Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking

Do Upper and Lower Camptocormias Affect Gait and Postural Control in Patients with Parkinson's Disease? An Observational Cross-Sectional Study

Gait impairments and camptocormia (CC) are common and debilitating in patients with Parkinson's disease (PD). Two types of CC affect patients with PD, but no studies investigated their relative contribution in worsening gait and postural control. Therefore, we investigated spatiotemporal gait parameters, gait variability, and asymmetry and postural control in PD patients (Hoehn & Yahr ≤4) with upper CC and lower CC and patients without CC. This observational cross-sectional study involving patients with PD and upper CC (n=16) and lower CC (n=14) and without CC (n=16). The primary outcome measure was gait speed assessed by the GAITRite System. The secondary outcome measures were other spatiotemporal parameters, gait variability, and asymmetry. Postural control and balance were assessed with posturography and the Mini-BESTest. Patients with lower CC showed a higher H&Y stage (p=0.003), a worse PDQ8 (p=0.042), and a lower Mini-BESTest score (p=0.006) than patients with PD without CC. Patients with lower CC showed a reduced gait speed (p=0.012), stride length, and velocity than patients with PD without CC. Upper CC patients showed a higher stride length than lower CC ones (p=0.007). In the eyes open and closed condition, patients with lower CC showed a higher (worse) velocity of CoP displacement in mediolateral direction and length of CoP than patients with PD without CC. No significant between-group differences were measured in gait variability and asymmetry. In conclusion, lower CC was associated with more severe gait and postural control impairment than patients with upper CC and without CC. Categorizing CC based on the bending fulcrum is compulsory to identify patients with the worst performance and to implement specific rehabilitation programs.

Adolescents’ Postural Control Learning According to the Frequency of Knowledge of Process

Feedback is one of the most influential factors for motor skills learning. Physical Education teachers commonly use verbal cues to provide knowledge of process (KP) when teaching motor skills, but the ideal presentation frequency for KP in adolescents is unclear. The aim of this study was to compare the effectiveness of the frequency of KP (i.e., 100%, 67%, 0%) on dynamic balance. Thirty adolescents, age 14–15 years, participated in the study. Performance on a stabilometer platform was used to assess dynamic balance. Participants received feedback after each trial (100%), in two out of three trials (67%), or no feedback during 12 30-s trials of practice. Adolescents who received feedback (67% or 100%) required lower mean velocity to maintain similar dynamic balance performance (i.e., root mean square). Moreover, adolescents receiving 100% feedback had a higher α-scaling than those who did not received it. During the post-test and the retention, both 67% and 100% KP frequencies were effective at improving postural control, compared to the no feedback control.

The use of smartphone in measuring stance and gait patterns in patients with orthostatic tremor

Orthostatic tremor (OT) is a rare movement disorder characterized by a fast tremor (13–18 Hz) in the lower extremities during stance. Patients with OT typically complain of instability while standing/walking. However, due to the geographical limitation, the standing instability or gait problems in patients with OT cannot be assessed and monitored frequently. The increasing popularity of using smartphone-based accelerometers could be a solution to eliminate this limitation. This study examined the feasibility of using smartphone-based accelerometers to identify the changes in body movement in different standing and locomotor tasks. Twenty patients with OT and seven healthy controls were consented to participate in this study. Subjects stood with eyes open or eyes closed for 20 seconds. They also performed four different locomotor tasks (normal walking, tandem walk, walking on an elevated surface, and obstacle negotiation). When performed different locomotor tasks, patients with OT had a larger acceleration of body movement than controls in the medial-lateral direction (tandem walk: p = 0.026, walking on an elevated surface: p = 0.002, and stepping over the obstacle: p = 0.028). Patients with OT had smaller acceleration of body movement than controls while standing with eyes open in the vertical direction (p = 0.012), in the anterior-posterior direction (p = 0.013) and in the medial-lateral direction (p = 0.011). This study provides objective evidence of balance instability in patients with OT not only while standing but also during different challenging locomotor tasks by using smartphone-based accelerometers.

The effects of mobile phone use on walking: a dual task study

OBJECTIVES

The aim of this study was to examine the effects of walking at different speeds while using a mobile phone on spatiotemporal stride parameters among young adults. Ten participants (7 male, 3 female; age = 24.7 ± 4.4 years, mean ± 1SD) completed 12 walking trials. Trials consisted of tasks performed at both normal and fast walking speeds-walking only, walking while texting, and walking while talking on a mobile phone. Gait velocity, stride length, cadence, and double support time were computed using data from accelerometers on either shoe.

RESULTS

The effects of distracted walking were not significantly larger when performed at a self-selected fast walking speed compared with a normal walking speed. However, walking while texting produced significant decreases in gait velocity, stride length, and cadence, with a significant increase in double support time at both walking speeds. Moreover texting increased the size of the relative variability of walking, observed through a significant increase in the coefficient of variation of cadence, stride length, and double support time. The observed changes may be suggestive of compromised balance when walking while texting regardless of walking speed. This may place the individual at a greater risk of, slips, trips and falls.

Role of muscle power output as a mediator between gait variability and gait velocity in hospitalized older adults

Acute illness requiring hospitalization is a sentinel event leading to functional decline and frequently, long-term disability in older adults. Although functional decline has become a key outcome during and after hospitalization, there is currently no gold standard for measuring functional impairment. The purpose of this study was to compare gait characteristics and muscle performance endpoints of hospitalized older adults based on the Short Physical Performance Battery (SPPB) score (0-12 points) obtained at admission, and to determine the association underlying the gait impairment. A total of 130 hospitalized older adults (aged ≥75) were included. The primary endpoints were differences in functional capacity between groups, assessed with the 6-m Gait Velocity Test (GVT), verbal and arithmetic GVT, followed by gait pattern data recorded using an inertial sensor unit. Maximal muscle strength (MS) and muscle power (MP) were also measured as muscle performance endpoints. A mediation analysis was performed to understand gait disorders. The walking parameters measured at admission were related to functional status and showed significant differences among phenotype groups (disabled, frail, and prefrail groups), as well as muscle performance endpoints (p < 0.05). Finally, the indirect effect was significant (-0.27; 95%CI, -0.59 to -0.05), confirming the mediation role of MP between gait variability and gait velocity in this model. MP slightly weakens the relationship between gait variability and gait velocity. In addition to MS and MP, gait velocity and gait pattern parameters are distinguishing factors among acutely hospitalized older adults.

High Hip Center Reduces the Dynamic Hip Range of Motion and Increases the Hip Load: A Gait Analysis Study in Hip Arthroplasty Patients With Unilateral Developmental Dysplasia

BACKGROUND

Long-term favorable clinical outcomes of anatomical or high hip center techniques in total hip arthroplasty (THA) are reported in patients with developmental dysplasia of the hip (DDH). However, there is little information about the effect of the hip center location on gait characteristics. The purpose of this study was to compare these surgical techniques with gait analysis, analyze the effect of the hip rotation center location on gait parameters, and discuss the possible problems that may arise.

METHODS

A total of 40 patients who underwent THA due to unilateral coxarthrosis secondary to Crowe type III-IV DDH and completed 5 years of follow-up were included in the study. Group 1 included 20 patients who underwent anatomical hip center reconstruction, while group 2 included 20 patients who underwent high hip center reconstruction. Gait analysis was performed, and the groups were compared according to the gait characteristics.

RESULTS

The mean temporospatial values were similar between the groups. The extension of the operated side was significantly lower in group 2 (-9.11 ± 8.92) than in group 1 (-1.87 ± 11.51) (P = .04). The mean longitudinal hip joint force was found to be significantly higher in group 2 (8.92 N/kg ± 0.54) than in group 1 (8.16 N/kg ± 0.66) (P = .04). The high hip center technique has been shown to increase the load on the hip and restrict the dynamic range of motion.

