Hans Wambacq

A Clinical Measurement to Quantify Spasticity in Children with Cerebral Palsy by Integration of Multidimensional Signals

Most clinical tools for measuring spasticity, such as the Modified Ashworth Scale (MAS) and the Modified Tardieu Scale (MTS), are not sufficiently accurate or reliable. This study investigated the clinimetric properties of an instrumented spasticity assessment. Twenty-eight children with spastic cerebral palsy (CP) and 10 typically developing (TD) children were included. Six of the children with CP were retested to evaluate reliability. To quantify spasticity in the gastrocnemius (GAS) and medial hamstrings (MEH), three synchronized signals were collected and integrated: surface electromyography (sEMG); joint-angle characteristics; and torque. Muscles were manually stretched at low velocity (LV) and high velocity (HV). Spasticity parameters were extracted from the change in sEMG and in torque between LV and HV. Reliability was determined with intraclass-correlation coefficients and the standard error of measurement; validity by assessing group differences and correlating spasticity parameters with the MAS and MTS. Reliability was moderately high for both muscles. Spasticity parameters in both muscles were higher in children with CP than in TD children, showed moderate correlation with the MAS for both muscles and good correlation to the MTS for the MEH. Spasticity assessment based on multidimensional signals therefore provides reliable and clinically relevant measures of spasticity. Moreover, the moderate correlations of the MAS and MTS with the objective parameters further stress the added value of the instrumented measurements to detect and investigate spasticity, especially for the GAS.

To what extent is mean EMG frequency during gait a reflection of functional muscle strength in children with cerebral palsy

The aim of the current paper was to analyze the potential of the mean EMG frequency, recorded during 3D gait analysis (3DGA), for the evaluation of functional muscle strength in children with cerebral palsy (CP). As walking velocity is known to also influence EMG frequency, it was investigated to which extent the mean EMG frequency is a reflection of underlying muscle strength and/or the applied walking velocity. Surface EMG data of the lateral gastrocnemius (LGAS) and medial hamstrings (MEH) were collected during 3DGA. For each muscle, 20 CP children characterized by a weak and 20 characterized by a strong muscle (LGAS or MEH) were selected. A weak muscle was defined as a manual muscle testing score <3; a strong muscle was defined as a manual muscle testing score ≥4. Patient selection was based on the following inclusion criteria: (a) predominantly spastic type of CP (3-15 years old), (b) either (near) normal muscle strength or muscle weakness in at least one of the studied lower limb muscles, (c) no lower limb Botulinum Toxin-A treatment within 6 months prior to the 3DGA, (d) no history of lower limb surgery, and (e) high-quality noise-free EMG-data. For each muscle, twenty age-related typically developing (TD) children were included as controls. In both muscles a consistent pattern of increasing mean EMG frequency with decreasing muscle strength was observed. This was significant in the LGAS (TD versus weak CP). Walking velocity also had a significant effect on mean EMG frequency in the LGAS. Furthermore, based on R(2) and partial correlations, it could be concluded that both walking velocity and muscle strength have an impact on EMG, but the contribution of muscle strength was always higher. These findings underscore the potential of the mean EMG frequency recorded during 3DGA, for the evaluation of functional muscle strength in children with CP.

Probabilistic gait classification in children with cerebral palsy: A Bayesian approach

Three-dimensional gait analysis (3DGA) generates a wealth of highly variable data. Gait classifications help to reduce, simplify and interpret this vast amount of 3DGA data and thereby assist and facilitate clinical decision making in the treatment of CP. CP gait is often a mix of several clinically accepted distinct gait patterns. Therefore, there is a need for a classification which characterizes each CP gait by different degrees of membership for several gait patterns, which are considered by clinical experts to be highly relevant. In this respect, this paper introduces Bayesian networks (BN) as a new approach for classification of 3DGA data of the ankle and knee in children with CP. A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph. Furthermore, they provide an explicit way of introducing clinical expertise as prior knowledge to guide the BN in its analysis of the data and the underlying clinically relevant relationships. BNs also enable to classify gait on a continuum of patterns, as their outcome consists of a set of probabilistic membership values for different clinically accepted patterns. A group of 139 patients with CP was recruited and divided into a training- (n=80% of all patients) and a validation-dataset (n=20% of all patients). An average classification accuracy of 88.4% was reached. The BN of this study achieved promising accuracy rates and was found to be successful for classifying ankle and knee joint motion on a continuum of different clinically relevant gait patterns.

Children with Spastic Cerebral Palsy Experience Difficulties Adjusting Their Gait Pattern to Weight Added to the Waist, While Typically Developing Children Do Not

The prevalence of childhood overweight and obesity is increasing in the last decades, also in children with Cerebral Palsy (CP). Even though it has been established that an increase in weight can have important negative effects on gait in healthy adults and children, it has not been investigated what the effect is of an increase in body weight on the characteristics of gait in children with CP. In CP, pre and post three-dimensional gait analyses are performed to assess the effectiveness of an intervention. As a considerable amount of time can elapse between these measurements, and the effect of an alteration in the body weight is not taken into consideration, this effect of increased body weight is of specific importance. Thirty children with the predominantly spastic type of CP and 15 typically developing (TD) children were enrolled (age 3–15 years). All children underwent three-dimensional gait analysis with weight-free (baseline) and weighted (10% of the body weight added around their waist) trials. Numerous gait parameters showed a different response to the added weight for TD and CP children. TD children increased walking velocity, step- and stride length, and decreased double support duration with a slightly earlier timing of foot-off, while the opposite was found in CP. Similarly, increased ranges of motion at the pelvis (coronal plane) and hip (all planes), higher joint angular velocities at the hip and ankle, as well as increased moments and powers at the hip, knee and ankle were observed for TD children, while CP children did not change or even showed decreases in the respective measures in response to walking with added weight. Further, while TD children increased their gastrocnemius EMG amplitude during weighted walking, CP children slightly decreased their gastrocnemius EMG amplitude. As such, an increase in weight has a significant effect on the gait pattern in CP children. Clinical gait analysts should therefore take into account the negative effects of increased weight during pre–post measurements to avoid misinterpretation of treatment results. Overweight and obesity in CP should be counteracted or prevented as the increased weight has detrimental effects on the gait pattern.