Heiko Gaßner

Immediate effects of perturbation treadmill training on gait and postural control in patients with Parkinson’s disease

The study investigates immediate adaptations of gait and balance to a single session of perturbed treadmill walking in patients with Parkinsons disease. 39 Parkinsons patients in stage 1-3.5 of the Hoehn and Yahr Scale were randomized into one of two groups, stratified by disease severity: The experimental group (n=19) walked on a treadmill prototype which constantly applied perturbation by small three-dimensional tilting movements of the walking surface. The control group (n=20) trained on the identical treadmill without perturbations. Patients walked on the treadmill for 20min. Primary outcome measure was overground walking speed. Secondary outcomes were postural sway during quiet standing and spatiotemporal gait parameters during treadmill walking. Outcomes were measured repeatedly throughout the training session and after 10min retention. The experimental group significantly increased overground walking speed after intervention compared to the control group (p=0.014; ES=+0.41). Gait variability during treadmill walking significantly decreased after walking with perturbation. Sway area increased with treadmill walking only in the control group (p=0.009; ES=+0.49). No other postural sway measures changed over time. Subgroup analyses revealed that in the experimental group patients with more pronounced motor impairment demonstrated larger increases in overground walking speed (p=0.016; ES=+0.40) and stance phase symmetry (p=0.011; ES=-0.42). In conclusion, a single session of perturbation treadmill training led to gait improvements, which were more pronounced compared to unperturbed treadmill walking. Effects on static postural sway were less pronounced.

Towards Mobile Gait Analysis: Concurrent Validity and Test-Retest Reliability of an Inertial Measurement System for the Assessment of Spatio-Temporal Gait Parameters

The purpose of this study was to assess the concurrent validity and test–retest reliability of a sensor-based gait analysis system. Eleven healthy subjects and four Parkinson’s disease (PD) patients were asked to complete gait tasks whilst wearing two inertial measurement units at their feet. The extracted spatio-temporal parameters of 1166 strides were compared to those extracted from a reference camera-based motion capture system concerning concurrent validity. Test–retest reliability was assessed for five healthy subjects at three different days in a two week period. The two systems were highly correlated for all gait parameters (r>0.93). The bias for stride time was 0±16 ms and for stride length was 1.4±6.7 cm. No systematic range dependent errors were observed and no significant changes existed between healthy subjects and PD patients. Test-retest reliability was excellent for all parameters (intraclass correlation (ICC) > 0.81) except for gait velocity (ICC > 0.55). The sensor-based system was able to accurately capture spatio-temporal gait parameters as compared to the reference camera-based system for normal and impaired gait. The system’s high retest reliability renders the use in recurrent clinical measurements and in long-term applications feasible.

Segmentation of Gait Sequences in Sensor-Based Movement Analysis: A Comparison of Methods in Parkinson’s Disease

Robust gait segmentation is the basis for mobile gait analysis. A range of methods have been applied and evaluated for gait segmentation of healthy and pathological gait bouts. However, a unified evaluation of gait segmentation methods in Parkinson’s disease (PD) is missing. In this paper, we compare four prevalent gait segmentation methods in order to reveal their strengths and drawbacks in gait processing. We considered peak detection from event-based methods, two variations of dynamic time warping from template matching methods, and hierarchical hidden Markov models (hHMMs) from machine learning methods. To evaluate the methods, we included two supervised and instrumented gait tests that are widely used in the examination of Parkinsonian gait. In the first experiment, a sequence of strides from instructed straight walks was measured from 10 PD patients. In the second experiment, a more heterogeneous assessment paradigm was used from an additional 34 PD patients, including straight walks and turning strides as well as non-stride movements. The goal of the latter experiment was to evaluate the methods in challenging situations including turning strides and non-stride movements. Results showed no significant difference between the methods for the first scenario, in which all methods achieved an almost 100% accuracy in terms of F-score. Hence, we concluded that in the case of a predefined and homogeneous sequence of strides, all methods can be applied equally. However, in the second experiment the difference between methods became evident, with the hHMM obtaining a 96% F-score and significantly outperforming the other methods. The hHMM also proved promising in distinguishing between strides and non-stride movements, which is critical for clinical gait analysis. Our results indicate that both the instrumented test procedure and the required stride segmentation algorithm have to be selected adequately in order to support and complement classical clinical examination by sensor-based movement assessment.

