Gait Complexity and Regularity Are Differently Modulated by Treadmill Walking in Parkinson's Disease and Healthy Population

Influence of Aerobic Exercise on Functional Capacity and Maximal Oxygen Uptake in Patients With Parkinson Disease: A Systematic Review and Meta-analysis

OBJECTIVE

To determine the effects of aerobic training in randomized controlled clinical trials on functional capacity, motor symptoms, and oxygen consumption in individuals with Parkinson disease (PD) through a systematic literature review and meta-analysis.

DATA SOURCES

PUBMED, Web of Science, CINAHL, SciELO, and Medline databases were searched to identify published studies until September 2023.

STUDY SELECTION

Randomized controlled clinical trials that evaluated the long-term effect of aerobic exercise in individuals with PD were included.

DATA EXTRACTION

Two independent reviewers extracted the data and assessed the risk of bias and the Grading of Recommendation Assessment, Development, and Evaluation. In case of disagreement, a third reviewer was consulted.

DATA SYNTHESIS

Thirteen studies were included in the systematic review, and the number of participants was 588 with an average age of 66.2 years (57-73y). The study's exercise intervention lasted between 6 and 70 weeks, with most studies lasting 10-12 weeks, with 3 sessions per week and an average duration of 47 minutes per session. The meta-analysis revealed that aerobic exercise is effective in enhancing maximal oxygen uptake (standardized mean difference, SMD 0.42 [95% CI, 0.18, 0.66; P=.0007]) and functional capacity (SMD 0.48 [95% CI, 0.24-0.71; P<.0001]). In addition, aerobic exercise can reduce the motor-unified Parkinson disease rating scale (mean difference-2.48 [95% CI, -3.16 to -1.81; P<.00001]) score in individuals with PD.

CONCLUSIONS

Aerobic exercise training conducted 2-3 times a week, with different intensities (low to high), can be an effective intervention for enhancing functional capacity, maximizing oxygen uptake, and reducing the UPDRS scores in individuals with PD.

Validation of Linear and Nonlinear Gait Variability Measures Derived From a Smartphone System Compared to a Gold-Standard Footswitch System During Overground Walking

Smartphones, with embedded accelerometers, may be a viable method to monitor gait variability in the free-living environment. However, measurements estimated using smartphones must first be compared to known quantities to ensure validity. This study assessed the validity and reliability of smartphone-derived gait measures compared to a gold-standard footswitch system during overground walking. Seventeen adults completed three 8-minute overground walking trials during 3 separate visits. The stride time series was calculated as the time difference between consecutive right heel contact events within the footswitch and smartphone-accelerometry signals. Linear (average stride time, stride time standard deviation, and stride time coefficient of variation) and nonlinear (fractal scaling index, approximate entropy, and sample entropy) measures were calculated for each stride time series. Bland-Altman plots with 95% limits of agreement assessed agreement between systems. Intraclass correlation coefficients assessed reliability across visits. Bland-Altman plots revealed acceptable limits of agreement for all measures. Intraclass correlation coefficients revealed good-to-excellent reliability for both systems, except for fractal scaling index, which was moderate. The smartphone system is a valid method and performs similarly to gold-standard research equipment. These findings suggest the development and implementation of an inexpensive, easy-to-use, and ubiquitous telehealth instrument that may replace traditional laboratory equipment for use in the free-living environment.

Parkinson's Critical Heart Rate Test: Applying the Critical Power Model for People with Parkinson's Disease

Aerobic exercise with the correct intensity can attenuate motor and non-motor symptoms of Parkinson's disease (PD) and improve the quality of life. However, a specific, validated, non-invasive, and outside the laboratory protocol that assesses physiological variables to prescribe optimal aerobic exercise intensity for people with PD is nonexistent. Therefore, this study aimed to propose a protocol, the Parkinson's critical heart rate test (Parkinson-CHR test), to determine the critical heart rate (CHR) in individuals with PD and verify its validity, reliability, and sensitivity. Fifteen people with idiopathic PD, who were able to practice exercises, were recruited to participate in the study (71.1 ± 6.6 years). The study consisted of two experiments: i) the first one aimed to assess the validity and reliability of the protocol, with participants performing the test twice at a one-week interval; ii) the second experiment aimed to investigate the protocol sensitivity, with individuals being evaluated before and after an 8-week training program according to Parkinson-CHR intensity. In experiment 1, no differences between test and retest were observed in the time to cover the distances (400, 800 and 1200 m), the total heart rate, the critical heart rate, and critical speed (p > 0.05). In experiment 2, there was a reduction in time to cover 400 and 800 m as well as in the total heart rate for all distances after the 8-week training program. The Parkinson-CHR test is a reliable, reproducible, inexpensive, and non-invasive protocol to assess, prescribe, and monitor aerobic exercise intensity in people with PD.

The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability

The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to determine the agreement of several measures of stride time variability across five wearable sensors (Opal APDM, Vicon Blue Trident, Axivity, Plantiga, Xsens DOT) and force plates during military load carriage. Nineteen Australian Army trainee soldiers (age: 24.8 ± 5.3 years, height: 1.77 ± 0.09 m, body mass: 79.5 ± 15.2 kg, service: 1.7 ± 1.7 years) completed three 12-min walking trials on an instrumented treadmill at 5.5 km/h, carrying 23 kg of an external load. Simultaneously, 512 stride time intervals were identified from treadmill-embedded force plates and each sensor where linear (standard deviation and coefficient of variation) and non-linear (detrended fluctuation analysis and sample entropy) measures were obtained. Sensor and force plate agreement was evaluated using Pearson's r and intraclass correlation coefficients. All sensors had at least moderate agreement (ICC > 0.5) and a strong positive correlation (r > 0.5). These results suggest wearable devices could be employed to quantify linear and non-linear measures of stride time variability during military load carriage.

