Dataset Information

Coordination of the non-paretic leg during hemiparetic gait: expected and novel compensatory patterns.

ABSTRACT:

Background

Post-stroke hemiparesis is usually considered a unilateral motor control deficit of the paretic leg, while the non-paretic leg is assumed to compensate for paretic leg impairments and have minimal to no deficits. While the non-paretic leg electromyography (EMG) patterns are clearly altered, how the non-paretic leg acts to compensate remains to be established.

Methods

Kinesiological data were recorded from sixty individuals with chronic hemiparesis (age: 60.9, SD=12.6 years, 21 females, 28 right hemiparetic, time since stroke: 4.5 years, SD 3.9 years), divided into three speed-based groups, and twenty similarly aged healthy individuals (age: 65.1, SD=10.4 years, 15 females). All walked on an instrumented split-belt treadmill at their self-selected speed and control subjects also walked at slower speeds matching those of the persons with hemiparesis. We determined the differences in magnitude and timing of non-paretic EMG activity relative to healthy control subjects in four pre-defined regions of stance phase of the gait cycle.

Findings

Integrated EMG activity and EMG timing in the non-paretic leg were different in many muscles. Multiple compensatory patterns identified included: increased EMG output when the muscle was typically active in controls and novel compensatory EMG patterns that appeared to provide greater propulsion or support with little evidence of impaired motor performance.

Interpretation

Most novel compensations were made possible by altered kinematics of the paretic and non-paretic leg (i.e., early stance plantarflexor activity provided propulsion due to the decreased advancement of the non-paretic foot) while others (late single limb stance knee extensor and late stance hamstring activity) appeared to be available mechanisms for increasing propulsion.

SUBMITTER: Raja B

PROVIDER: S-EPMC3535278 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Coordination of the non-paretic leg during hemiparetic gait: expected and novel compensatory patterns.

Raja Bhavana B Neptune Richard R RR Kautz Steven A SA

Clinical biomechanics (Bristol, Avon) 20120913 10

<h4>Background</h4>Post-stroke hemiparesis is usually considered a unilateral motor control deficit of the paretic leg, while the non-paretic leg is assumed to compensate for paretic leg impairments and have minimal to no deficits. While the non-paretic leg electromyography (EMG) patterns are clearly altered, how the non-paretic leg acts to compensate remains to be established.<h4>Methods</h4>Kinesiological data were recorded from sixty individuals with chronic hemiparesis (age: 60.9, SD=12.6 ye ...[more]

PMID: 22981679

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Project description:IntroductionRobot-assisted gait training has been reported to improve gait in individuals with hemiparetic stroke. Ideally, the gait training program should be customized based on individuals' gait characteristics and longitudinal changes. However, a gait robot that uses gait characteristics to provide individually tailored gait training has not been proposed. The new gait training robot, "Welwalk WW-2000," permits modification of various parameters, such as time and load of mechanical assistance for a patient's paralyzed leg. The robot is equipped with sensors and a markerless motion capture system to detect abnormal hemiparetic gait patterns during robot-assisted gait training. Thus, it can provide individually tailored gait training. This study aimed to investigate the criterion validity of the gait analysis system in the Welwalk WW-2000 in healthy adults.Materials and methodsTwelve healthy participants simulated nine abnormal gait patterns that were often manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform a total of 36 gait trials, with four levels of severity for each abnormal gait pattern. Fifteen strides for each gait trial were recorded using the markerless motion capture system in the Welwalk WW-2000 and a marker-based three-dimensional (3D) motion analysis system. The abnormal gait pattern index was then calculated for each stride from both systems. The correlation of the index values between the two methods was evaluated using Spearman's rank correlation coefficients for each gait pattern in each participant.ResultsUsing the participants' index values for each abnormal gait pattern obtained using the two motion analysis methods, the median Spearman's rank correlation coefficients ranged from 0.68 to 0.93, which corresponded to moderate to very high correlation.ConclusionThe gait analysis system in the Welwalk WW-2000 for real-time detection of abnormal gait patterns during robot-assisted gait training was suggested to be a valid method for assessing gait characteristics in individuals with hemiparetic stroke.Clinical trial registration[https://jrct.niph.go.jp], identifier [jRCT 042190109].

Project description:BackgroundSpasticity is an important complication after stroke, especially in the anti-gravity muscles, i.e. lower limb extensors. However the contribution of hyperexcitable muscle spindle reflex loops to gait impairments after stroke is often disputed. In this study a neuro-musculoskeletal model was developed to investigate the contribution of an increased length and velocity feedback and altered reflex modulation patterns to hemiparetic gait deficits.MethodsA musculoskeletal model was extended with a muscle spindle model providing real-time length and velocity feedback of gastrocnemius, soleus, vasti and rectus femoris during a forward dynamic simulation (neural control model). By using a healthy subject's base muscle excitations, in combination with increased feedback gains and altered reflex modulation patterns, the effect on kinematics was simulated. A foot-ground contact model was added to account for the interaction effect between the changed kinematics and the ground. The qualitative effect i.e. the directional effect and the specific gait phases where the effect is present, on the joint kinematics was then compared with hemiparetic gait deviations reported in the literature.ResultsOur results show that increased feedback in combination with altered reflex modulation patterns of soleus, vasti and rectus femoris muscle can contribute to excessive ankle plantarflexion/inadequate dorsiflexion, knee hyperextension/inadequate flexion and increased hip extension/inadequate flexion during dedicated gait cycle phases. Increased feedback of gastrocnemius can also contribute to excessive plantarflexion/inadequate dorsiflexion, however in combination with excessive knee and hip flexion. Increased length/velocity feedback can therefore contribute to two types of gait deviations, which are both in accordance with previously reported gait deviations in hemiparetic patients. Furthermore altered modulation patterns, in particular the reduced suppression of the muscle spindle feedback during swing, can contribute largely to an increased plantarflexion and knee extension during the swing phase and consequently to hampered toe clearance.ConclusionsOur results support the idea that hyperexcitability of length and velocity feedback pathways, especially in combination with altered reflex modulation patterns, can contribute to deviations in hemiparetic gait. Surprisingly, our results showed only subtle temporal differences between length and velocity feedback. Therefore, we cannot attribute the effects seen in kinematics to one specific type of feedback.