CONCLUSION

The high hip center technique can decrease the survival of the implant and increase the fall risk as it increases the load on the hip and reduces the dynamic range of motion. The hip center should be reconstructed anatomically when possible in DDH patients who undergo unilateral THA.

Fractal analysis of gait in people with Parkinson's disease: three minutes is not enough

BACKGROUND

The fractal dynamics of gait variability in people with Parkinson's disease has been studied by applying the detrended fluctuation analysis (DFA) to short time series (<200 strides). However, DFA is sensitive to time series length, and it is unclear if DFA results from short time series are reliable and if they reflect the fractal dynamics of longer time series.

RESEARCH QUESTION

Is DFA reliable when applied to short time series?

METHODS

We applied DFA to stride time series from five 3-min trials and one 15-min trial in 12 people with Parkinson's disease, 14 healthy older adults and 14 healthy young adults walking overground. Within each group, intraclass correlations (ICC 3,1) were performed to assess the reliability of i) the five 3-min trials together, ii) each 3-min trials to the 15-min trial, and iii) the first 150 strides from the 15-min trial to the full 15-min trial.

RESULTS

Our three main findings are that 1) stride time α-DFA values are not consistent from trial-to-trial for short stride time series, 2) stride time α-DFA values from each 3-min trials are not consistent when compared to stride time α-DFA values from a 15-min trial, and 3) stride time α-DFA values from the first 150 strides of the 15-min trial are not consistent when compared to α-DFA values from the full 15-min trial.

SIGNIFICANCE

Our results confirm that α-DFA values from 3-min walking trials are not reliable, and that they do not reflect the scale invariant properties of longer time series. This suggests that previous studies assessing the fractal dynamics of gait variability from about 3-min walking must be interpreted with caution. A major clinical implication is that DFA cannot be used to study gait in people unable to perform 500 strides continuously.

Years of running experience influences stride-to-stride fluctuations and adaptive response during step frequency perturbations in healthy distance runners

RESEARCH QUESTION

The current study investigated stride-to-stride fluctuations of step rate and contact time in response to enforced step frequency perturbations as well as adaptation and de-adaptation behavior.

METHODS

Forty distance runners ran at a self-selected speed and were asked to match five different enforced step frequencies (150, 160, 170, 180, and 190 beats per min). The influence of experience was explored, because running is a skill that presumably gets better with practice, and increased years of running experience is protective against injury. Detrended fluctuation analysis was used to determine the strength of long-range correlations in gait fluctuations at baseline, during the perturbation, and post-perturbation. Adaptive response was measured by the ability to match, rate of matching, and aftereffect of step frequency perturbations.

RESULTS

The structure of stride-to-stride fluctuations for step rate and contact time did not change during the perturbation or post-perturbation compared to baseline. However, fluctuations in step rate were affected by the level of perturbation. Runners with the most experience had a less persistent structural gait pattern for both step rate and contact time at baseline. Highly experienced runners also demonstrated the best adaptive response. They better matched the enforced step frequency, reached the enforced step frequency sooner, and returned to preferred step frequency more quickly following removal of the perturbation.

SIGNIFICANCE

These findings indicate baseline locomotor flexibility may be beneficial to achieve task demands and return to a stable state once the task is complete. Increased locomotor flexibility may also be a contributing factor for reduced injury risk in experienced runners.

Fatigue-Mediated Loss of Complexity is Contraction-Type Dependent in Vastus Lateralis Electromyographic Signals

The purpose of this study was to investigate the effect of fatigue status and contraction type on complexity of the surface electromyographic (sEMG) signal. Twelve females (mean age ± SD = 21.1 ± 1.4 years) performed three fatigue-inducing protocols that involved maximal concentric, eccentric, or isometric knee-extensor contractions over three non-consecutive sessions. Pre- and post-fatigue assessments were also completed each session and consisted of three maximal efforts for each type of contraction. Complexity of sEMG signals from the vastus lateralis was assessed using Sample Entropy (SampEn) and Detrended Fluctuation Analysis (DFA) as expressed using the scaling exponent α. The results showed that fatigue decreased (p < 0.05) sEMG complexity as indicated by decreased SampEn (non-fatigued: 1.57 ± 0.22 > fatigued: 1.46 ± 0.25) and increased DFA α (non-fatigued: 1.27 ± 0.26 < fatigued: 1.32 ± 0.23). In addition, sEMG complexity was different among contraction types as indicated by SampEn (concentric: 1.58 ± 0.22 > eccentric: 1.47 ± 0.27 and isometric: 1.50 ± 0.21) and DFA α (concentric: 1.27 ± 0.18 < isometric: 1.32 ± 0.18). Thus, these findings suggested sEMG complexity is affected by fatigue status and contraction type, with the degree of fatigue-mediated loss of complexity dependent on the type of contraction used to elicit fatigue.

Synchronization dynamics modulates stride-to-stride fluctuations when walking to an invariant but not to a fractal-like stimulus

Walking with different types of cueing/stimulus (i.e. auditory, visual) has been shown to alter gait variability, thus emerging as an innovative therapeutical tool to restore abnormal gait variability in clinical populations. However, the majority of the research in this area has focused on auditory stimuli while visual stimuli are an understudied alternative that needs more attention, particularly due to the natural dependence on vision during walking. Furthermore, the time differences between the occurrences of the walking steps and the sensory cues, also known as asynchronies, have also received minimal attention, even though the ability to synchronize with different stimuli is of great importance. This study investigated how synchronizing to visual stimuli with different temporal structures could affect gait variability and the respective asynchronies. Participants performed four 15-min walking trials around an indoor track while wearing insole footswitches for the following conditions: a) self-paced walking, and b) walking with glasses that instructed the subjects to step in sync with a virtual moving bar. The stepping occurences of the moving bar were presented in three different ways b1) non-variable, b2) variable and b3) random. Stride times and asynchronies were determined, and the mean values along with the fractal scaling (an indicator of the complexity) in their time series, were calculated. The fractal scaling of the stride times was unaltered when participants walked with the variable stimulus as compared to the self-paced walking condition; while fractal scaling was significantly decreased during the non-variable and random conditions, indicating a loss of complexity for these two conditions. No differences were observed in the means or the fractal scaling of the asynchronies. The correlation analysis between stride times and asynchronies revealed a strong relationship for the non-variable condition but a weak relationship for both variable and random conditions. Taken together, the present study results supports the idea of an existing internal timekeeper that exhibits complexity. We have shown that this complex pattern is similar regardless of the stimulus condition, suggesting that the system's complexity is likely to be expressed at the task performance level - asyncrhonies - when walking to a stimulus. Thus, future research in sensoriomotor gait synchronization should focus and further explore the role of the asynchronies, as it may be of clinical significance.

Gait Segmentation of Data Collected by Instrumented Shoes Using a Recurrent Neural Network Classifier

The authors present a Recurrent Neural Network classifier model that segments the walking data recorded with instrumented footwear. The signals from 3 piezoresistive sensors, a 3-axis accelerometer, and Euler angles are used to generate temporal gait characteristics of a user. The model was tested using a data set collected from 28 adults containing 4198 steps. The mean errors for heel strikes and toe-offs were -5.9 ± 37.1 and 11.4 ± 47.4 milliseconds. These small errors show that the algorithm can be reliably used to segment the gait recordings and to use this segmentation to estimate temporal parameters of the subjects.

Cardiac and gait rhythms in healthy younger and older adults during treadmill walking tasks

BACKGROUND

Aging and pathology result in changes in the dynamics of several physiological subsystems. Often, these changes are concurrent, altering the dynamics between subsystems. Cardiac and gait rhythms are one example in which patterns change during physical activity.

AIMS

The purpose of this research is to simultaneously monitor changes in cardiac and gait rhythms when participants complete various treadmill walking tasks-normal speed, fast speed, and while synchronizing steps with a blinking metronome.