Effects of overground gait training assisted by a wearable exoskeleton in patients with Parkinson's disease

BACKGROUND

In the recent past, wearable devices have been used for gait rehabilitation in patients with Parkinson's disease. The objective of this paper is to analyze the outcome of a wearable hip orthosis whose assistance adapts in real time to the patient's gait kinematics via adaptive oscillators. In particular, this study focuses on a metric characterizing natural gait variability, i.e., the level of long-range autocorrelations (LRA) in series of stride durations.

METHODS

Eight patients with Parkinson's disease (Hoehn and Yahr stages 1[Formula: see text]2.5) performed overground gait training three times per week for four consecutive weeks, assisted by a wearable hip orthosis. Gait was assessed based on performance metrics such as the hip range of motion, speed, stride length and duration, and the level of LRA in inter-stride time series assessed using the Adaptive Fractal Analysis. These metrics were measured before, directly after, and 1 month after training.

RESULTS

After training, patients increased their hip range of motion, their gait speed and stride length, and decreased their stride duration. These improvements were maintained 1 month after training. Regarding long-range autocorrelations, the population's behavior was standardized towards a metric closer to the one of healthy individuals after training, but with no retention after 1 month.

CONCLUSION

This study showed that an overground gait training with adaptive robotic assistance has the potential to improve key gait metrics that are typically affected by Parkinson's disease and that lead to higher prevalence of fall.

TRIAL REGISTRATION

ClinicalTrials.gov Identifer NCT04314973. Registered on 11 April 2020.

High-density EMG, IMU, kinetic, and kinematic open-source data for comprehensive locomotion activities

Novel sensor technology enables new insights in the neuromechanics of human locomotion that were previously not possible. Here, we provide a dataset of high-density surface electromyography (HDsEMG) and high-resolution inertial measurement unit (IMU) signals, along with motion capture and force data for the lower limb of 10 healthy adults during multiple locomotion modes. The participants performed level-ground and slope walking, as well as stairs ascent/descent, side stepping gait, and stand-to-walk and sit-to-stand-to-walk, at multiple walking speeds. These data can be used for the development and validation of locomotion mode recognition and control algorithms for prosthetics, exoskeletons, and bipedal robots, and for motor control investigations.

Temporal organization of stride-to-stride variations contradicts predictive models for sensorimotor control of footfalls during walking

Walking exhibits stride-to-stride variations. Given ongoing perturbations, these variations critically support continuous adaptations between the goal-directed organism and its surroundings. Here, we report that stride-to-stride variations during self-paced overground walking show cascade-like intermittency-stride intervals become uneven because stride intervals of different sizes interact and do not simply balance each other. Moreover, even when synchronizing footfalls with visual cues with variable timing of presentation, asynchrony in the timings of the cue and footfall shows cascade-like intermittency. This evidence conflicts with theories about the sensorimotor control of walking, according to which internal predictive models correct asynchrony in the timings of the cue and footfall from one stride to the next on crossing thresholds leading to the risk of falling. Hence, models of the sensorimotor control of walking must account for stride-to-stride variations beyond the constraints of threshold-dependent predictive internal models.

Acclimatization of force production during walking in persons with Parkinson's disease

Individuals with Parkinson's disease walk slowly, with short strides resulting in decreased mobility. Treadmill walking assessments are utilized to understand gait impairment in persons with Parkinson's disease and treadmill-based interventions to mobility have become increasingly popular. While walking on a treadmill, there is a reported initial acclimatization period where individuals adjust to the speed and dynamics of the moving belt before producing consistent walking patterns. It is unknown how much walking time is required for individuals with Parkinson's disease to acclimate to the treadmill. We investigated how spatiotemporal parameters and ground reaction forces changed during treadmill acclimatization. Twenty individuals with idiopathic Parkinson's (15 Males, 5 Females) walked for a five-minute treadmill session on an instrumented treadmill while motion capture data were collected. The measures of interest included ground reaction force measures (peak propulsive force, peak braking force, propulsive impulse, and braking impulse) and spatiotemporal measures (stride length, stride time, or double support time). Analyses demonstrated significantly increased propulsive impulse (p <.001) after the first minute, with no significant difference for the remaining minutes (p ≥ 0.395). There were no significant changes in the spatiotemporal measures (P =.065). These results quantify the stabilization of ground reaction force during the treadmill acclimatization period. Based on our findings, if steady-state gait is desired, we recommend participants walk for at least two minutes before data collection. Future clinical investigations should consider ground reaction force as sensitive parameters for evaluating gait in persons with Parkinson's disease in treadmill-based assessments or interventional therapies.

Insight into the hierarchical control governing leg stiffness during the stance phase of running

Leg stiffness plays a key role in the storage and release of elastic energy during stance. However, the extent to which a runner is able to reuse stored energy remains a limiting factor in determining their running effectiveness. In this study, ten habitual rearfoot strikers and ten habitual forefoot strikers were asked to run on a treadmill in three footwear conditions: traditional, neutral, and minimal running shoes. We examined the effect of habitual foot strike pattern and footwear on leg stiffness control within three task-relevant phases of stance (i.e. touch-down, loading, unloading). Control was quantified using stride-to-stride leg stiffness time-series and the coefficient of variability and detrended fluctuation analysis (DFA). The results are interpreted within a theoretical framework that blends dynamic systems theory and optimal feedback control. Results indicate that leg stiffness control is tightly regulated by an active control process during the loading period of stance. In contrast, the touch-down and unloading phases are driven mostly by passive allometric control mechanisms. The effect of footwear on leg stiffness control was inconclusive due to inconsistent trends across three shoe types. However, stiffness control was affected by landing technique. Habitual rearfoot strike runners have reduced DFA values during the touch-down and unloading phases. These sub-phases are associated with an allometric control process and suggests that rearfoot strike runners express a reduction in system complexity for leg stiffness control and hence, a less adaptable system.