Perturbation During Treadmill Training Improves Dynamic Balance and Gait in Parkinson’s Disease: A Single-Blind Randomized Controlled Pilot Trial:

Background. Gait and balance dysfunction are major symptoms in Parkinson’s disease (PD). Treadmill training improves gait characteristics in this population but does not reflect the dynamic nature of controlling balance during ambulation in everyday life contexts. Objective. To evaluate whether postural perturbations during treadmill walking lead to superior effects on gait and balance performance compared with standard treadmill training. Methods. In this single-blind randomized controlled trial, 43 PD patients (Hoehn & Yahr stage 1-3.5) were assigned to either an 8-week perturbed treadmill intervention (n = 21) or a control group (n = 22) training on the identical treadmill without perturbations. Patients were assessed at baseline, postintervention, and at 3 months’ follow-up. Primary endpoints were overground gait speed and balance (Mini-BESTest). Secondary outcomes included fast gait speed, walking capacity (2-Minute Walk Test), dynamic balance (Timed Up-and-Go), static balance (postural sway), and balance confidence (Activities-Specific Balance Confidence [ABC] scale). Results. There were no significant between-group differences in change over time for the primary outcomes. At postintervention, both groups demonstrated similar improvements in overground gait speed (P = .009), and no changes in the Mini-BESTest (P = .641). A significant group-by-time interaction (P = .048) existed for the Timed Up-and-Go, with improved performance only in the perturbation group. In addition, the perturbation but not the control group significantly increased walking capacity (P = .038). Intervention effects were not sustained at follow-up. Conclusions. Our primary findings suggest no superior effect of perturbation training on gait and balance in PD patients. However, some favorable trends existed for secondary gait and dynamic balance parameters, which should be investigated in future trials.

Gait and Cognition in Parkinson’s Disease: Cognitive Impairment Is Inadequately Reflected by Gait Performance during Dual Task

Introduction Cognitive and gait deficits are common symptoms in Parkinson’s disease (PD). Motor-cognitive dual tasks (DTs) are used to explore the interplay between gait and cognition. However, it is unclear if DT gait performance is indicative for cognitive impairment. Therefore, the aim of this study was to investigate if cognitive deficits are reflected by DT costs of spatiotemporal gait parameters. Methods Cognitive function, single task (ST) and DT gait performance were investigated in 67 PD patients. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) followed by a standardized, sensor-based gait test and the identical gait test while subtracting serial 3’s. Cognitive impairment was defined by a MoCA score <26. DT costs in gait parameters [(DT − ST)/ST × 100] were calculated as a measure of DT effect on gait. Correlation analysis was used to evaluate the association between MoCA performance and gait parameters. In a linear regression model, DT gait costs and clinical confounders (age, gender, disease duration, motor impairment, medication, and depression) were correlated to cognitive performance. In a subgroup analysis, we compared matched groups of cognitively impaired and unimpaired PD patients regarding differences in ST, DT, and DT gait costs. Results Correlation analysis revealed weak correlations between MoCA score and DT costs of gait parameters (r/rSp ≤ 0.3). DT costs of stride length, swing time variability, and maximum toe clearance (|r/rSp| > 0.2) were included in a regression analysis. The parameters only explain 8% of the cognitive variance. In combination with clinical confounders, regression analysis showed that these gait parameters explained 30% of MoCA performance. Group comparison revealed strong DT effects within both groups (large effect sizes), but significant between-group effects in DT gait costs were not observed. Conclusion These findings suggest that DT gait performance is not indicative for cognitive impairment in PD. DT effects on gait parameters were substantial in cognitively impaired and unimpaired patients, thereby potentially overlaying the effect of cognitive impairment on DT gait costs. Limits of the MoCA in detecting motor-function specific cognitive performance or variable individual response to the DT as influencing factors cannot be excluded. Therefore, DT gait parameters as marker for cognitive performance should be carefully interpreted in the clinical context.

Acute Neuromuscular Adaptations in the Postural Control of Patients with Parkinson’s Disease after Perturbed Walking

Patients suffering from Parkinson’s disease (PD) present motor impairments reflected in the dynamics of the center of pressure (CoP) adjustments during quiet standing. One method to study the dynamics of CoP adjustments is the entropic half-life (EnHL), which measures the short-term correlations of a time series at different time scales. Changes in the EnHL of CoP time series suggest neuromuscular adaptations in the control of posture. In this study, we sought to investigate the immediate changes in the EnHL of CoP adjustments of patients with PD during one session of perturbed (experimental group) and unperturbed treadmill walking (control group). A total of 39 patients with PD participated in this study. The experimental group (n = 19) walked on a treadmill providing small tilting of the treadmill platform. The control group (n = 20) walked without perturbations. Each participant performed 5-min practice followed by three 5-min training blocks of walking with or without perturbation (with 3-min resting in between). Quiet standing CoP data was collected for 30 s at pre-training, after each training block, immediately post-training, and after 10 min retention. The EnHL was computed on the original and surrogates (phase-randomized) CoP signals in the medio-lateral (ML) and anterior–posterior (AP) directions. Data was analyzed using four-way mixed ANOVA. Increased EnHL values were observed for both groups (Time effect, p < 0.001) as the intervention progressed, suggesting neuromuscular adaptations in the control of posture. The EnHL of surrogate signals were significantly lower than for original signals (p < 0.001), confirming that these adaptations come from non-random control processes. There was no Group effect (p = 0.622), however by analyzing the significant Group by Direction by Time interaction (p < 0.05), a more pronounced effect in the ML direction of the perturbed group was observed. Altogether, our findings show that treadmill walking decreases the complexity of CoP adjustments, suggesting neuromuscular adaptations in balance control during a short training period. Further investigations are required to assess these adaptations during longer training intervals.