METHODS

The cardiac and gait rhythms of younger and older healthy adults were examined in this study during treadmill walking tasks. Pre-test and post-test walking at a preferred walking speed were compared to fast walking and walking with a gait synchronization test. Cardiac and gait rhythms were observed to calculate the mean, standard deviation, coefficient of variation, detrended fluctuation analysis scaling exponent alpha (DFA α), and sample entropy from each 15-min trial. Separate MANOVAs were used to examine the two experimental conditions for cardiac and gait rhythm variability.

RESULTS

During the gait synchronization experiment, main effects for phase were exhibited for all gait variables, but none were shown during the fast walking task. Meanwhile, the cardiac rhythms demonstrated decreased mean and increased DFA α only during the synchronization condition.

DISCUSSION

Participants, regardless of age, exhibited similar patterns of change in their cardiac and locomotor rhythms during the treadmill walking tasks. Cardiac rhythms were only altered during the gait synchronization task, suggesting it may be possible to simultaneously influence the variability and structure of cardiac and gait rhythms.

Quantification of trunk segmental coordination and head stability in laterally unstable sitting identifies aging and cerebellar ataxia

BACKGROUND

We quantified trunk segmental coordination and head stability in unstable sitting and investigated whether it can discriminate postural control, age-related differences and presence of coordination disorder.

METHODS

Subjects were a healthy younger group (n = 7), a healthy elderly group (n = 7), and a cerebellar ataxia group (n = 8). The motion sensors and surface electrodes were located on the trunk and/or head segments to measure angle displacements, acceleration and electromyograms in unstable sitting during a lateral tilt task. Trunk lateral angle cross-correlation and electromyogram cross-correlation for the trunk segmental coordination, head root mean square (RMS) for the head stability, clinical performance scales, and gait parameters (velocity, coefficient of variation, and RMS ratio) were analyzed.

FINDINGS

Trunk lateral angle cross-correlation showed a significantly negative correlation in the healthy younger group compared with the two other groups (p < 0.01). Head RMS showed a significantly larger value in the cerebellar ataxia group compared with the two other groups (p < 0.01). Trunk lateral angle cross-correlation had moderate correlation with the clinical performance scale of ataxia and gait parameters; however, it was not correlated with head RMS. Classification using trunk lateral angle cross-correlation and head RMS was validated by discriminant analysis and hierarchical cluster analysis.

INTERPRETATION

We found that trunk lateral angle cross-correlation reflected age-related differences and head RMS characterized the pathology of cerebellar ataxia. Trunk segmental coordination and head stability, as two aspects of sitting postural control, can be used to discriminate the degree of aging and cerebellar ataxia.

The effect of unstable shoe designs on the variability of gait measures

BACKGROUND

Unstable footwear designs are popular as training devices to strengthen human neuromuscular control, and many studies have evaluated their effect on gait parameters in comparison to conventional footwear designs. However, there is minimal research on variability of gait measures during walking with unstable shoes. Therefore, the study objective was to compare variability of gait measures between stable and unstable shoe configurations, in conjunction with kinematic and kinetic changes.

METHODS

Fifteen healthy male subjects walked in both a stable and unstable footwear device configuration while full-body gait kinematic and kinetic data was collected. Averages and standard deviations of gait trials were compared between the two configurations at different stages of each step.

RESULTS

Comparison of gait variability between both footwear configurations revealed that variability of frontal-plane foot center of pressure offset, transverse-plane ankle moment, and frontal-plane shoulder angle decreased significantly while walking in the unstable configuration, while transverse-plane spine angle variability increased. No changes in variability of gait measures at the knee, hip, or pelvis were observed. Kinematic and kinetic changes were observed throughout the whole body with the unstable shoe.

CONCLUSION

Our findings suggest that the unstable device used in the study may reduce gait variability at the two extremes of the kinematic chain (i.e., foot, ankle, and shoulders), but increase variability of spine rotation angle. This may suggest a compensatory mechanism to maintain both stability and adaptability, and may have potential clinical implications for gait retraining and enhancing dynamic gait stability and joint stability, pending further investigation.

Stride-time variability is related to sensorimotor cortical activation during forward and backward walking

Previous research has used functional near-infrared spectroscopy (fNIRS) to show that motor areas of the cortex are activated more while walking backward compared to walking forward. It is also known that head movement creates motion artifacts in fNIRS data. The aim of this study was to investigate cortical activation during forward and backward walking, while also measuring head movement. We hypothesized that greater activation in motor areas while walking backward would be concurrent with increased head movement. Participants performed forward and backward walking on a treadmill. Participants wore motion capture markers on their head to quantify head movement and pressure sensors on their feet to calculate stride-time. fNIRS was placed over motor areas of the cortex to measure cortical activation. Measurements were compared for forward and backward walking conditions. No significant differences in body movement or head movement were observed between forward and backward walking conditions, suggesting that conditional differences in movement did not influence fNIRS results. Stride-time was significantly shorter during backward walking than during forward walking, but not more variable. There were no differences in activation for motor areas of the cortex when outliers were removed. However, there was a positive correlation between stride-time variability and activation in the primary motor cortex. This positive correlation between motor cortex activation and stride-time variability suggests that forward walking variability may be represented in the primary motor cortex.

The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations

Background: Differentiating idiopathic Parkinson's disease (IPD) from atypical Parkinsonian disorders (APD) is challenging, especially in early disease stages. Postural instability and gait difficulty (PIGD) are substantial motor impairments of IPD and APD. Clinical evidence implies that patients with APD have larger PIGD impairment than IPD patients. Sensor-based gait analysis as instrumented bedside test revealed more gait deficits in APD compared to IPD. However, the diagnostic value of instrumented bedside tests compared to clinical assessments in differentiating APD from IPD patients have not been evaluated so far.

Objective: The objectives were (a) to evaluate whether sensor-based gait parameters provide additional information to validated clinical scores in differentiating APD from matched IPD patients, and (b) to investigate if objective, instrumented gait assessments have comparable discriminative power to clinical scores.

Methods: In a previous study we have recorded instrumented gait parameters in patients with APD (Multiple System Atrophy and Progressive Supranuclear Palsy). Here, we compared gait parameters to those of retrospectively pairwise disease duration-, age-, and gender-matched IPD patients in order to address this new research questions. To this aim, the PIGD score was calculated as sum of the MDS-UPDRS-3-items “gait,” “postural stability,” “arising from chair,” and “posture.” Gait characteristics were evaluated in standardized gait tests using an instrumented, sensor-based gait analysis system. Machine learning algorithms were used to extract spatio-temporal gait parameters. Receiver Operating Characteristic analysis was performed in order to detect the discriminative power of the instrumented vs. the clinical bedside tests in differentiating IPD from APD.

Results: Sensor-based stride length, gait velocity, toe off angle, and parameters representing gait variability significantly differed between IPD and APD groups. ROC analysis revealed a high Area Under the Curve (AUC) for PIGD score (0.919), and UPDRS-3 (0.848). Particularly, the objective parameters stance time variability (0.841), swing time variability (0.834), stride time variability (0.821), and stride length variability (0.804) reached high AUC's as well.

Conclusions: PIGD symptoms showed high discriminative power in differentiating IPD from APD supporting gait disorders as substantial diagnostic target. Sensor-based gait variability parameters provide metric, objective added value, and serve as complementary outcomes supporting clinical diagnostics and long-term home-monitoring concepts.

