Dynamic structure of lower limb joint angles during walking post-stroke

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

A Multimodal Analysis to Explore Upper Limb Motor Recovery at 4 Weeks After Stroke: Insights From EEG and Kinematics Measures

Background. Stroke is a leading cause of death and disability worldwide and there is a very short period of increased synaptic plasticity, fundamental in motor recovery. Thus, it is crucial to acquire data to guide the rehabilitation treatment. Promising results have been achieved with kinematics and neurophysiological data, but currently, few studies integrate these different modalities. Objectives. We explored the correlations between standardized clinical scales, kinematic data, and EEG measures 4 weeks after stroke. Methods. 26 patients were considered. Among them, 20 patients also performed the EEG study, beyond the kinematic analysis, at 4 weeks. Results. We found correlations between the Fugl-Meyer Assessment-Upper Extremity, movement duration, smoothness measures, and velocity peaks. Moreover, EEG measures showed a tendency for the healthy hemisphere to vicariate the affected one in patients characterized by better clinical conditions. Conclusions. These results suggest the relevance of kinematic (in particular movement duration and smoothness) and EEG biomarkers to evaluate post-stroke recovery. We emphasize the importance of integrating clinical data with kinematic and EEG analyses from the early stroke stages, in order to guide rehabilitation strategies to best leverage the short period of increased synaptic plasticity.

The Interplay Between Walking Speed, Economy, and Stability After Stroke

BACKGROUND AND PURPOSE

Energy minimization is thought to underlie the naturally selected, preferred walking speed; however, people post-stroke walk slower than their most economical speed, presumably to optimize other objectives, such as stability. The purpose of this study was to examine the interplay between walking speed, economy, and stability.

METHODS

Seven individuals with chronic hemiparesis walked on a treadmill at 1 of 3 randomized speeds: slow, preferred, and fast. Concurrent measurements of speed-induced changes in walking economy (ie, the energy needed to move 1 kg of bodyweight 1 ml O 2 /kg/m) and stability were made. Stability was quantified as the regularity and divergence of the mediolateral motion of the pelvic center of mass (pCoM) during walking, as well as pCoM motion relative to the base of support.

RESULTS

Slower walking speeds were more stable (ie, pCoM motion was 10% ± 5% more regular and 26% ± 16% less divergent) but 12% ± 5% less economical. Conversely, faster walking speeds were 9% ± 8% more economical, but also less stable (ie, pCoM motion was 17% ± 5% more irregular). Individuals with slower walking speeds had an enhanced energetic benefit when walking faster ( rs = 0.96, P < 0.001). Individuals with greater neuromotor impairment had an enhanced stability benefit when walking slower ( rs = 0.86, P = 0.01).

DISCUSSION AND CONCLUSIONS

People post-stroke appear to prefer walking speeds that are faster than their most stable speed but slower than their most economical speed. The preferred walking speed after stroke appears to balance stability and economy. To encourage faster and more economical walking, deficits in the stable control of the mediolateral motion of the pCoM may need to be addressed.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A416 ).

Characterizing stroke-induced changes in the variability of lower limb kinematics using multifractal detrended fluctuation analysis

Movement variability reflects the adaptation of the neuromuscular control system to internal or external perturbations, but its relationship to stroke-induced injury is still unclear. In this study, the multifractal detrended fluctuation analysis was used to explore the stroke-induced changes in movement variability by analyzing the joint angles in a treadmill-walking task. Eight healthy subjects and ten patients after stroke participated in the experiment, performing a treadmill-walking task at a comfortable speed. The kinematics data of the lower limbs were collected by the motion-capture system, and two indicators, the degree of multifractality (α) and degree of correlation [h(2)], were used to investigate the mechanisms underlying neuromuscular control. The results showed that the knee and ankle joint angles were multifractal and persistent at various scales, and there was a significant difference in the degree of multifractality and the degree of correlation at the knee and ankle joint angles among the three groups, with the values being ranked in the following order: healthy subjects < non-paretic limb < paretic limb. These observations highlighted increased movement variability and multifractal strength in patients after stroke due to neuromotor defects. This study provided evidence that multifractal detrended analysis of the angles of the knee and ankle joints is useful to investigate the changes in movement variability and multifractal after stroke. Further research is needed to verify and promote the clinical applications.

Effect of gap-filling technique and gap location on linear and nonlinear calculations of motion during locomotor activities

BACKGROUND

Marker occlusion during camera-based movement analysis is common. Different interpolation techniques are available for estimating location of missing marker trajectories.

RESEARCH QUESTION

What is the effect of gap location and interpolation technique on linear and nonlinear measures for a given kinematic time series?

METHODS

Kinematic data were recorded during motor-assisted elliptical training and treadmill walking. Gap-filling techniques (i.e., Cubic, Makima, Autoregressive, Nearest Neighbor, and No Interpolation) and gap locations experimentally applied to each cycle across initially complete time series (Gap 1: local minimum and maximum peaks; Gap 2: maximum peaks; Gap 3: maximum peaks at negative slope; Gap 4: random locations) were examined during linear (Maxima and Minima joint angles) and nonlinear [maximum Lyapunov exponent (LyE)] measures.

