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

Moran Amit; Cagri Yalcin; Jiaxi Liu; Andrew J. Skalsky; Harinath Garudadri; Tse Nga Ng

iScience (Nov 2022)

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

Moran Amit,
Cagri Yalcin,
Jiaxi Liu,
Andrew J. Skalsky,
Harinath Garudadri,
Tse Nga Ng

Affiliations

Moran Amit: Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
Cagri Yalcin: Qualcomm Institute, University of California San Diego, La Jolla, CA 92093, USA; Institute of Medical Engineering, Faculty of Electrical Engineering and Information Technology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
Jiaxi Liu: Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
Andrew J. Skalsky: Department of Orthopedic Surgery, University of California San Diego, La Jolla, CA 92093, USA; Rady Children’s Hospital, San Diego, CA 92123, USA
Harinath Garudadri: Qualcomm Institute, University of California San Diego, La Jolla, CA 92093, USA
Tse Nga Ng: Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA; Corresponding author

Journal volume & issue: Vol. 25, no. 11
p. 105286

Abstract

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Summary: 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.

Published in iScience

ISSN: 2589-0042 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science
Website: http://www.cell.com/iscience/home

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