Data-Driven Based Approach to Aid Parkinson's Disease Diagnosis

This article presents a machine learning methodology for diagnosing Parkinson's disease (PD) based on the use of vertical Ground Reaction Forces (vGRFs) data collected from the gait cycle. A classification engine assigns subjects to healthy or Parkinsonian classes. The diagnosis process involves four steps: data pre-processing, feature extraction and selection, data classification and performance evaluation. The selected features are used as inputs of each classifier. Feature selection is achieved through a wrapper approach established using the random forest algorithm. The proposed methodology uses both supervised classification methods including K-nearest neighbour (K-NN), decision tree (DT), random forest (RF), Naïve Bayes (NB), support vector machine (SVM) and unsupervised classification methods such as K-means and the Gaussian mixture model (GMM). To evaluate the effectiveness of the proposed methodology, an online dataset collected within three different studies is used. This data set includes vGRF measurements collected from eight force sensors placed under each foot of the subjects. Ninety-three patients suffering from Parkinson's disease and 72 healthy subjects participated in the experiments. The obtained performances are compared with respect to various metrics including accuracy, precision, recall and F-measure. The classification performance evaluation is performed using the leave-one-out cross validation. The results demonstrate the ability of the proposed methodology to accurately differentiate between PD subjects and healthy subjects. For the purpose of validation, the proposed methodology is also evaluated with an additional dataset including subjects with neurodegenerative diseases (Amyotrophic Lateral Sclerosis (ALS) and Huntington's disease (HD)). The obtained results show the effectiveness of the proposed methodology to discriminate PD subjects from subjects with other neurodegenerative diseases with a relatively high accuracy.

Strength or Motor Control: What Matters in High-Functioning Stroke?

Background: The two primary motor impairments that hinder function after stroke are declines in strength and motor control. The impact of motor impairments on functional capacity may vary with the severity of stroke motor impairments. In this study, we focus on high-functioning stroke individuals who experience mild to moderate motor impairments and often resume prior activities or return to work. These tasks require the ability to move independently, placing high demands on their functional mobility. Therefore, the purpose of this study was to quantify impairments in strength and motor control and their contribution to functional mobility in high-functioning stroke.

Methods:Twenty-one high-functioning stroke individuals (Fugl Meyer Lower Extremity Score = 28.67 ± 4.85; Functional Activity Index = 28.47 ± 7.04) and 21 age-matched healthy controls participated in this study. To examine motor impairments in strength and motor control, participants performed the following tasks with the paretic ankle (1) maximum voluntary contractions (MVC) and (2) visuomotor tracking of a sinusoidal trajectory. Strength was quantified as the maximum force produced during ankle plantarflexion and dorsiflexion. Motor control was quantified as (a) the accuracy and (b) variability of ankle movement during the visuomotor tracking task. For functional mobility, participants performed (1) overground walking for 7 meters and (2) simulated driving task. Functional mobility was determined by walking speed, stride length variability, and braking reaction time.

Results: Compared with the controls, the stroke group showed decreased plantarflexion strength, decreased accuracy, and increased variability of ankle movement. In addition, the stroke group demonstrated decreased walking speed, increased stride length variability, and increased braking reaction time. The multiple-linear regression model revealed that motor accuracy was a significant predictor of the walking speed and braking reaction time. Further, motor variability was a significant predictor of stride length variability. Finally, the dorsiflexion or plantarflexion strength did not predict walking speed, stride length variability or braking reaction time.

Conclusions: The impairments in motor control but not strength predict functional deficits in walking and driving in high-functioning stroke individuals. Therefore, rehabilitation interventions assessing and improving motor control will potentially enhance functional outcomes in high-functioning stroke survivors.

Learning to shape virtual patient locomotor patterns: internal representations adapt to exploit interactive dynamics

This work aimed to understand the sensorimotor processes used by humans when learning how to manipulate a virtual model of locomotor dynamics. Prior research shows that when interacting with novel dynamics humans develop internal models that map neural commands to limb motion and vice versa. Whether this can be extrapolated to locomotor rehabilitation, a continuous and rhythmic activity that involves dynamically complex interactions, is unknown. In this case, humans could default to model-free strategies. These competing hypotheses were tested with a novel interactive locomotor simulator that reproduced the dynamics of hemiparetic gait. A group of 16 healthy subjects practiced using a small robotic manipulandum to alter the gait of a virtual patient (VP) that had an asymmetric locomotor pattern modeled after stroke survivors. The point of interaction was the ankle of the VP's affected leg, and the goal was to make the VP's gait symmetric. Internal model formation was probed with unexpected force channels and null force fields. Generalization was assessed by changing the target locomotor pattern and comparing outcomes with a second group of 10 naive subjects who did not practice the initial symmetric target pattern. Results supported the internal model hypothesis with aftereffects and generalization of manipulation skill. Internal models demonstrated refinements that capitalized on the natural pendular dynamics of human locomotion. This work shows that despite the complex interactive dynamics involved in shaping locomotor patterns, humans nevertheless develop and use internal models that are refined with experience. NEW & NOTEWORTHY This study aimed to understand how humans manipulate the physics of locomotion, a common task for physical therapists during locomotor rehabilitation. To achieve this aim, a novel locomotor simulator was developed that allowed participants to feel like they were manipulating the leg of a miniature virtual stroke survivor walking on a treadmill. As participants practiced improving the simulated patient's gait, they developed generalizable internal models that capitalized on the natural pendular dynamics of locomotion.

Persistence in postural dynamics is dependent on constraints of vision, postural orientation, and the temporal structure of support surface translations

Activities of daily living require maintaining upright posture within a variety of environmental constraints. A healthy postural control system can adapt to different environmental constraints. Afferent sensory information is used to determine where the body is in relation to the gravitational vertical and efferent motor commands make corrections with the goal of keeping the center of mass within the base of support. The purpose of this research was to understand how vision, direction of translation, and the temporal correlation of the support surface stimuli affected the persistence characteristics of postural dynamics on short and long time scales. Ten healthy young adults performed a standing task with either eyes open or closed, oriented anteriorly or mediolaterally while the support surface underwent structured translations based on different levels of temporal correlation-white noise (no correlation), pink noise (moderate correlation), and red noise and sinusoidal movements (strong correlations). Center of pressure velocity was analyzed using fractal analysis to determine the dynamics of postural control. On the short time scale, persistence was shown to be stronger with eyes closed, in the mediolateral direction, and when the structure of translation contained stronger temporal correlation. On the long time scale, anti-persistence was stronger with eyes closed, in the mediolateral direction, and for all structures of movement except red noise. This study provides deeper insight into the flexibility existing in human movement responses to structured environmental stimuli through the fractal analysis of movement variability.

Walking speed and spatiotemporal step mean measures are reliable during feedback-controlled treadmill walking; however, spatiotemporal step variability is not reliable

The purpose of the study was to compare the effects of a feedback-controlled treadmill (FeedbackTM) to a traditional fixed-speed treadmill (FixedTM) on spatiotemporal gait means, variability, and dynamics. The study also examined inter-session reliability when using the FeedbackTM. Ten young adults walked on the FeedbackTM for a 5-minute familiarization followed by a 16-minute experimental trial. They returned within one week and completed a 5-minute familiarization followed by a 16-minute experimental trial each for FeedbackTM and FixedTM conditions. Mean walking speed and step time, length, width, and speed means and coefficient of variation were calculated from all experimental conditions. Step time, length, width, and speed gait dynamics were analyzed using detrended fluctuation analysis. Mean differences between experimental trials were determined using ANOVAs and reliability between FeedbackTM sessions was determined by intraclass correlation coefficient. No difference was found in mean walking speed nor spatiotemporal variables, with the exception of step width, between the experimental trials. All mean spatiotemporal variables demonstrated good to excellent reliability between sessions, while coefficient of variation was not reliable. Gait dynamics of step time, length, width, and speed were significantly more persistent during the FeedbackTM condition compared to FixedTM, especially step speed. However, gait dynamics demonstrated fair to poor reliability between FeedbackTM sessions. When walking on the FeedbackTM, users maintain a consistent set point, yet the gait dynamics around the mean are different when compared to walking on a FixedTM. In addition, spatiotemporal gait dynamics and variability may not be consistent across separate days when using the FeedbackTM.