Comparing adaptive fractal and detrended fluctuation analyses of stride time variability: Tests of equivalence

BACKGROUND

Fractal analyses quantify self-similarities in stride-to-stride fluctuations over different time scales. Fractal exponents can be measured with adaptive fractal analysis (AFA) or detrended fluctuation analysis (DFA), though measurements obtained with the algorithms have not been directly compared.

RESEARCH QUESTION

Are stride time fractal exponents measured with AFA and DFA algorithms equivalent?

METHODS

Data from 50 participants with Parkinson's Disease (n = 15), age-similar healthy adults (n = 15) and healthy young adults (n = 20) were analyzed in this cross-sectional, observational study. Participants completed 6-min walks at self-selected speeds overground on a straight walkway and on a treadmill. Stride times were measured with inertial measurement units. Fractal exponents in stride time data were processed using AFA and DFA algorithms and compared with two one-sided tests of equivalence. Mixed ANOVAs were used to compare exponents between groups and conditions.

RESULTS

Fractal exponents computed with AFA and DFA were equivalent neither in the overground (0.796 & 0.830, respectively, p = .587) nor treadmill conditions (0.806 & 0.882, respectively, p = .122). Fractal exponents measured with DFA were higher than when measured with AFA. Standard errors were 22% lower when measured with AFA. Additionally, a group × condition interaction was statistically significant when fractal exponents were processed with the AFA algorithm (F(2,47) = 11.696, p < .001), whereas the group × condition interaction was not statistically significant when DFA exponents were compared (F(2, 47) = 2.144, p = .129).

SIGNIFICANCE

AFA and DFA do not produce equivalent estimates of the fractal exponent α in stride time dynamics. Estimates of the fractal exponent α obtained with AFA or DFA algorithms therefore should not be used interchangeably. Standard errors were lower when derived with AFA. Fractal exponents calculated with AFA may be more sensitive to conditions that influence stride time fractal dynamics than are measures calculated with DFA.

Biomechanical Correlates of Falls Risk in Gait Impaired Stroke Survivors

Increased falls risk is prevalent among stroke survivors with gait impairments. Tripping is the leading cause of falls and it is highly associated with mid-swing Minimum Foot Clearance (MFC), when the foot’s vertical margin from the walking surface is minimal. The current study investigated MFC characteristics of post-stroke individuals (n = 40) and healthy senior controls (n = 21) during preferred speed treadmill walking, using an Optotrak 3D motion capture system to record foot-ground clearance. In addition to MFC, bi-lateral spatio-temporal gait parameters, including step length, step width and double support time, were obtained for the post-stroke group’s Unaffected and Affected limb and the control group’s Dominant and Non-dominant limbs. Statistical analysis of MFC included central tendency (mean, median), step-to-step variability (standard deviation and interquartile range) and distribution (skewness and kurtosis). In addition, the first percentile, that is the lowest 1% of MFC values (MFC 1%) were computed to identify very high-risk foot trajectory control. Spatio-temporal parameters were described using the mean and standard deviation with a 2 × 2 (Group × Limb) Multivariate Analysis of Variance applied to determine significant Group and Limb effects. Pearson’s correlations were used to reveal any interdependence between gait variables and MFC control. The main finding of the current research was that post-stroke group’s affected limb demonstrated lower MFC 1% with higher variability and lower kurtosis. Post-stroke gait was also characterised by shorter step length, larger step width and increased double support time. Gait retraining methods, such as using real-time biofeedback, would, therefore, be recommended for post-stroke individuals, allowing them to acquire optimum swing foot control and reduce their tripping risk by elevating the swing foot and improving step-to-step consistency in gait control.

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

BACKGROUND

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

Nonlinear analysis of the movement variability structure can detect aging-related differences among cognitively healthy individuals

Studying the dynamics of nonlinear systems can provide additional information about the variability structure of the system. Within the current study, we examined the application of regularity and local stability measures to capture motor function alterations due to dual-tasking using a previously validated upper-extremity function (UEF). We targeted young (ages 18 and 30 years) and older adults (65 years or older) with normal cognition based on clinical screening. UEF involved repetitive elbow flexion without counting (ST) and while counting backward by one (DT1) or three (DT3). We measured the regularity (measured by sample entropy (SE)), local stability (measured by the largest Lyapunov exponent (LyE)), as well as conventional peak-dependent variability measures (coefficient of variation of kinematics parameters) to capture motor dynamic alterations due to dual-tasking. Within both groups, only SE showed significant differences between all pairs of UEF condition comparisons, even ST vs DT1 (p = 0.007, effect size = 0.507), for which no peak-dependent parameter showed significant difference. Among all measures, the only parameter that showed a significant difference between young and older adults was LyE (p < 0.001, effect size = 0.453). Current findings highlight the potential of nonlinear analysis to detect aging-related alterations among cognitively healthy participants.

Speeding Up Gait in Parkinson's Disease

BACKGROUND

Gait speed is an important outcome that relates to mobility, function, and mortality, and is altered in people with Parkinson's disease (PwPD). However, changes in gait speed may not reflect changes in other important aspects of gait.

OBJECTIVE

To characterize which outcomes change concomitantly with walking speed in PwPD. This information can inform the choice of outcome variables for characterizing and tracking gait performance in this population.

METHODS

67 PwPD and 40 neurotypical adults completed 2-minute overground walking bouts at comfortable and fast self-selected speeds. Eight inertial sensors were used to characterize gait and turning. We identified a subset of participants (38 per group) where the PD participant's "fast" walk was similar speed to neurotypical participants "comfortable" walk, facilitating an across-group gait comparison controlling for gait speed.

