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Laying the Groundwork for More Personalized Rehabilitation Therapies After Stroke

EVENT: 
Seminar
Who Should Attend: 
Researchers
Event Flyer: 
PDF icon busza_9-19-23_.pdf

Speakers

Assistant Professor of Neurology, Neuroscience, Neurosurgery, and Physical Medicine and Rehabilitation

Abstract

Stroke is the leading cause of adult disability in the US. Of those who receive rehabilitation therapy, approximately 40% have chronically impaired motor function of the upper extremity, contributing to decreased quality of life and increased societal burden of stroke. Currently, clinical rehabilitation focuses on repetitive motor exercises, but interventions are not adapted to individual stroke lesion location or predicted trajectory of recovery. Prior studies have identified distinct impairments of motor control that contribute to poor function at the chronic stage and likely depend on neuroanatomical structures damaged by the stroke, but the details of what contributes to development of these impairments and timing of when they emerge remains unclear. In order to create optimal rehabilitation strategies and maximize each individual patient’s rehabilitation potential, we need better methods for predicting and treating these motor control impairments. In this talk, I will describe several projects in my lab including (1) a longitudinal study using an electromyographic computer interface to study motor impairments in patients with arm impairment after stroke (2) using gyroscope and accelerometer data from wearable sensors to categorize and quantify rehabilitation dose and (3) adaptation of a VR and finger tracking system to study proprioception in patients with cerebellar damage due to stroke. By better understanding the relationship between stroke location, rehabilitation practice, and recovery, we ultimately hope to contribute towards the development of personalized and more effective therapies for patients with disability from stroke.

Publications

Noah Balestra, Gaurav Sharma, Linda M Riek, Ania Busza
Automatic Identification of Upper Extremity Rehabilitation Exercise Type and Dose Using Body-Worn Sensors and Machine Learning: A Pilot Study
Digit Biomark . 2021 Jul 2;5(2):158-166. doi: 10.1159/000516619. eCollection 2021 May-Aug.
E L Isenstein, T Waz, A LoPrete, Y Hernandez, E J Knight, A Busza, D Tadin
Rapid assessment of hand reaching using virtual reality and application in cerebellar stroke
PLoS One . 2022 Sep 29;17(9):e0275220. doi: 10.1371/journal.pone.0275220. eCollection 2022.

When

Tuesday, September 19, 2023 - 12:30pm

Where

Conference Room: 
Billings Building – Rosedale

More Information

Darlene White