Quantifying Dynamic Balance in Young, Elderly and Parkinson's Individuals: A Systematic Review

Introduction: Falling is one of the primary concerns for people with Parkinson's Disease and occurs predominately during dynamic movements, such as walking. Several methods have been proposed to quantify dynamic balance and to assess fall risk. However, no consensus has been reached concerning which method is most appropriate for examining walking balance during unperturbed and perturbed conditions, particularly in Parkinson's Disease individuals. Therefore, this systematic review aimed to assess the current literature on quantifying dynamic balance in healthy young, elderly and Parkinson's individuals during unperturbed and perturbed walking. Methods: The PubMed database was searched by title and abstract for publications quantifying dynamic balance during unperturbed and mechanically perturbed walking conditions in elderly adults and PD. Inclusion criteria required publications to be published in English, be available in full-text, and implement a dynamic balance quantification method. Exclusion criteria included clinical dynamic balance measures, non-mechanical perturbations, pathologies other than PD, and dual-tasking conditions. The initial database search yielded 280 articles, however, only 81 articles were included after title, abstract and full-text screening. Methodological quality and data were extracted from publications included in the final synthesis. Results: The dynamic balance articles included 26 Coefficient of Variation of Spatiotemporal Variability, 10 Detrended Fluctuation Analysis, 20 Lyapunov Exponent, 7 Maximum Floquet Multipliers, 17 Extrapolated Center of Mass, 11 Harmonic Ratios, 4 Center of Mass-Center of Pressure Separation, 2 Gait Stability Ratio, 1 Entropy, 3 Spatiotemporal Variables, 2 Center of Gravity and Center of Pressure, and 2 Root Mean Square in the final synthesis. Assessment of methodological quality determined that 58 articles had a low methodological rating, a 22 moderate rating, and 1 having a high rating. Conclusion: Careful consideration must be given when selecting a method to quantify dynamic balance because each method defines balance differently, reflects a unique aspect of neuromuscular stability mechanisms, and is dependent on the walking condition (unperturbed vs. perturbed). Therefore, each method provides distinct information into stability impairment in elderly and PD individuals.

Multifractal Analysis of Uterine Electromyography Signals for the Assessment of Progression of Pregnancy in Term Conditions

OBJECTIVES

The objectives of this paper are to examine the source of multifractality in uterine electromyography (EMG) signals and to study the progression of pregnancy in the term (gestation period > 37 weeks) conditions using multifractal detrending moving average (MFDMA) algorithm.

METHODS

The signals for the study, considered from an online database, are obtained from the surface of abdomen during the second (T1) and third trimester (T2). The existence of multifractality is tested using Hurst and scaling exponents. With the intention of identifying the origin of multifractality, the preprocessed signals are converted to shuffle and surrogate data. The original and the transformed signals are subjected to MFDMA to extract multifractal spectrum features, namely strength of multifractality, maximum, minimum, and peak singularity exponents.

RESULTS

The Hurst and scaling exponents extracted from the signals indicate that uterine EMG signals are multifractal in nature. Further analysis shows that the source of multifractality is mainly owing to the presence of long-range correlation, which is computed as 79.98% in T1 and 82.43% in T2 groups. Among the extracted features, the peak singularity exponent and strength of multifractality show statistical significance in identifying the progression of pregnancy. The corresponding coefficients of variation are found to be low, which show that these features have low intersubject variability.

CONCLUSION

It appears that the multifractal analysis can help in investigating the progressive changes in uterine muscle contractions during pregnancy.

The effect of working memory intervention on the gait patterns of the elderly

INTRODUCTION

The purpose of this study was to evaluate the role of working memory (WM) training on walking patterns in elderly people.

METHODS

20 elderly adults were selected and assigned randomly to two groups: WM training group and control group. WM training group received 6 weeks of computerized training on various spatial and verbal WM tasks. The spatial-temporal parameters, the ground reaction force and the timing activity of muscles in pre-posttest and in a follow-up were taken.

RESULT

The results indicated that a significant change in gait speed, double support time and stride time (p < 0.05). Alternations in ground reaction force (GRF) components were found significant. Timing of muscle activity also showed non-significant change after WM intervention.

CONCLUSION

Based on the results of this study, it can be concluded that WM intervention can be applied to improve gait parameters. The improvements in vertical ground reaction force after training may result in an increase upright stability and a decreased in rate falls.

Altering gait variability with an ankle exoskeleton

Exoskeletons can influence human gait. A healthy gait is characterized by a certain amount of variability compared to a non-healthy gait that has more inherent variability; however which exoskeleton assistance parameters are necessary to avoid increasing gait variability or to potentially lower gait variability below that of unassisted walking are unknown. This study investigated the interaction effects of exoskeleton timing and power on gait variability. Ten healthy participants walked on a treadmill with bilateral ankle-foot exoskeletons under ten conditions with different timing (varied from 36% to 54% of the stride) and power (varied from 0.2 to 0.5 W∙kg-1) combinations. We used the largest Lyapunov exponent (LyE) and maximum Floquet multiplier (FM) to evaluate the stride-to-stride fluctuations of the kinematic time series. We found the lowest LyE at the ankle and a significant reduction versus powered-off with exoskeleton power (summed for both legs) of 0.45 W∙kg-1 and actuation timing at 48% of the stride cycle. At the knee, a significant positive effect of power and a negative interaction effect of power and timing were found for LyE. We found significant positive interaction effects of the square of timing and power for LyE at the knee and hip joints. In contrast, the FM at the ankle increased with increasing power and later timing. We found a significant negative effect of power and a positive interaction effect of power and timing for FM at the knee and no significant effects of any of the exoskeleton parameters for FM at the hip. The ability of the exoskeleton to reduce the LyE at the ankle joint offers new possibilities in terms of altering gait variability, which could have applications for using exoskeletons as rehabilitation devices. Further efforts could examine if it is possible to simultaneously reduce the LyE and FM at one or more lower limb joints.

The mental representation of the human gait in hip osteoarthrosis and total hip arthroplasty patients: A clinical cross-sectional study

OBJECTIVE:

To explore differences in gait-specific long-term memory structures and actual gait performance between patients with hip osteoarthrosis, patients seen six months after total hip arthroplasty and healthy controls to gain insights into the role of the gait-specific mental representation for rehabilitation.

DESIGN:

Cross-sectional study.

SUBJECTS:

Twenty hip osteoarthrosis patients, 20 patients seen six months after total hip arthroplasty and 20 healthy controls.

METHODS:

Spatio-temporal (gait speed, step length) and temporophasic (stance time, swing time, single support time, total double support time) gait parameters, and gait variability were measured with an electronic walkway (OptoGait). The gait-specific mental representation was assessed using the structural dimensional analysis of mental representations (SDA-M).

RESULTS:

Hip osteoarthrosis patients showed significantly longer stance and total double support times, shorter swing and single support times, and a decreased gait speed as compared with healthy controls (all P < 0.01). The differences in double support times were still evident in patients seen six months after total hip arthroplasty ( P < 0.01). The gait-specific mental representation differed between hip osteoarthrosis patients and healthy controls with regard to mid-stance and mid-swing phases; the mid-stance phase was still affected six months after total hip arthroplasty (both P < 0.05).

CONCLUSION:

Our data indicated that actual gait performance and gait-specific long-term memory structures differ between hip osteoarthrosis patients and healthy controls. Important, some of these disease-related changes were still evident in patients seen six months after total hip arthroplasty.

