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.

The gap between clinical gaze and systematic assessment of movement disorders after stroke.

BACKGROUND: Movement disorders after stroke are still captured by clinical gaze and translated to ordinal scores of low resolution. There is a clear need for objective quantification, with outcome measures related to pathophysiological background. Neural and non-neural contributors to joint behavior should be separated using different measurement conditions (tasks) and standardized input signals (force, position and velocity). METHODS: We reviewed recent literature for the application of biomechanical and/or elektromyographical (EMG) outcome measures under various measurement conditions in clinical research. RESULTS: Since 2005, 36 articles described the use of biomechanical and/or EMG outcome measures to quantify post-stroke movement disorder. Nineteen of the articles strived to separate neural and non-neural components. Only 6 of the articles measured biomechanical and EMG outcome measures simultaneously, while applying active and passive tasks and multiple velocities. CONCLUSION: The distinction between neural and non-neural components to separately assess paresis, stiffness and muscle overactivity is not commonplace yet, while a large gap is to be bridged to attain reproducible and comparable results. Pathophysiologically clear concepts, substantiated with a comprehensive and concise measuring protocol will help professionals to identify and treat limiting factors in movement capabilities of post-stroke patients.