RESULTS

Walking at fast gait speed compared to comfortable lead to significant changes in stride length, cadence, and stride time variability, but not in steps to turn, trunk ROM, and trunk and lumbar stability in PwPD. Sub-group analyses showed that despite walking at a similar speed as neurotypical adults, PwPD exhibit altered turning outcomes, lumbar stability, and stride length/cadence.

CONCLUSIONS

Gait speed is a critical outcome for characterizing mobility. However, in PwPD, several important outcomes do not exhibit a uniform relationship with gait speed, and remain altered compared to neurotypical adults despite "normalizing" walking speed. Given the complex relationship between gait speed and other gait quality measures, care should be taken when choosing outcome measures to characterize the breadth of gait abnormality in PwPD.

Influence of Autocorrelated Rhythmic Auditory Stimulations on Parkinson's Disease Gait Variability: Comparison With Other Auditory Rhythm Variabilities and Perspectives

Parkinson's Disease patients suffer from gait impairments such as reduced gait speed, shortened step length, and deterioration of the temporal organization of stride duration variability (i.e., breakdown in Long-Range Autocorrelations). The aim of this study was to compare the effects on Parkinson's Disease patients' gait of three Rhythmic Auditory Stimulations (RAS), each structured with a different rhythm variability (isochronous, random, and autocorrelated). Nine Parkinson's Disease patients performed four walking conditions of 10-15 min each: Control Condition (CC), Isochronous RAS (IRAS), Random RAS (RRAS), and Autocorrelated RAS (ARAS). Accelerometers were used to assess gait speed, cadence, step length, temporal organization (i.e., Long-Range Autocorrelations computation), and magnitude (i.e., coefficient of variation) of stride duration variability on 512 gait cycles. Long-Range Autocorrelations were assessed using the evenly spaced averaged Detrended Fluctuation Analysis (α-DFA exponent). Spatiotemporal gait parameters and coefficient of variation were not modified by the RAS. Long-Range Autocorrelations were present in all patients during CC and ARAS although all RAS conditions altered them. The α-DFA exponents were significantly lower during IRAS and RRAS than during CC, exhibiting anti-correlations during IRAS in seven patients. α-DFA during ARAS was the closest to the α-DFA during CC and within normative data of healthy subjects. In conclusion, Isochronous RAS modify patients' Long-Range Autocorrelations and the use of Autocorrelated RAS allows to maintain an acceptable level of Long-Range Autocorrelations for Parkinson's Disease patients' gait.

Test-Retest Reliability and the Effects of Walking Speed on Stride Time Variability During Continuous, Overground Walking in Healthy Young Adults

Studies have investigated the reliability and effect of walking speed on stride time variability during walking trials performed on a treadmill. The objective of this study was to investigate the reliability of stride time variability and the effect of walking speed on stride time variability, during continuous, overground walking in healthy young adults. Participants completed: (1) 2 walking trials at their preferred walking speed on 1 day and another trial 2 to 4 days later and (2) 1 trial at their preferred walking speed, 1 trial approximately 20% to 25% faster than their preferred walking speed, and 1 trial approximately 20% to 25% slower than their preferred walking speed on a separate day. Data from a waist-mounted accelerometer were used to determine the consecutive stride times for each trial. The reliability of stride time variability outcomes was generally poor (intraclass correlations: .167-.487). Although some significant differences in stride time variability were found between the preferred walking speed, fast, and slow trials, individual between-trial differences were generally below the estimated minimum difference considered to be a real difference. The development of a protocol to improve the reliability of stride time variability outcomes during continuous, overground walking would be beneficial to improve their application in research and clinical settings.

Benefits of nonlinear analysis indices of walking stride interval in the evaluation of neurodegenerative diseases

Indices characterising the long-range temporal structure of walking stride interval (SI) variability such as Hurst exponent (H) and fractal dimension (D) may be used in addition to indices measuring the amount of variability like the coefficient of variation (CV). We assess the added value of the former indices in a clinical neurological context. Our aim is to demonstrate that they provide a clinical significance in aging and in frequent neurodegenerative diseases such as Parkinson's disease, Huntington, and amyotrophic lateral sclerosis. Indices assessing the temporal structure of variability are mainly dependent on SI time series length and algorithms used, making quantitative comparisons between different studies difficult or even impossible. Here, we recompute these indices from available SI time series, either from our lab or from online databases. More precisely, we recompute CV, H, and D in a unified way. The average SI is also added to the measured parameters. We confirm that variability indices are relevant indicators of aging process and neurodegenerative diseases. While CV is sensitive to aging process and pathology, it does not discriminate between specific neurodegenerative diseases. H, which measures predictability of SI, significantly decreases with age but increases in patients suffering from amyotrophic lateral sclerosis. D, catching complexity of SI, is correlated with total functional capacity in patients with Huntington's disease. We conclude that the computation of H complements the clinical diagnosis of walking in patients with neurodegenerative diseases and we recommend it as a relevant supplement to classical CV or averaged SI. Since H and D indices did not lead to the same observations, suggesting the multi-fractal nature of SI dynamics, we recommend to open clinical gait analysis to the evaluation of more parameters.

