Differentiation between non-neural and neural contributors to ankle joint stiffness in cerebral palsy

Background Spastic paresis in cerebral palsy (CP) is characterized by increased joint stiffness that may be of neural origin, i.e. improper muscle activation caused by e.g. hyperreflexia or non-neural origin, i.e. altered tissue viscoelastic properties (clinically: “spasticity” vs. “contracture”). Differentiation between these components is hard to achieve by common manual tests. We applied an assessment instrument to obtain quantitative measures of neural and non-neural contributions to ankle joint stiffness in CP. Methods Twenty-three adolescents with CP and eleven healthy subjects were seated with their foot fixated to an electrically powered single axis footplate. Passive ramp-and-hold rotations were applied over full ankle range of motion (RoM) at low and high velocities. Subject specific tissue stiffness, viscosity and reflexive torque were estimated from ankle angle, torque and triceps surae EMG activity using a neuromuscular model. Results In CP, triceps surae reflexive torque was on average 5.7 times larger (p?=?.002) and tissue stiffness 2.1 times larger (p?=?.018) compared to controls. High tissue stiffness was associated with reduced RoM (p?<?.001). Ratio between neural and non-neural contributors varied substantially within adolescents with CP. Significant associations of SPAT (spasticity test) score with both tissue stiffness and reflexive torque show agreement with clinical phenotype. Conclusions Using an instrumented and model based approach, increased joint stiffness in CP could be mainly attributed to higher reflexive torque compared to control subjects. Ratios between contributors varied substantially within adolescents with CP. Quantitative differentiation of neural and non-neural stiffness contributors in CP allows for assessment of individual patient characteristics and tailoring of therapy.Biomechanical EngineeringMechanical, Maritime and Materials Engineerin

Estimation of tissue stiffness, reflex activity, optimal muscle length and slack length in stroke patients using an electromyography driven antagonistic wrist model

Background: About half of all chronic stroke patients experience loss of arm function coinciding with increased stiffness, reduced range of motion and a flexed wrist due to a change in neural and/or structural tissue properties. Quantitative assessment of these changes is of clinical importance, yet not trivial. The goal of this study was to quantify the neural and structural properties contributing to wrist joint stiffness and to compare these properties between healthy subjects and stroke patients. Methods: Stroke patients (n = 32) and healthy volunteers (n = 14) were measured using ramp-and-hold rotations applied to the wrist joint by a haptic manipulator. Neural (reflexive torque) and structural (connective tissue stiffness and slack lengths and (contractile) optimal muscle lengths) parameters were estimated using an electromyography driven antagonistic wrist model. Kruskal-Wallis analysis with multiple comparisons was used to compare results between healthy subjects, stroke patients with modified Ashworth score of zero and stroke patients with modified Ashworth score of one or more. Findings: Stroke patients with modified Ashworth score of one or more differed from healthy controls (P < 0.05) by increased tissue stiffness, increased reflexive torque, decreased optimal muscle length and decreased slack length of connective tissue of the flexor muscles. Interpretation: Non-invasive quantitative analysis, including estimation of optimal muscle lengths, enables to identify neural and non-neural changes in chronic stroke patients. Monitoring these changes in time is important to understand the recovery process and to optimize treatment

Early shortening of wrist flexor muscles coincides with poor recovery after stroke

Background. The mechanism and time course of increased wrist joint stiffness poststroke and clinically observed wrist flexion deformity is still not well understood. The components contributing to increased joint stiffness are of neural reflexive and peripheral tissue origin and quantified by reflexive torque and muscle slack length and stiffness coefficient parameters. Objective. To investigate the time course of the components contributing to wrist joint stiffness during the first 26 weeks poststroke in a group of patients, stratified by prognosis and functional recovery of the upper extremity. Methods. A total of 36 stroke patients were measured on 8 occasions within the first 26 weeks poststroke using ramp-and-hold rotations applied to the wrist joint by a robot manipulator. Neural reflexive and peripheral tissue components were estimated using an electromyography-driven antagonistic wrist model. Outcome was compared between groups cross-sectionally at 26 weeks poststroke and development over time was analyzed longitudinally. Results. At 26 weeks poststroke, patients with poor recovery (Action Research Arm Test [ARAT] ≤9 points) showed a higher predicted reflexive torque of the flexors (P &lt;.001) and reduced predicted slack length (P &lt;.001) indicating shortened muscles contributing to higher peripheral tissue stiffness (P &lt;.001), compared with patients with good recovery (ARAT ≥10 points). Significant differences in peripheral tissue stiffness between groups could be identified around weeks 4 and 5; for neural reflexive stiffness, this was the case around week 12. Conclusions. We found onset of peripheral tissue stiffness to precede neural reflexive stiffness. Temporal identification of components contributing to joint stiffness after stroke may prompt longitudinal interventional studies to further evaluate and eventually prevent these phenomena.Biomechatronics & Human-Machine Contro

Supplementary_Table_A_longitudinal – Supplemental material for Early Shortening of Wrist Flexor Muscles Coincides With Poor Recovery After Stroke

<p>Supplemental material, Supplementary_Table_A_longitudinal for Early Shortening of Wrist Flexor Muscles Coincides With Poor Recovery After Stroke by Karin L. de Gooijer-van de Groep, Jurriaan H. de Groot, Hanneke van der Krogt, Erwin de Vlugt, J. Hans Arendzen and Carel G. M. Meskers in Neurorehabilitation and Neural Repair</p