Project description:BACKGROUND:Stroke survivors often have lower extremity sensorimotor impairments, resulting in an inability to sufficiently recruit muscle activity at appropriate times in a gait cycle. Currently there is a lack of a standardized method that allows comparison of muscle activation in hemiparetic gait post-stroke to a normative profile. METHODS:We developed a new tool to quantify altered muscle activation patterns (AMAP). AMAP accounts for spatiotemporal asymmetries in stroke gait by evaluating the deviations of muscle activation specific to each gait sub-phase. It also recognizes the characteristic variability within the healthy population. The inter-individual variability of normal electromyography (EMG) patterns within some sub-phases of the gait cycle is larger compared to others, therefore AMAP penalizes more for deviations in a gait sub-phase with a constant profile (absolute active or inactive) vs variable profile. EMG data were collected during treadmill walking, from eight leg muscles of 34 stroke survivors at self-selected speeds and 20 healthy controls at four different speeds. Stroke survivors' AMAP scores, for timing and amplitude variations, were computed in comparison to healthy controls walking at speeds matched to the stroke survivors' self-selected speeds. RESULTS:Altered EMG patterns in the stroke population quantified using AMAP agree with the previously reported EMG alterations in stroke gait that were identified using qualitative methods. We defined scores ranging between ±2.57 as "normal". Only 9% of healthy controls were outside "normal" window for timing and amplitude. Percentages of stroke subjects outside the "normal" window for each muscle were, Soleus = 79%; 73%, Medial Gastrocnemius = 62%; 79%, Tibialis Anterior = 62%; 59%, and Gluteus Medius = 48%; 51% for amplitude and timing component respectively, alterations were relatively smaller for the other four muscles. Paretic-propulsion was negatively correlated to AMAP scores for the timing component of Soleus. Stroke survivors' self-selected walking speed was negatively correlated with AMAP scores for amplitude and timing of Soleus but only amplitude of Medial gastrocnemius (p < 0.05). CONCLUSIONS:Our results validate the ability of AMAP to identify alterations in the EMG patterns within the stroke population and its potential to be used to identify the gait phases that may require more attention when developing an optimal gait training paradigm. TRIAL REGISTRATION:ClinicalTrials.gov NCT00712179 , Registered July 3rd 2008.

Project description:Background:A better understanding of the neural changes associated with paresis in stroke patients could have important implications for therapeutic approaches. Dynamic Causal Modeling (DCM) for functional magnetic resonance imaging (fMRI) is commonly used for analyzing effective connectivity patterns of brain networks due to its significant property of modeling neural states behind fMRI signals. We applied this technique to analyze the differences between motor networks (MNW) activated by continuous passive movement (CPM) of paretic and non-paretic ankles in subacute stroke patients. This study aimed to identify CPM induced connectivity characteristics of the primary sensory area (S1) and the differences in extrinsic directed connections of the MNW and to explain the hemodynamic differences of brain regions of MNW. Methods:For the network analysis, we used ten stroke patients' task fMRI data collected under CPMs of both ankles. Regions for the MNW, the primary motor cortex (M1), the premotor cortex (PM), the supplementary motor area (SMA) and the S1 were defined in a data-driven way, by independent component analysis. For the network analysis of both CPMs, we compared twelve models organized into two model-families, depending on the S1 connections and input stimulus modeling. Using DCM, we evaluated the extrinsic connectivity strengths and hemodynamic parameters of both stimulations of all patients. Results:After a statistical comparison of the extrinsic connections and their modulations of the "best model", we concluded that three contralateral self-inhibitions (cM1, cS1 and cSMA), one contralateral inter-regional connection (cSMA?cM1), and one interhemispheric connection (cM1?iM1) were significantly different. Our research shows that hemodynamic parameters can be estimated with the Balloon model using DCM but the parameters do not change with stroke. Conclusions:Our results confirm that the DCM-based connectivity analyses combined with Bayesian model selection may be a useful technique for quantifying the alteration or differences in the characteristics of the motor network in subacute stage stroke patients and in determining the degree of MNW changes.

Dataset Information

Coordination of the non-paretic leg during hemiparetic gait: expected and novel compensatory patterns.

Background

Methods

Findings

Interpretation

Publications

Coordination of the non-paretic leg during hemiparetic gait: expected and novel compensatory patterns.

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