Uncontrolled manifold analysis of the effects of a perturbation-based training on the organization of leg joint variance in cerebellar ataxia

Walking patterns of persons affected by cerebellar ataxia (CA) are characterized by wide stride-to-stride variability ascribable to: the background pathology-related sensory-motor noise; the motor redundancy, i.e., an excess of elemental degrees of freedom that overcomes the number of variables underlying a specific task performance. In this study, we first tested the hypothesis that healthy and, especially, CA subjects can effectively exploit solutions in the domain of segmental angles to stabilize the position of either the foot or the pelvis (task performance) across heel strikes, in accordance with the uncontrolled manifold (UCM) theory. Next, we verified whether a specific perturbation-based training allows CA subjects to further take advantage of this coordination mechanism to better cope with their inherent pathology-related variability. Results always rejected the hypothesis of pelvis stabilization whereas supported the idea that the foot position is stabilized across heel strikes by a synergic covariation of elevation and azimuth angles of lower limb segments in CA subjects only. In addition, it was observed that the perturbation-based training involves a decreasing trend in the variance component orthogonal to the UCM in both groups, reflecting an improved accuracy of the foot control. Concluding, CA subjects can effectively structure the wide amount of pathology-related sensory-motor noise to stabilize specific task performance, such as the foot position across heel strikes. Moreover, the promising effects of the proposed perturbation-based training paradigm are expected to improve the coordinative strategy underlying the stabilization of the foot position across strides, thus ameliorating balance control during treadmill locomotion.

Immersive Virtual Reality to Restore Natural Long-Range Autocorrelations in Parkinson's Disease Patients' Gait During Treadmill Walking

Effects of treadmill walking on Parkinson’s disease (PD) patients’ spatiotemporal gait parameters and stride duration variability, in terms of magnitude [coefficient of variation (CV)] and temporal organization [long range autocorrelations (LRA)], are known. Conversely, effects on PD gait of adding an optic flow during treadmill walking using a virtual reality headset, to get closer to an ecological walk, is unknown. This pilot study aimed to compare PD gait during three conditions: Overground Walking (OW), Treadmill Walking (TW), and immersive Virtual Reality on Treadmill Walking (iVRTW). Ten PD patients completed the three conditions at a comfortable speed. iVRTW consisted in walking at the same speed as TW while wearing a virtual reality headset reproducing an optic flow. Gait parameters assessed were: speed, step length, cadence, magnitude (CV) and temporal organization (evenly spaced averaged Detrended Fluctuation Analysis, α exponent) of stride duration variability. Motion sickness was assessed after TW and iVRTW using the Simulator Sickness Questionnaire (SSQ). Step length was greater (p = 0.008) and cadence lower (p = 0.009) during iVRTW compared to TW while CV was similar (p = 0.177). α exponent was similar during OW (0.77 ± 0.07) and iVRTW (0.76 ± 0.09) (p = 0.553). During TW, α exponent (0.85 ± 0.07) was higher than during OW (p = 0.039) and iVRTW (p = 0.016). SSQ was similar between TW and iVRTW (p = 0.809). iVRTW is tolerable, could optimize TW effects on spatiotemporal parameters while not increasing CV in PD. Furthermore, iVRTW could help to capture the natural LRA of PD gait in laboratory settings and could potentially be a challenging second step in PD gait rehabilitation.

Effect of Parkinson's disease and two therapeutic interventions on muscle activity during walking: a systematic review

Gait deficits are a common feature of Parkinson’s disease (PD) and predictors of future motor and cognitive impairment. Understanding how muscle activity contributes to gait impairment and effects of therapeutic interventions on motor behaviour is crucial for identifying potential biomarkers and developing rehabilitation strategies. This article reviews sixteen studies that investigate the electromyographic (EMG) activity of lower limb muscles in people with PD during walking and reports on their quality. The weight of evidence establishing differences in motor activity between people with PD and healthy older adults (HOAs) is considered. Additionally, the effect of dopaminergic medication and deep brain stimulation (DBS) on modifying motor activity is assessed. Results indicated greater proximal and decreased distal activity of lower limb muscles during walking in individuals with PD compared to HOA. Dopaminergic medication was associated with increased distal lower limb muscle activity whereas subthalamic nucleus DBS increased activity of both proximal and distal lower limb muscles. Tibialis anterior was impacted most by the interventions. Quality of the studies was not strong, with a median score of 61%. Most studies investigated only distal muscles, involved small sample sizes, extracted limited EMG features and lacked rigorous signal processing. Few studies related changes in motor activity with functional gait measures. Understanding mechanisms underpinning gait impairment in PD is essential for development of personalised rehabilitative interventions. Recommendations for future studies include greater participant numbers, recording more functionally diverse muscles, applying multi-muscle analyses, and relating EMG to functional gait measures.

Fractal auditory stimulation has greater benefit for people with Parkinson's disease showing more random gait pattern

BACKGROUND

Healthy gait dynamics are characterized by the presence of fractal, persistent stride-to-stride variations, which become more random with Parkinson's disease (PD). Rhythmic auditory stimulation with fractal beat-to-beat variations can change gait dynamics in people with PD toward more persistence.

RESEARCH QUESTION

How does gait in people with PD change when synchronizing steps with fractal melodic metronomes with different step-to-beat ratios, and which stimulus do they prefer?

METHODS

In this cross-sectional study, 15 people with PD and 15 healthy older adults walked over-ground in three conditions: self-paced, paced by a fractal auditory stimulus with a 1:1 step-to-beat ratio ('metronome'), and fractal auditory stimulus with a 1:2 step-to-beat ratio ('music'). Gait dynamics were recorded with instrumented insoles, and detrended fluctuation analysis (DFA) was applied to the series of stride time intervals. Stimuli preference was assessed using Likert-like scales and open-ended questions. ANOVAs were used to compare mean, coefficient of variation, α-DFA, and the responses from the continuous Likert scales. Pearson correlations were used to assess the relationship between 'music' and 'metronome' enjoyment or difficulty with gait outcomes, and to determine the association between baseline α-DFA and changes due to the stimuli.

