls. MethodsEvent-related functional magnetic resonance imaging (fMRI) was used to evaluate age-related effects on the recruitment of executive control brain network in selective attention task, as measured with a flanker paradigm. Brain activation patterns were compared between twenty young (21 years ± 2.5) and thirty-four old participants (72 years ± 5.3) with high fall risks. We then determined to what extend age-related differences in activation patterns were associated with alterations in several gait parameters, measured with electronic devices providing a precise quantitative evaluation of gait, as well as with alterations in several aspects of cognitive and physical abilities. ResultsWe found that both young and old participants recruited a distributed fronto-parietal-occipital network during interference by incongruent distractors in the flanker task. However, additional activations were observed in posterior parieto-occipital areas in the older relative to the younger participants. Furthermore, a differential recruitment of both the left dorsal parieto-occipital sulcus and precuneus was significantly correlated with higher gait variability. Besides, decreased activation in the right cerebellum was found in the older with poorer cognitive processing speed scores. ConclusionsOverall results converge to indicate greater sensitivity to attention interference and heightened recruitment of cortical executive control systems in the elderly with fall risks. Critically, this change was associated with selective increases in gait variability indices, linking attentional control with gait performance in elderly with high risks of falls.

The association between sleep and dual-task performance in preterm and full-term children: an exploratory study

ObjectivesThe present study explored associations between sleep and children's dual-task performance using cognitive-motor dual tasks (eg, walking and talking). Previous research with older adults indicated correlations between higher gait variability and unfavorable sleep continuity variables. Based on this research, as a first objective, we investigated similar correlations in a sample of children. Second, we explored correlations between dual-task performance and dimensions of sleep architecture. Third, we tested moderating effects of prematurity on these associations. MethodsIn this study, 7-to 12-year-old children were tested in dual-task situations; of those, 39 were formerly preterm, and 59 were full-term born children. They were asked to walk and simultaneously perform different cognitive tasks. Gait was measured using an electronic walkway system. Sleep was measured using in–home sleep-electroencephalography. ResultsAfter accounting for age and cognition, regression analyses revealed correlations between a higher number of awakenings after sleep onset and lower dual-task performance; concerning sleep architecture, analyses revealed correlations between a higher amount of rapid-eye-movement (REM) sleep and lower gait variability. Furthermore, associations between a higher amount of slow wave sleep (SWS) and children's higher cognitive performance were found. Moderation analyses indicated no effects of prematurity. ConclusionsOur exploratory study suggests that a more disrupted sleep was related to children's poorer dual-task performance. Our findings support claims that REM sleep seems more related to performance in procedural tasks whereas SWS seems more related to performance in declarative tasks, suggesting that different sleep stages may support the processing of different performance types.

Gait Variability Can Predict the Risk of Cognitive Decline in Cognitively Normal Older People

Background: The aim of this study was to investigate the association of gait speed and gait variability, an index of how much gait parameters, such as step time, fluctuate step-to-step, with risk of cognitive decline in cognitively normal elderly individuals. While high gait variability is emerging as an early indicator of dementing illnesses, there is little research on whether high gait variability predicts cognitive decline in cognitively normal elderly who have no evidence of cognitive impairment. Methods: In this 4-year prospective cohort study on 91 community-dwelling cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism, we evaluated gait speed and step time variability using a tri-axial accelerometer placed on the center of body mass, and diagnosed mild cognitive impairment (MCI) according to the International Working Group on MCI. We performed Kaplan-Meier analysis with consecutive log-rank testing for MCI-free survival by cohort-specific tertiles of gait speed; hazard ratios (HR) of incident MCI were estimated using Cox proportional hazards regression analysis adjusted for age, sex, education level, Cumulative Illness Rating Scale score, GDS score, and presence of the apolipoprotein E ε4 allele. Results: Out of the 91 participants in the baseline assessment, 87 completed one or more 2-year follow-up assessments, and the median duration of follow-up was 47.1 months. Kaplan-Meier curves of incident MCI show evident differences in risk by gait variability group (χ² = 9.64, p = 0.002, log-rank test). Mean MCI-free survival in the high variability group was 12% shorter than in the mid-to-low tertile group (47.4 ± 1.74 [SD] vs. 54.04 ± 0.52 months), while it was comparable between gait speed groups (51.59 ± 0.70 vs. 50.64 ± 1.77 months; χ² = 1.16, p = 0.281). In multivariate analysis, subjects with high gait variability showed about 12-fold higher risk of MCI (HR = 11.97, 95% CI = 1.29–111.37) than those with mid-to-low variability. However, those with slow gait speed showed comparable MCI risk to those with mid-to-high speed (HR = 5.04, 95% CI = 0.53–48.18). Conclusions: Gait variability may be a better predictor of cognitive decline than gait speed in cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism.

Effects of walking speed and age on the directional stride regularity and gait variability in treadmill walking

In Inertial measurement unit (IMU) based gait analysis systems, the shoe-type sensor is not commonly used, unlike trunk attached sensors. The purpose of this study was to assess the directional Stride regularity (SR) and Gait variability (GV) of data from shoe-type IMU sensors during leveled treadmill walking. The other aim was to investigate the effects of walking speed and age on directional SR and GV in an attempt to find the directional preference associated with gait stability. The DynaStabTM (IMU based gait analysis system) including Smart Balance® (shoe-type data logger) was used to collect normal gait data from forty-four subjects in their 20s (n = 20), 40s (n = 13), and 60s (n = 11). Four different walking speeds (3, 4, 5 and 6 km/h, respectively) on a treadmill were applied for one-minute of continuous leveled walking. Three linear accelerations and three angular velocities were measured with shoe-type IMU sensors. The SR (autocorrelation) and CV of ensemble data (coefficient of variation) on directional kinematics were calculated and compared with different walking speeds and ages. The results indicated that the lateral kinematics (mediolateral acceleration and yawing and rolling angular velocities) had lower stride regularity and higher gait variability than the anteroposterior and vertical kinematics across all walking speeds and ages. Significant interactions on the SRs and GVs from walking speed and age were found for only mediolateral acceleration and rolling angular velocity. Conclusively, the shoe-type IMU sensor system assessed directional SR and GV during walking conveniently. People should be careful with lateral kinematics since it is very sensitive to walking speed and age from the perspective of gait stability.

Multiple gait parameters derived from iPod accelerometry predict age-related gait changes

IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims (1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and (2) to assess if these variables accurately distinguish young (aged 18–45) from healthy older (aged 46–75) adults. MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables. ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%. DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.