Fractal Analysis of BOLD Time Series in a Network Associated With Waiting Impulsivity

Fractal phenomena can be found in numerous scientific areas including neuroscience. Fractals are structures, in which the whole has the same shape as its parts. A specific structure known as pink noise (also called fractal or 1/f noise) is one key fractal manifestation, exhibits both stability and adaptability, and can be addressed via the Hurst exponent (H). FMRI studies using H on regional fMRI time courses used fractality as an important characteristic to unravel neural networks from artificial noise. In this fMRI-study, we examined 103 healthy male students at rest and while performing the 5-choice serial reaction time task. We addressed fractality in a network associated with waiting impulsivity using the adaptive fractal analysis (AFA) approach to determine H. We revealed the fractal nature of the impulsivity network. Furthermore, fractality was influenced by individual impulsivity in terms of decreasing fractality with higher impulsivity in regions of top-down control (left middle frontal gyrus) as well as reward processing (nucleus accumbens and anterior cingulate cortex). We conclude that fractality as determined via H is a promising marker to quantify deviations in network functions at an early stage and, thus, to be able to inform preventive interventions before the manifestation of a disorder.

Stability and predictability in human control of complex objects

Previous research on movement control suggested that humans exploit stability to reduce vulnerability to internal noise and external perturbations. For interactions with complex objects, predictive control based on an internal model of body and environment is needed to preempt perturbations and instabilities due to delays. We hypothesize that stability can serve as means to render the complex dynamics of the body and the task more predictable and thereby simplify control. However, the assessment of stability in complex interactions with nonlinear and underactuated objects is challenging, as for existent stability analyses the system needs to be close to a (known) attractor. After reviewing existing methods for stability analysis of human movement, we argue that contraction theory provides a suitable approach to quantify stability or convergence in complex transient behaviors. To test its usefulness, we examined the task of carrying a cup of coffee, an object with internal degrees of freedom. A simplified model of the task, a cart with a suspended pendulum, was implemented in a virtual environment to study human control strategies. The experimental task was to transport this cart-and-pendulum on a horizontal line from rest to a target position as fast as possible. Each block of trials presented a visible perturbation, which either could be in the direction of motion or opposite to it. To test the hypothesis that humans exploit stability to overcome perturbations, the dynamic model of the free, unforced system was analyzed using contraction theory. A contraction metric was obtained by numerically solving a partial differential equation, and the contraction regions with respect to that metric were computed. Experimental results showed that subjects indeed moved through the contraction regions of the free, unforced system. This strategy attenuated the perturbations, obviated error corrections, and made the dynamics more predictable. The advantages and shortcomings of contraction analysis are discussed in the context of other stability analyses.

Detrended fluctuation analysis in a simple spreadsheet as a tool for teaching fractal physiology

Fractal physiology demonstrated growing interest over the last decades among physiologists, neuroscientists, and clinicians. Many physiological systems coordinate themselves for reducing variability and maintain a steady state. When recorded over time, the output signal exhibits small fluctuations around a stable value. It is becoming increasingly clear that these fluctuations, in most free-running healthy systems, are not simply due to uncorrelated random errors and possess interesting properties, one of which is the property of fractal dynamics. Fractal dynamics model temporal processes in which similar patterns occur across multiple timescales of measurement. Smaller copies of a pattern are nested within larger copies of the pattern, a property termed scale invariance. It is an intriguing process that may deserve attention for implementing curricular development for students to reconsider homeostasis. Teaching fractal dynamics needs to make calculating resources available for students. The present paper offers a calculating resource that uses a basic formula and is executable in a simple spreadsheet. The spreadsheet allows computing detrended fluctuation analysis (DFA), the most frequently used method in the literature to quantify the fractal-scaling index of a physiological time series. DFA has been nicely described by the group at Harvard that designed it; the authors made the C language source available. Going further, it is suggested here that a guide to build DFA step by step in a spreadsheet has many advantages for teaching fractal physiology and beyond: 1) it promotes the DIY (do-it-yourself) in students and highlights scaling concepts; and 2) it makes DFA available for people not familiarized with executing code in C language.

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.

Full Band Spectra Analysis of Gait Acceleration Signals for Peripheral Arterial Disease Patients

Peripheral arterial disease (PAD) is an artherosclerotic occlusive disorder of distal arteries, which can give rise to the intermittent claudication (IC) phenomenon, i.e., limb pain and necessity to stop. PAD patients with IC have altered their gait, increasing the fall risk. Several gait analysis works have studied acceleration signals (from sensors) to characterize the gait. One common technique is spectral analysis. However, this approach mainly uses dominant frequency (f_d ) to characterize gait patterns, and in a narrow spectral band, disregarding the full spectra information. We propose to use a full band spectral analysis (up to 15 Hz) and the fundamental frequency (f₀) in order to completely characterize gait for both control subjects and PAD patients. Acceleration gait signals were recorded using an acquisition equipment consisting of four wireless sensor nodes located at ankle and hip height on both sides. Subjects had to walk, free-fashion, up to 10 min. The analysis of the periodicity of the gait acceleration signals, showed that f₀ is statistically higher (p < 0.05) in control subjects (0.9743 ± 0.0716) than in PAD patients (0.8748 ± 0.0438). Moreover, the spectral envelope showed that, in controls, the power spectral density distribution is higher than in PAD patients, and that the power concentration is hither around the f_d . In conclusion, full spectra analysis allowed to better characterize gait in PAD patients than classical spectral analysis. It allowed to better discriminate PAD patients and control subjects, and it also showed promising results to assess severity of PAD.

A Patient Suffering From Neurodegenerative Disease May Have a Strengthened Fractal Gait Rhythm

Scale invariance in stride series, namely, the series shows similar patterns across multiple time scales, is used widely as a non-invasive identifier of health assessment. Detailed calculations in the literature with standard tools, such as de-trended fluctuation analysis and wavelet transform modulus maxima seem to lead a conclusion that patients suffering from neurodegenerative diseases have weakened fractal gait rhythm compared with healthy persons. These variance-based methods are dynamical mechanism dependent, namely, for some dynamical process the scale invariance cannot be detected qualitatively, while for some others the scale invariance can be detected correctly, but the estimated value of scaling exponent is not correct. Generally, we have limited knowledge on the dynamical mechanism. What is more, the stride series for the patients have a typical finite length of ~300, which may lead to unreasonable statistical fluctuations to the evaluation procedure. Hence, how a neurodegenerative disorder disease affects the scale invariance is still an open problem. In this paper the balanced estimation of diffusion entropy (cBEDE) is used to overcome the limitations. The volunteers include healthy individuals and patients with/without freezing of gait (FOG). It is found that scale invariance exists widely in the gait time series for all the individuals. The average of scaling exponents for patients suffering from FOG is similar with or larger than that for healthy individuals, and similar with that for patients without FOG. The patients not suffering from FOG have an average of scaling exponent significantly larger than that for healthy people. From the results estimated by cBEDE, we can conclude that a patient may have an increased scaling exponent, which is contradictory qualitatively with that in the literatures.

Multifractality, Interactivity, and the Adaptive Capacity of the Human Movement System: A Perspective for Advancing the Conceptual Basis of Neurologic Physical Therapy

BACKGROUND AND PURPOSE

Physical therapists seek to optimize movement as a means of reducing disability and improving health. The short-term effects of interventions designed to optimize movement ultimately are intended to be adapted for use across various future patterns of behavior, in potentially unpredictable ways, with varying frequency, and in the context of multiple tasks and environmental conditions. In this perspective article, we review and discuss the implications of recent evidence that optimal movement variability, which previously had been associated with adaptable motor behavior, contains a specific complex nonlinear feature known as "multifractality."

SUMMARY OF KEY POINTS

Multifractal movement fluctuation patterns reflect robust physiologic interactivity occurring within the movement system across multiple time scales. Such patterns provide conceptual support for the idea that patterns of motor behavior occurring in the moment are inextricably linked in complex, physiologic ways to patterns of motor behavior occurring over much longer periods. The human movement system appears to be particularly tuned to multifractal fluctuation patterns and exhibits the ability to reorganize its output in response to external stimulation embedded with multifractal features.