RESULTS

Our major findings are that (i) stride-to-stride variations were more persistent with the 'metronome' compared to baseline for both groups, (ii) the effect was greater for people with lower α-DFA at baseline (i.e., more random stride-to-stride variations), and (iii) both groups found the 'metronome' less difficult to synchronize with.

SIGNIFICANCE

This study showed that people with PD and healthy older adults walk with higher statistical persistence in their stride-to-stride variations when instructed to synchronize their steps with a fractal stimulus. Participants with lower persistence at baseline benefited the most from the fractal 'metronome', highlighting the importance to develop patient-centered tests and interventions.

Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis

Human physiological signals are inherently rhythmic and have a hallmark feature in that even distant intrasignal measurements are related to each other. This relationship is termed long-range correlation and has been recognized as an indicator of the optimal state of the observed physiological systems, among which the locomotor system. Loss of long-range correlations has been found as a result of aging as well as disease, which can be evaluated with detrended fluctuation analysis (DFA). Recently, DFA and the scaling exponent α have been employed for understanding the degeneration of temporal regulation of human walking biorhythms in, for example, Parkinson disease (PD). However, heterogeneous evidence on scaling exponent α values reported in the literature across different population groups has put into question what constitutes a healthy physiological pattern. Therefore, the purpose of this systematic review was to investigate the functional thresholds of scaling exponent α in young vs. older adults, as well as between patients with PD and age-matched asymptomatic controls. Aging and PD exhibited a negative effect size (i.e., led to decreased long-range correlations) of -0.20 and -0.53, respectively. Our meta-analysis based on 14 studies provides evidence that a mean scaling exponent α threshold of 0.86 [2 standard error (0.76, 0.96)] is able to optimally discriminate temporal organization of stride interval between young and old, whereas 0.82 (0.72, 0.92) differentiates patients with PD and age-matched asymptomatic controls. The optimal thresholds presented in this review together with the consensus guidelines for using DFA might allow a more sensitive and reliable application of this metric for understanding human walking physiology than has been achieved to date.

Treadmill walking alters stride time dynamics in Parkinson's disease

BACKGROUND

Treadmill training may be used to improve gait rhythmicity in people with Parkinson's disease. Treadmills, however, alter dynamical stride time fluctuations in healthy adults in a manner that mimics pathologic states, indicating the stride-to-stride fluctuations that characterize healthy gait are constrained. It is unclear if treadmills similarly alter dynamic gait properties in Parkinson's disease.

RESEARCH QUESTION

Do stride time fractal dynamics in individuals with Parkinson's disease differ between treadmill and overground walking?

METHODS

Fifteen participants with Parkinson's disease and 15 healthy age-similar adults walked for 6 min in a conventional overground condition and on a treadmill while wearing inertial measurement units. Gait speed, stride times and stride time variability were measured. Fractal exponents (α) were computed with adaptive fractal analysis. Inferential statistics were analyzed with mixed model analyses of variance and post hoc simple effects tests.

RESULTS

Mean gait speeds decreased and stride times increased on the treadmill but did not differ between the Parkinson's and control groups. Stride time variability was greater in the Parkinson's than control group in both conditions. Most relevant to our research question, stride time fractal exponents were greater on the treadmill (mean α = .910) than overground (mean α = .797) in individuals with Parkinson's disease, but not in healthy controls.

SIGNIFICANCE

The fractal scaling exponent α emanating from stride time fluctuations during treadmill walking increased toward a 1/f signal of α = 1.0 that has been interpreted as an optimal structural variability for gait. The clinical implication is that treadmill training may promote more efficient walking dynamics in people with Parkinson's disease than conventional overground training.

Asymmetric dynamic center-of-pressure in Parkinson's disease

BACKGROUND

Gait disturbance gradually worsens as Parkinson's disease (PD) progresses, which significantly affects the quality of life of PD patients. Treadmill-based gait analysis systems can measure gait parameters including the dynamic center-of-pressure (COP) trajectory during ambulation. In this study, we hypothesized that altered dynamic COP changes are new gait characteristics for PD patients.

METHODS

Dynamic COP parameters and classic spatiotemporal parameters were obtained for each patient using a treadmill-based system at the maximal comfortable treadmill speed (MCTS). We compared dynamic COP parameters between 44 PD patients and 31 controls, correlated these parameters with clinical and spatiotemporal data, and adjusted for age and MCTS to determine whether the parameters were independent from the treadmill speed. We also evaluated characteristics of COP parameters in relation to the more and less affected sides in PD patients.

RESULTS

During treadmill walking the length of the COP trajectory in the stance phase was decreased, an effect that was more prominent on the more affected side in PD patients. COP parameters related to this change were significantly altered in patients when compared to controls. Asymmetry of the COP trajectories compared between both feet was identified as a significant gait characteristic after adjusting for age and MCTS. The overlaid graphical display of dynamic COP trajectory in PD patients showed "distorted butterfly with asymmetric wing" feature.

CONCLUSION

Dynamic COP asymmetry provides a new and intuitive way to analyze gait abnormalities of PD patients. Further studies with prospective designs will substantiate the clinical usefulness of this feature of gait.

Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review

A growing body of research calibrating and validating accelerometers to classify physical activity intensities has led to a range of cut-points. However, the applicability of current calibration protocols to clinical populations remains to be addressed. The aim of this review was to evaluate the accuracy of the methods for calibrating and validating of accelerometers to estimate physical activity intensity thresholds for clinical populations. Six databases were searched between March and July to 2017 using text words and subject headings. Studies developing moderate-to-vigorous intensity physical activity cut-points for adult clinical populations were included. The risk of bias was assessed using the health measurement instruments and a specific checklist for calibration studies. A total of 543,741 titles were found and 323 articles were selected for full-text assessment, with 11 meeting the inclusion criteria. Twenty-three different methods for calibration were identified using different models of ActiGraph and Actical accelerometers. Disease-specific cut-points ranged from 591 to 2717 counts·min-1 and were identified for two main groups of clinical conditions: neuromusculoskeletal disorders and metabolic diseases. The heterogeneity in the available clinical protocols hinders the applicability and comparison of the developed cut-points. As such, a mixed protocol containing a controlled laboratory exercise test and activities of daily-life is suggested. It is recommended that this be combined with a statistical approach that allows for adjustments according to disease severity or the use of machine learning models. Finally, this review highlights the generalisation of cut-points developed on healthy populations to clinical populations is inappropriate.

