Multimodal assessment of spasticity using a point-of-care instrumented glove to separate neural and biomechanical contributions

Accurate assessment of spasticity is crucial for physicians to select the most suitable treatment for patients. However, the current clinical practice standard is limited by imprecise assessment scales relying on perception. Here, we equipped the clinician with a portable, multimodal sensor glove to shift bedside evaluations from subjective perception to objective measurements. The measurements were correlated with biomechanical properties of muscles and revealed dynamic characteristics of spasticity, including catch symptoms and velocity-dependent resistance. Using the biomechanical data, a radar metric was developed for ranking severity in spastic knees and elbows. The continuous monitoring results during anesthesia induction enable the separation of neural and structural contributions to spasticity in 21 patients. This work delineated effects of reflex excitations from structural abnormalities, to classify underlying causes of spasticity that will inform treatment decisions for evidence-based patient care.