Parameters that integrated electrophysiological signals with joint movement characteristics were best able to quantify spasticity .
There were conflicting results regarding biomechanical-based parameters that quantify the resistance to passive stretch .
AIM The first aim of this study was to systematic ally review and critically assess manually controlled instrumented spasticity assessment methods that combine multidimensional signals .
The second aim was to extract a set of quantified parameters that are psychometrically sound to assess spasticity in a clinical setting .
Comprehensive quantification of the spastic catch in children with cerebral palsy.
In clinical setting s , the spastic catch is judged subjectively . This study assessed the psychometric properties of objective parameters that define and quantify the severity of the spastic catch in children with cerebral palsy ( CP ) . A convenience sample of children with spastic CP ( N=46 ; age range : 4 - 16 years ) underwent objective spasticity assessment s. High velocity , passive stretches were applied to the gastrocnemius ( GAS ) and medial hamstrings ( MEH ) .  Muscle activity was measured with surface electromyography ( sEMG ) , joint angle characteristics using inertial sensors and reactive torque using a force sensor . To test reliability , a group of 12 children were retested after an average of 13 ± 9 days . The angle of spastic catch ( AOC ) was estimated by three biomechanical definitions : joint angle at ( 1 ) maximum angular deceleration ; ( 2 ) maximum change in torque ; and ( 3 ) minimum power . Each definition was checked for reliability and validity . Construct and clinical validity were evaluated by correlating each AOC definition to the averaged root mean square envelope of EMG ( RMS-EMG ) and the Modified Tardieu Scale ( MTS ) . Severity categories were created based on selected parameters to establish face validity . All definitions showed moderate to high reliability . Significant correlations were found between AOC3 and the MTS of both muscles and the RMS-EMG of the MEH , though coefficients were only weak . AOC3 further distinguished between mild , moderate and severe catches . Objective parameters can define and quantify the severity of the spastic catch in children with CP . However , a comprehensive underst and ing requires the integration of both biomechanical and RMS-EMG data
Parameters that integrated electrophysiological signals with joint movement characteristics were best able to quantify spasticity .
There were conflicting results regarding biomechanical-based parameters that quantify the resistance to passive stretch .
AIM The first aim of this study was to systematic ally review and critically assess manually controlled instrumented spasticity assessment methods that combine multidimensional signals .
The second aim was to extract a set of quantified parameters that are psychometrically sound to assess spasticity in a clinical setting .