RESULTS

Gap-filling technique and gap location influenced values calculated for linear and nonlinear measures of joint motions. When referenced to the gold standard (original data series without gaps), across all joints studied the average % error of Maxima and Minima joint angles and LyE % error were lower when applying Cubic, Makima, Autoregressive, and Nearest Neighbor techniques compared to No Interpolation (p < 0.0001). The % error of Maxima joint angles was lower for Gaps 1, 3, and 4 compared to Gap 2 (p = 0.0003), while % error of Minima joint angles was lower for Gaps 2 and 3, compared to Gaps 1 and 4 (p < 0.0001). An interaction between gap-filling technique and gap location was identified for LyE % error, in which Gap 4 % error was significantly greater during No Interpolation compared to other gap-filling techniques (p < 0.0001).

SIGNIFICANCE

Findings can guide selection of appropriate techniques to manage missing kinematic data points in camera-based motion analysis time series. Gap-filling techniques significantly reduced error in calculating select linear and nonlinear measures of variability, with Cubic most consistently resulting in the greatest reduction in error.

Dance-based exergaming on postural stability and kinematics in people with chronic stroke - A preliminary study

INTRODUCTION

The study evaluated the feasibility, and compliance of a dance-based exergaming (DBExG) on postural stability (PS) and lower extremity (LE) kinematics, along with post-intervention changes in gait function and falls self-efficacy in people with chronic stroke (PwCS).

METHODS

Fifteen PwCS underwent DBExG for six weeks using Kinect "Just Dance 3." Pre- to post- changes were recorded during DBExG assessment on a fast-paced song (130 bpm) using an 8-camera motion capture system to assess PS (center of mass [CoM] excursions [EXs] in the anterior-posterior [AP] and mediolateral [ML] directions) and LE kinematics (hip, knee, and ankle joint angle EXs). Gait function was also assessed with gait parameters, such as gait speed, cadence, and gait symmetry on an electronic walkway. Falls self-efficacy was recorded with Falls Efficacy Scale (FES).

RESULTS

The AP and ML CoM EXs and paretic joint angle EXs significantly increased pre- to post- DBExG assessment (p < .05). Gait parameters, and falls self-efficacy measures significantly changed pre- to post- DBExG (p < .05).

CONCLUSIONS

Results exhibited the feasibility of the proposed DBExG for positively impacting postural stability, and kinematics, along with increasing gait function and falls self-efficacy among PwCS.

Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke

Hemiparetic walking after stroke is typically slow, asymmetric, and inefficient, significantly impacting activities of daily living. Extensive research shows that functional, intensive, and task-specific gait training is instrumental for effective gait rehabilitation, characteristics that our group aims to encourage with soft robotic exosuits. However, standard clinical assessments may lack the precision and frequency to detect subtle changes in intervention efficacy during both conventional and exosuit-assisted gait training, potentially impeding targeted therapy regimes. In this paper, we use exosuit-integrated inertial sensors to reconstruct three clinically meaningful gait metrics related to circumduction, foot clearance, and stride length. Our method corrects sensor drift using instantaneous information from both sides of the body. This approach makes our method robust to irregular walking conditions poststroke as well as usable in real-time applications, such as real-time movement monitoring, exosuit assistance control, and biofeedback. We validate our algorithm in eight people poststroke in comparison to lab-based optical motion capture. Mean errors were below 0.2 cm (9.9%) for circumduction, −0.6 cm (−3.5%) for foot clearance, and 3.8 cm (3.6%) for stride length. A single-participant case study shows our technique’s promise in daily-living environments by detecting exosuit-induced changes in gait while walking in a busy outdoor plaza.

Dynamic structure of variability in joint angles and center of mass position during user-driven treadmill walking

BACKGROUND

Overground locomotion exhibits greater movement variability and less dynamic stability compared to typical fixed-speed treadmill walking. To minimize the differences between treadmill and overground locomotion, researchers are developing user-driven treadmill systems that adjust the speed of the treadmill belts in real-time based on how fast the subject is trying to walk.

RESEARCH QUESTION

Does dynamic structure of variability, quantified by the Lyapunov exponent (LyE), of joint angles and center of mass (COM) position differ between a fixed-speed treadmill (FTM) and user-driven treadmill (UTM) for healthy subjects?

METHODS

Eleven healthy, adult subjects walked on a user-driven treadmill that updated its speed in real-time based on the subjects' propulsive forces, location, step length, and step time, and at a matched speed on a typical, fixed-speed treadmill for 1-minute. The LyE for flexion/extension joint angles and center of mass position were calculated.

RESULTS

Subjects exhibited higher LyE values of joint angles on the UTM compared to the FTM indicating that walking on the UTM may be more similar to overground locomotion. No change in COM LyE was observed between treadmill conditions indicating that subjects' balance was not significantly altered by this new training paradigm.

SIGNIFICANCE

The user-driven treadmill may be a more valuable rehabilitation tool for improving gait than fixed-speed treadmill training, as it may increase the effectiveness of transitioning learned behaviors to overground compared to fixed-speed treadmills.