RECOMMENDATIONS FOR CLINICAL PRACTICE

As a fundamental feature of human movement, multifractality opens new avenues for conceptualizing the link between physiologic interactivity and adaptive capacity. Preliminary evidence supporting the positive influence of multifractal rhythmic auditory stimulation on the gait patterns of individuals with Parkinson disease is used to illustrate how physical therapy interventions might be devised to specifically target the adaptive capacity of the human movement system.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A183).

Movement Symmetry Assessment by Bilateral Motion Data Fusion

OBJECTIVE

A new approach, named bilateral motion data fusion, was proposed for the analysis of movement symmetry, which takes advantage of cross-information between both sides of the body and processes the unilateral motion data at the same time.

METHODS

This was accomplished using canonical correlation analysis and joint independent component analysis. It should be noted that human movements include many categories, which cannot be enumerated one by one. Therefore, the gait rhythm fluctuations of the healthy subjects and patients with neurodegenerative diseases were employed as an example for method illustration. In addition, our model explains the movement data by latent parameters in the time and frequency domains, respectively, which were both based on bilateral motion data fusion.

RESULTS

They show that our method not only reflects the physiological correlates of movement but also obtains the differential signatures of movement asymmetry in diverse neurodegenerative diseases. Furthermore, the latent variables also exhibit the potentials for sharper disease distinctions.

CONCLUSION

We have provided a new perspective on movement analysis, which may prove to be a promising approach.

SIGNIFICANCE

This method exhibits the potentials for effective movement feature extractions, which might contribute to many research fields such as rehabilitation, neuroscience, biomechanics, and kinesiology.

Gait Dynamics in Parkinson's Disease: Short Gait Trials "Stitched" Together Provide Different Fractal Fluctuations Compared to Longer Trials

The fractal analysis of stride-to-stride fluctuations in walking has become an integral part of human gait research. Fractal analysis of stride time intervals can provide insights into locomotor function and dysfunction, but its application requires a large number of strides, which can be difficult to collect from people with movement disorders such as Parkinson's disease. It has recently been suggested that "stitching" together short gait trials to create a longer time series could be a solution. The objective of this study was to determine if scaling exponents from "stitched" stride time series were similar to those from continuous, longer stride time series. Fifteen young adults, fourteen older adults, and thirteen people with Parkinson's disease walked around an indoor track in three blocks: one time 15 min, five times 3 min, and thirty times 30 s. Stride time intervals were determined from gait events recorded with instrumented insoles, and the detrended fluctuation analysis was applied to each stride time series of 512 strides. There was no statistically significant difference between scaling exponents in the three blocks, but intra-class correlation revealed very low between-blocks reliability of scaling exponents. This result challenges the premise that the stitching procedure could provide reliable information about gait dynamics, as it suggests that fractal analysis of stitched time series does not capture the same dynamics as gait recorded continuously. The stitching procedure cannot be considered as a valid alternative to the collection of continuous, long trials. Further studies are recommended to determine if the application of fractal analysis is limited by its own methodological considerations (i.e., long time series), or if other solutions exists to obtain reliable scaling exponents in populations with movement disorders.

Concern about Falling and Complexity of Free-Living Physical Activity Patterns in Well-Functioning Older Adults

BACKGROUND

Fall-related psychological concerns are common among older adults, potentially contributing to functional decline as well as to restriction of activities and social participation. To effectively prevent such negative consequences, it is important to understand how even very low concern about falling could affect physical activity behavior in everyday life. We hypothesized that concern about falling is associated with a reduction in diversity, dynamics, and performance of daily activities, and that these features can be comprehensively quantified in terms of complexity of physical activity patterns.

METHODS

A sample of 40 community-dwelling older adults were assessed for concern about falling using the Falls Efficacy Scale-International (FES-I). Free-living physical activity was assessed using a set of metrics derived from data recorded with a chest-worn tri-axial accelerometer. The devised metrics characterized physical activity behavior in terms of endurance (total locomotion time, longest locomotion period, usual walking cadence), performance (cadence of longest locomotion period, locomotion periods with at least 30 steps and 100 steps/min), and complexity of physical activity patterns. Complexity was quantified according to variations in type, intensity, and duration of activities, and was considered as an adaptive response to environmental exigencies over the course of the day.

RESULTS

Based on FES-I score, participants were classified into two groups: not concerned at all/fully confident (n = 25) and concerned/less confident (n = 15). Demographic and health-related variables did not differ significantly between groups. Comparison of physical activity behavior indicated no significant differences for endurance-related metrics. In contrast, performance and complexity metrics were significantly lower in the less confident group compared to the fully confident group. Among all metrics, complexity of physical activity patterns appeared as the most discriminative feature between fully confident and less confident participants (p = 0.001, non-parametric Cliff's delta effect size = 0.63).

CONCLUSIONS

These results extend our understanding of the interplay between low concern about falling and physical activity behavior of community-dwelling older persons in their everyday life context. This information could serve to better design and evaluate personalized intervention programs in future prospective studies.

Do spatiotemporal parameters and gait variability differ across the lifespan of healthy adults? A systematic review

BACKGROUND

Aging is often associated with changes in the musculoskeletal system, peripheral and central nervous system. These age-related changes often result in mobility problems influencing gait performance. Compensatory strategies are used as a way to adapt to these physiological changes.

RESEARCH QUESTION

The aim of this review is to investigate the differences in spatiotemporal and gait variability measures throughout the healthy adult life.

METHODS

This systematic review was conducted according to the PRISMA guidelines and registered in the PROSPERO database (no. CRD42017057720). Databases MEDLINE (Pubmed), Web of Science (Web of Knowledge), Cochrane Library and ScienceDirect were systematically searched until March 2018.

RESULTS

Eighteen of the 3195 original studies met the eligibility criteria and were included in this review. The majority of studies reported spatiotemporal and gait variability measures in adults above the age of 65, followed by the young adult population, information of middle-aged adults is lacking. Spatiotemporal parameters and gait variability measures were extracted from 2112 healthy adults between 18 and 98 years old and, in general, tend to deteriorate with increasing age. Variability measures were only reported in an elderly population and show great variety between studies.

SIGNIFICANCE

The findings of this review suggest that most spatiotemporal parameters significantly differ across different age groups. Elderly populations show a reduction of preferred walking speed, cadence, step and stride length, all related to a more cautious gait, while gait variability measures remain stable over time. A preliminary framework of normative reference data is provided, enabling insights into the influence of aging on spatiotemporal parameters, however spatiotemporal parameters of middle-aged adults should be investigated more thoroughly.

Stride-to-stride variability and complexity between novice and experienced runners during a prolonged run at anaerobic threshold speed

BACKGROUND

Motor control, related to running performance and running related injuries, is affected by progression of fatigue during a prolonged run. Distance runners are usually recommended to train at or slightly above anaerobic threshold (AT) speed for improving performance. However, running at AT speed may result in accelerated fatigue. It is not clear how one adapts running gait pattern during a prolonged run at AT speed and if there are differences between runners with different training experience.

PURPOSES

To compare characteristics of stride-to-stride variability and complexity during a prolonged run at AT speed between novice runners (NR) and experienced runners (ER).

METHODS

Both NR (n = 17) and ER (n = 17) performed a treadmill run for 31 min at his/her AT speed. Stride interval dynamics was obtained throughout the run with the middle 30 min equally divided into six time intervals (denoted as T1, T2, T3, T4, T5 and T6). Mean, coefficient of variation (CV) and scaling exponent alpha of stride intervals were calculated for each interval of each group.

RESULTS

This study revealed mean stride interval significantly increased with running time in a non-linear trend (p<0.001). The stride interval variability (CV) maintained relatively constant for NR (p = 0.22) and changed nonlinearly for ER (p = 0.023) throughout the run. Alpha was significantly different between groups at T2, T5 and T6, and nonlinearly changed with running time for both groups with slight differences.

