Proposition of a Classification of Adult Patients with Hemiparesis in Chronic Phase

Abstract

BackgroundPatients who have developed hemiparesis as a result of a central nervous system lesion, often experience reduced walking capacity and worse gait quality. Although clinically, similar gait patterns have been observed, presently, no clinically driven classification has been validated to group these patients’ gait abnormalities at the level of the hip, knee and ankle joints. This study has thus intended to put forward a new gait classification for adult patients with hemiparesis in chronic phase, and to validate its discriminatory capacity.Methods and FindingsTwenty-six patients with hemiparesis were included in this observational study. Following a clinical examination, a clinical gait analysis, complemented by a video analysis, was performed whereby participants were requested to walk spontaneously on a 10m walkway. A patient’s classification was established from clinical examination data and video analysis. This classification was made up of three groups, including two sub-groups, defined with key abnormalities observed whilst walking. Statistical analysis was achieved on the basis of 25 parameters resulting from the clinical gait analysis in order to assess the discriminatory characteristic of the classification as displayed by the walking speed and kinematic parameters. Results revealed that the parameters related to the discriminant criteria of the proposed classification were all significantly different between groups and subgroups. More generally, nearly two thirds of the 25 parameters showed significant differences (p<0.05) between the groups and sub-groups. However, prior to being fully validated, this classification must still be tested on a larger number of patients, and the repeatability of inter-operator measures must be assessed.ConclusionsThis classification enables patients to be grouped on the basis of key abnormalities observed whilst walking and has the advantage of being able to be used in clinical routines without necessitating complex apparatus. In the midterm, this classification may allow a decision-tree of therapies to be developed on the basis of the group in which the patient has been categorised.

An Optimization Method Tracking EMG, Ground Reactions Forces, and Marker Trajectories for Musculo-Tendon Forces Estimation in Equinus Gait

“…It is however, established that walking is a locomotion task that is performed in sagittal, coronal, and transversal planes (Perry and Burnfield, 2010). In particular, patients often develop compensatory movements in the coronal plane when pathological impairments result in reduced foot clearance capacity in the sagittal plane (Chantraine et al, 2016). Despite this simplification, the accuracy of kinematic tracking observed in the present results suggest that there is potential for the EMG marker tracking optimization process to perform 3D gait motion simulations.…”

Lower limb sagittal gait kinematics can be predicted based on walking speed, gender, age and BMI

“…This can be illustrated with the knee flexion amplitude during gait. A reduced knee flexion during the swing phase is commonly called stiff-knee gait after a central nervous system lesion, with a spasticity of the rectus femoris muscle as primary recognised causal impairment 9,10 . However, several authors have also pointed out the impact of walking speed on this gait feature 7,8 .…”

A Study of Biofeedback Gait Training in Cerebral Stroke Patients in the Early Recovery Phase with Stance Phase as Target Parameter

“…The minimum number of sessions was eight. The mean number of sessions was 9.2 ± 2.12 (8)(9)(10)(11). This was the reality in which we worked.…”

“…The gait of hemiplegic patients has very specific features [6,7]: reduced walking speed, increased double stance phase, and reduced amplitude of movement in the leg joints [8]. There are four main gait abnormalities associated with hemiparesis [9]: the drop-foot gait, the circumduction gait, the hip hiking gait, and the back knee gait.…”

“…The third parameter-cadence-is also not specific to the affected side. However, not only do the above mentioned resultant parameters change significantly in patients with cerebral stroke but also their determinant parameters [8][9][10]: walking cycle duration, stance period, double and single support periods, and gait harmony (equal intervals of the start of the walking cycle (WC) on both sides).…”