Characterization of statistical persistence in joint angle variation during walking

The objective of this study was to characterize joint angle variation across strides. Specifically, the statistical persistence of variations were quantified using the Hurst exponent. If a time series exhibits statistical persistence, then a parameter which is smaller (or larger) than average will tend to be followed by additional values that are also smaller (or larger) than average. Human walking has statistical persistence between stride durations. Variation in stride duration must arise from variation in the motion of the leg segments during walking. It is unclear, however, if the joint angle variation also exhibits statistical persistence. This study examined kinematic data collected from nine healthy adults walking for 10 min at a self-selected comfortable speed on a treadmill. The joint angle variation in the lower limbs was parameterized using first-order Fourier series which in turn were described by frequency and magnitude coefficients for each stride. To determine if the joint angle variation exhibited statistical persistence, the Hurst exponent was found for each coefficient at each joint. The mean Hurst exponents were 0.54 for the frequency coefficients and 0.61 for the magnitude coefficients. Neither the frequency or magnitude coefficients exhibited statistically significant persistence, although some of the magnitude coefficients were close to reaching statistical significance. This suggests that joint angle variability in healthy adults does not directly produce the statistical persistence observed in stride duration fluctuations.

Effect of sampling frequency on fractal fluctuations during treadmill walking

The temporal dynamics of stride-to-stride fluctuations in steady-state walking reveal important information about locomotor control and can be quantified using so-called fractal analyses, notably the detrended fluctuation analysis (DFA). Gait dynamics are often collected during treadmill walking using 3-D motion capture to identify gait events from kinematic data. The sampling frequency of motion capture systems may impact the precision of event detection and consequently impact the quantification of stride-to-stride variability. This study aimed i) to determine if collecting multiple walking trials with different sampling frequency affects DFA values of spatiotemporal parameters during treadmill walking, and ii) to determine the reliability of DFA values across downsampled conditions. Seventeen healthy young adults walked on a treadmill while their gait dynamics was captured using different sampling frequency (60, 120 and 240 Hz) in each condition. We also compared data from the highest sampling frequency to downsampled versions of itself. We applied DFA to the following time series: step length, time and speed, and stride length, time and speed. Reliability between experimental conditions and between downsampled conditions were measured with 1) intraclass correlation estimates and their 95% confident intervals, calculated based on a single-measurement, absolute-agreement, two-way mixed-effects model (ICC 3,1), and 2) Bland-Altman bias and limits of agreement. Both analyses revealed a poor reliability of DFA results between conditions using different sampling frequencies, but a relatively good reliability between original and downsampled spatiotemporal variables. Collectively, our results suggest that using sampling frequencies of 120 Hz or 240 Hz provide similar results, but that using 60 Hz may alter DFA values. We recommend that gait kinematics should be collected at around 120 Hz, which provides a compromise between event detection accuracy and processing time.

Fractal properties and short-term correlations in motor control in cycling: influence of a cognitive challenge

Fluctuations in cyclic tasks periods is a known characteristic of human motor control. Specifically, long-range fractal fluctuations have been evidenced in the temporal structure of these variations in human locomotion and thought to be the outcome of a multicomponent physiologic system in which control is distributed across intricate cortical, spinal and neuromuscular regulation loops. Combined with long-range correlation analyses, short-range autocorrelations have proven their use to describe control distribution across central and motor components. We used relevant tools to characterize long- and short-range correlations in revolution time series during cycling on an ergometer in 19 healthy young adults. We evaluated the impact of introducing a cognitive task (PASAT) to assess the role of central structures in control organization. Autocorrelation function and detrending fluctuation analysis (DFA) demonstrated the presence of fractal scaling. PSD in the short range revealed a singular behavior which cannot be explained by the usual models of even-based and emergent timing. The main outcomes are that (1) timing in cycling is a fractal process, (2) this long-range fractal behavior increases in persistence with dual-task condition, which has not been previously observed, (3) short-range behavior is highly persistent and unaffected by dual-task. Relying on the inertia of the oscillator may be a way to distribute more control to the periphery, thereby allocating less resources to central process and better managing additional cognitive demands. This original behavior in cycling may explain the high short-range persistence unaffected by dual-task, and the increase in long-range persistence with dual-task.

Deterioration of specific aspects of gait during the instrumented 6-min walk test among people with multiple sclerosis

Prolonged walking is typically impaired among people with multiple sclerosis (pwMS), however, it is unclear what the contributing factors are or how to evaluate this deterioration. We aimed to determine which gait features become worse during sustained walking and to examine the clinical correlates of gait fatigability in pwMS. Fifty-eight pwMS performed the 6-min walk test while wearing body-fixed sensors. Multiple gait domains (e.g., pace, rhythm, variability, asymmetry and complexity) were compared across each minute of the test and between mild- and moderate-disability patient groups. Associations between the decline in gait performance (i.e., gait fatigability) and patient-reported gait disability, fatigue and falls were also determined. Cadence, stride time variability, stride regularity, step regularity and gait complexity significantly deteriorated during the test. In contrast, somewhat surprisingly, gait speed and swing time asymmetry did not change. As expected, subjects with moderate disability (n = 24) walked more poorly in most gait domains compared to the mild-disability group (n = 34). Interestingly, a group × fatigue interaction effect was observed for cadence and gait complexity; these measures decreased over time in the moderate-disability group, but not in the mild group. Gait fatigability rate was significantly correlated with physical fatigue, gait disability, and fall history. These findings suggest that sustained walking affects specific aspects of gait, which can be used as markers for fatigability in MS. This effect on gait depends on the degree of disability, and may increase fall risk in pwMS. To more fully understand and monitor correlates that reflect everyday walking in pwMS, multiple domains of gait should be quantified.