Motor output complexity in Parkinson’s disease during quiet standing and walking: Analysis of short-term correlations using the entropic half-life

Parkinsons disease (PD) is associated with alterations in motor outputs such as center of pressure (CoP) adjustments during quiet standing and foot kinematics during walking. Previous research suggests that the complexity of motor outputs reflects the number of control processes stabilizing a specific movement, providing a measure that is linked to the neurological control of the movement. The Entropic Half Life (EnHL) represents a new method for assessing motor output complexity. We hypothesized that there will be a lack of neuromuscular control pathways for PD patients, resulting in a decrease in motor output complexity. We computed the EnHL of CoP adjustments during quiet standing and foot kinematics during walking of 70 PD patients and 33 age-matched controls. Patients with PD showed longer EnHL values compared to controls, suggesting a tighter motor control. Excluding vision led to a decrease of EnHL of CoP in both groups. EnHL was correlated with spatio-temporal gait parameters. We compared EnHL with the pull test and the timed up-and-go test. No significant differences were present in the pull test, yet motor output complexity was correlated with the timed up-and-go test. The results suggest a reduced complexity in motor outputs of PD patients affecting distinct motor functions.

Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty

BACKGROUND Despite the general success of total knee arthroplasty (TKA) regarding patient-reported outcome measures, studies investigating gait function have shown diverse functional outcomes. Mobile sensor-based systems have recently been employed for accurate clinical gait assessments, as they allow a better integration of gait analysis into clinical routines as compared to laboratory based systems. RESEARCH QUESTION In this study, we sought to examine whether an accurate assessment of gait function of knee osteoarthritis patients with respect to surgery outcome evaluation after TKA using a mobile sensor-based gait analysis system is possible. METHODS A foot-worn sensor-based system was used to assess spatio-temporal gait parameters of 24 knee osteoarthritis patients one day before and one year after TKA, and in comparison to matched control participants. Patients were clustered into positive and negative responder groups using a heuristic approach regarding improvements in gait function. Machine learning was used to predict surgery outcome based on pre-operative gait parameters. RESULTS Gait function differed significantly between controls and patients. Patient-reported outcome measures improved significantly after surgery, but no significant global gait parameter difference was observed between pre- and post-operative status. However, the responder groups could be correctly predicted with an accuracy of up to 89% using pre-operative gait parameters. Patients exhibiting high pre-operative gait function were more likely to experience a functional decrease after surgery. Important gait parameters for the discrimination were stride time and stride length. SIGNIFICANCE The early identification of post-surgical functional outcomes of patients is of great importance to better inform patients pre-operatively regarding surgery success and to improve post-surgical management.

Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications

Abstract Wearable sensor systems are of increasing interest in clinical gait analysis. However, little information about gait dynamics of patients under free living conditions is available, due to the challenges of integrating such systems unobtrusively into a patient’s everyday live. To address this limitation, new, fully integrated low power sensor insoles are proposed, to target applications particularly in home-monitoring scenarios. The insoles combine inertial as well as pressure sensors and feature wireless synchronization to acquire biomechanical data of both feet with a mean timing offset of 15.0 μs. The proposed system was evaluated on 15 patients with mild to severe gait disorders against the GAITRite® system as reference. Gait events based on the insoles’ pressure sensors were manually extracted to calculate temporal gait features such as double support time and double support. Compared to the reference system a mean error of 0.06 s ±0.06 s and 3.89 % ±2.61 % was achieved, respectively. The proposed insoles proved their ability to acquire synchronized gait parameters and address the requirements for home-monitoring scenarios, pushing the boundaries of clinical gait analysis.

Sensor-based gait analysis in atypical parkinsonian disorders

Gait impairment and reduced mobility are typical features of idiopathic Parkinsons disease (iPD) and atypical parkinsonian disorders (APD). Quantitative gait assessment may have value in the diagnostic workup of parkinsonian patients and as endpoint in clinical trials. The study aimed to identify quantitative gait parameter differences in iPD and APD patients using sensor‐based gait analysis and to correlate gait parameters with clinical rating scales.