SIGNIFICANCE

These findings provided insights into how the motor control system adapts to progression of fatigue and evidences that long-term training enhances motor control. Although both ER and NR could regulate gait complexity to maintain AT speed throughout the prolonged run, ER also regulated stride interval variability to achieve the goal.

Quantification of gait in children with mitochondrial disease

Mitochondrial disorders are multisystem conditions that can potentially affect gait in many ways. The aim of this study was to select the optimal protocol to quantify the spatiotemporal parameters of gait in ambulatory children with mitochondrial disorders based on feasibility, test-retest reliability, and the difference between patients and controls. Gait at self-selected pace was quantified in ambulatory children with a genetically confirmed primary mitochondrial disease using the GAITRite electronic walkway. Three protocols were tested: pre-exercise, post-exercise (after a 3-min walking test), and recovery. In 14 ambulatory patients, we showed good to perfect reliability for velocity, cadence, step length, step time, step time variability, and step width in the recovery condition. The difference between patients and 70 individually age- and gender matched healthy controls only became apparent in the post-exercise protocol. In conclusion, measuring spatiotemporal parameters of gait using the GAITRite in ambulatory children with mitochondrial disease is feasible and reliable for most of the parameters measured. When using gait analysis in future studies in children with mitochondrial disease, we advise i) to use an exercise test prior to the gait analysis, ii) to let children practice the test before the actual data collection, and iii) not to use symmetry parameters.

Entrainment and Synchronization to Auditory Stimuli During Walking in Healthy and Neurological Populations: A Methodological Systematic Review

Background: Interdisciplinary work is needed for scientific progress, and with this review, our interest is in the scientific progress toward understanding the underlying mechanisms of auditory-motor coupling, and how this can be applied to gait rehabilitation. Specifically we look into the process of entrainment and synchronization; where entrainment is the process that governs the dynamic alignments of the auditory and motor domains based on error-prediction correction, whereas synchronization is the stable maintenance of timing during auditory-motor alignment. Methodology: A systematic literature search in databases PubMed and Web of Science were searched up to 9th of August 2017. The selection criteria for the included studies were adult populations, with a minimum of five participants, investigating walking to an auditory stimulus, with an outcome measure of entrainment, and synchronization. The review was registered in PROSPERO as CRD42017080325. Objectives: The objective of the review is to systematically describe the metrics which measure entrainment and synchronization to auditory stimuli during walking in healthy and neurological populations. Results: Sixteen articles were included. Fifty percent of the included articles had healthy controls as participants (N = 167), 19% had neurological diseases such as Huntington's and Stroke (N = 76), and 31% included both healthy and neurological [Parkinson's disease (PD) and Stroke] participants (N = 101). In the included studies, six parameters were found to capture the interaction between the human movement and the auditory stimuli, these were: cadence, relative phase angle, resultant vector length, interval between the beat and the foot contact, period matching performance, and detrended fluctuation analysis. Conclusion: In this systematic review, several metrics have been identified, which measure the timing aspect of auditory-motor coupling and synchronization of auditory stimuli in healthy and neurological populations during walking. The application of these metrics may enhance the current state of the art and practice across the neurological gait rehabilitation. These metrics also have current shortcomings. Of particular pertinence is our recommendation to consider variability in data from a time-series rather than time-windowed viewpoint. We need it in view of the promising practical applications from which the studied populations may highly benefit in view of personalized medical care.

Complexity of Daily Physical Activity Is More Sensitive Than Conventional Metrics to Assess Functional Change in Younger Older Adults

The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60–70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants’ functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (ρ = 0.47, p = 0.03). Smoothing the activity output improved the correlation (ρ = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults.

COMPREHENSIVE CHARACTERIZATION OF GAIT VARIABILITY IN PATIENTS WITH KNEE OSTEOARTHRITIS FOR ALTERED VELOCITIES

This study focuses on quantifying the alterations in human gait variability in individuals with knee Osteoarthritis (OA). To assess the stride-to-stride variation, estimating the dynamical stability discloses the encrypted behavior of the locomotion system, at times facing perturbations, and for that the Largest Lyapunov Exponent is extracted for both Short ([Formula: see text]) and Long ([Formula: see text]) term. Information about the complexity of movement further bolsters the variation-driven conclusions which are calculated for Correlation Index and Kolmogorov–Sinai (K-S) entropy. Using gait analysis, knee angular displacement is the considered data tested for different walking speeds. In the result, [Formula: see text] revealed significant differences between the groups and their walking velocities while [Formula: see text] failed to represent any distinguishable differences. In contrast to the control group, increases in the walking velocity did not affect the amount of locomotion variability for the patients. The stride features also verified the vicissitudes in the gait pattern of knee OA suffering individuals.

Impact of Chronic Obstructive Pulmonary Disease on Cognitive and Motor Performances in Dual-Task Walking

When two tasks are performed simultaneously, they compete for attentional resources, resulting in a performance decrement in one or both tasks. Patients with attention disorders have a reduced ability to perform several tasks simultaneously (e.g., talking while walking), which increases the fall risk and frailty. This study assessed the cognitive and motor performances of patients with COPD and healthy controls within a dual-task walking paradigm. A subobjective was to assess the impact of a pulmonary rehabilitation program on the dual-task performances in COPD. Twenty-five patients with COPD and 20 controls performed a cognitive task (subtraction) and a 15-m walking test separately (single-task; ST) and jointly (dual-task; DT). In addition, a subsample of 10 patients performed the same evaluations 5 weeks later after a pulmonary rehabilitation program following current recommendations. Cognitive and gait performances in ST showed no differences between patients with COPD and controls (all p > 0.05). However, COPD patients exhibited a greater increase in gait variability than controls in DT (4.07 ± 1.46% vs. 2.17 ± 0.7%, p < 0.001). The pulmonary rehabilitation program had no effect on the dual-task impairment for the subsample of patients (p = 0.87). This study provides evidence of insufficient attentional resources to successfully deal with DT in patients with COPD, and this was expressed through an exaggerated increase in gait variability in DT walking. Given the high risk of falls and disability associated with altered gait variability, dual-task training interventions should be considered in pulmonary rehabilitation programs.

Abnormal gait pattern emerges during curved trajectories in high-functioning Parkinsonian patients walking in line at normal speed

Background

Several patients with Parkinson´s disease (PD) can walk normally along straight trajectories, and impairment in their stride length and cadence may not be easily discernible. Do obvious abnormalities occur in these high-functioning patients when more challenging trajectories are travelled, such as circular paths, which normally implicate a graded modulation in the duration of the interlimb gait cycle phases?

Methods

We compared a cohort of well-treated mildly to moderately affected PD patients to a group of age-matched healthy subjects (HS), by deliberately including HS spontaneously walking at the same speed of the patients with PD. All participants performed, in random order: linear and circular walking (clockwise and counter-clockwise) at self-selected speed. By means of pressure-sensitive insoles, we recorded walking speed, cadence, duration of single support, double support, swing phase, and stride time. Stride length-cadence relationships were built for linear and curved walking. Stride-to-stride variability of temporal gait parameters was also estimated.

Results

Walking speed, cadence or stride length were not different between PD and HS during linear walking. Speed, cadence and stride length diminished during curved walking in both groups, stride length more in PD than HS. In PD compared to HS, the stride length-cadence relationship was altered during curved walking. Duration of the double-support phase was also increased during curved walking, as was variability of the single support, swing phase and double support phase.

Conclusion

The spatio-temporal gait pattern and variability are significantly modified in well-treated, high-functioning patients with PD walking along circular trajectories, even when they exhibit no changes in speed in straight-line walking. The increased variability of the gait phases during curved walking is an identifying characteristic of PD. We discuss our findings in term of interplay between control of balance and of locomotor progression: the former is challenged by curved trajectories even in high-functioning patients, while the latter may not be critically affected.