Physiological complexity of gait between regular and non-exercisers with Parkinson's disease

BACKGROUND

Physiological complexity represents overall health of a system and its underlying capacity to adapt to stresses. The primary purpose of this study was to determine if physiological complexity of gait both ON and OFF anti-Parkinson medication differed between regular and non-exercisers with Parkinson's disease.

METHODS

Twenty participants with idiopathic Parkinson's disease were enrolled in this cross-sectional study (regular exercisers n = 10, non-exercisers n = 10). Two data collection sessions were completed during a single visit, first after a 12-hour overnight withdrawal from anti-Parkinson medications (OFF), and again one-hour after taking anti-Parkinson medications (ON). During each session participants completed a 2-minute walking task at their preferred pace while wearing wireless inertial measurement units on each lower extremity segment (thigh, shank, foot). Multivariate multiscale entropy was calculated from the tri-axial accelerometer signals and converted to a complexity index for analysis.

FINDINGS

Regular exercisers demonstrated significantly higher complexity indices ON and OFF anti-Parkinson medications compared to non-exercisers (ON F = 3.84 P = 0.02; OFF F = 3.61, P < 0.03). Regular exercisers did not significantly differ in complexity between OFF and ON states (most affected leg F = 0.15 P = 0.71; least affected leg F = 0.30 P = 0.60), but non-exercisers demonstrated significantly decreased complexity in the least affected leg OFF anti-Parkinson medications (F = 5.17 P < 0.04).

INTERPRETATION

Enhanced gait complexity in the regular exercisers may indicate that ongoing exercise is a key ingredient contributing to health in persons with Parkinson's disease. Exercising on a regular basis with Parkinson's disease may augment one's ability to adapt to barriers encountered during gait regardless of medication state.

Walking Along Curved Trajectories. Changes With Age and Parkinson's Disease. Hints to Rehabilitation

In this review, we briefly recall the fundamental processes allowing us to change locomotion trajectory and keep walking along a curved path and provide a review of contemporary literature on turning in older adults and people with Parkinson's Disease (PD). The first part briefly summarizes the way the body exploits the physical laws to produce a curved walking trajectory. Then, the changes in muscle and brain activation underpinning this task, and the promoting role of proprioception, are briefly considered. Another section is devoted to the gait changes occurring in curved walking and steering with aging. Further, freezing during turning and rehabilitation of curved walking in patients with PD is mentioned in the last part. Obviously, as the research on body steering while walking or turning has boomed in the last 10 years, the relevant critical issues have been tackled and ways to improve this locomotor task proposed. Rationale and evidences for successful training procedures are available, to potentially reduce the risk of falling in both older adults and patients with PD. A better understanding of the pathophysiology of steering, of the subtle but vital interaction between posture, balance, and progression along non-linear trajectories, and of the residual motor learning capacities in these cohorts may provide solid bases for new rehabilitative approaches.

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.

Which Gait Parameters and Walking Patterns Show the Significant Differences Between Parkinson's Disease and Healthy Participants?

This study investigated the difference in the gait of patients with Parkinson’s disease (PD), age-matched controls and young controls during three walking patterns. Experiments were conducted with 24 PD, 24 age-matched controls and 24 young controls, and four gait intervals were measured using inertial measurement units (IMU). Group differences between the mean and variance of the gait parameters (stride interval, stance interval, swing interval and double support interval) for the three groups were calculated and statistical significance was tested. The results showed that the variance in each of the four gait parameters of PD patients was significantly higher compared with the controls, irrespective of the three walking patterns. This study showed that the variance of any of the gait interval parameters obtained using IMU during any of the walking patterns could be used to differentiate between the gait of PD and control people.

Assessing Gait in Parkinson's Disease Using Wearable Motion Sensors: A Systematic Review

Abstract: Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Gait impairments are common among people with PD. Wearable sensor systems can be used for gait analysis by providing spatio-temporal parameters useful to investigate the progression of gait problems in Parkinson disease. However, various methods and tools with very high variability have been developed. The aim of this study is to review published articles of the last 10 years (from 2008 to 2018) concerning the application of wearable sensors to assess spatio-temporal parameters of gait in patients with PD. We focus on inertial sensors used for gait analysis in the clinical environment (i.e., we do not cover the use of inertial sensors to monitor walking or general activities at home, in unsupervised environments). Materials and Methods: Relevant articles were searched in the Medline database using Pubmed. Results and Discussion: Two hundred ninety-four articles were initially identified while searching the scientific literature regarding this topic. Thirty-six articles were selected and included in this review. Conclusion: Wearable motion sensors are useful, non-invasive, low-cost, and objective tools that are being extensively used to perform gait analysis on PD patients. Being able to diagnose and monitor the progression of PD patients makes wearable sensors very useful to evaluate clinical efficacy before and after therapeutic interventions. However, there is no uniformity in the use of wearable sensors in terms of: number of sensors, positioning, chosen parameters, and other characteristics. Future research should focus on standardizing the measurement setup and selecting which spatio-temporal parameters are the most informative to analyze gait in PD. These parameters should be provided as standard assessments in all studies to increase replicability and comparability of results.

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.