Personalizing Assessment of Motor Impairment for Stroke Rehabilitation
| dc.contributor.advisor | O'Malley, Marcia K | en_US |
| dc.creator | Rice, Elijah | en_US |
| dc.date.accessioned | 2025-05-30T21:05:08Z | en_US |
| dc.date.created | 2025-05 | en_US |
| dc.date.issued | 2025-04-25 | en_US |
| dc.date.submitted | May 2025 | en_US |
| dc.date.updated | 2025-05-30T21:05:08Z | en_US |
| dc.description.abstract | Motor impairment assessments of stroke are used by therapists to track recovery and prescribe treatment protocols that optimize rehabilitative outcomes. For outpatient-based stroke rehabilitation, lengthy administration times of traditional clinical assessments limit associated benefits and preclude additional therapist-directed rehabilitation that improves outcomes. Robotic and sensor-instrumented systems provide an objective method of assessment that offers additional resolution via measurement of kinematic quantities of movement. Prior research has validated assessment automation with such systems, but has neglected automating assessment using systems that are independently usable by stroke survivors. In this thesis, we analyze the effect of range of motion on a common assessment metric, movement smoothness, which gauges motor coordination as a facet of motor impairment. Based on our findings, we present guidelines for implementation of movement smoothness assessment that preserves task construct validity. A novel device, the FlexWrist, is presented as a usability-focused, glove-based flex sensor system for recording home exercise movement of stroke survivors' hemiparetic wrist and hand. | en_US |
| dc.embargo.lift | 2026-05-01 | en_US |
| dc.embargo.terms | 2026-05-01 | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/118524 | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Stroke | en_US |
| dc.subject | Exoskeleton | en_US |
| dc.subject | Wearable Devices | en_US |
| dc.title | Personalizing Assessment of Motor Impairment for Stroke Rehabilitation | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Mechanical Engineering | en_US |
| thesis.degree.discipline | Mechanical Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science | en_US |