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

• Contributors to wrist joint stiffness were quantified using an instrumented approach.
• Flexor optimal muscle length and slack length were decreased in stroke patients.
• Tissue stiffness and reflexive torque were increased in stroke patients.
• The quantitative method can be applied for therapy prescription and follow-up.

BackgroundAbout 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.MethodsStroke 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.FindingsStroke 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.InterpretationNon-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.