ADDRESSING THE GAPS IN ASSESSMENT AND TREATMENT OF THE UPPER EXTREMITY IN REHABILITATION OF INDIVIDUALS WITH NEUROLOGICAL CONDITIONS
Bibliographic record
Abstract
Regaining upper extremity function is critical following stroke and spinal cord injury (SCI). The objectives of this thesis were to develop and assess the psychometric properties of a 3D printed version of an upper extremity outcome assessment tool called the Toronto Rehabilitation Institute-Hand Function Test (TRI-HFT) and to assess the feasibility of stimulating interscapular muscles using transcutaneous functional electrical stimulation (FES). The first study explored the feasibility of 3D printing the original TRI-HFT objects and assessed its inter and intra-rater reliability and convergent validity in chronic stroke. The second study focused on assessing its psychometric properties in the sub-acute and chronic SCI populations. We hypothesized that the TRI-HFT could be 3D printed and that the 3D printed test would have high reliability and validity in stroke and SCI populations. In the third study I explored the feasibility and benefits of stimulating the Lower Trapezius (LT), Serratus Anterior (SA) and Upper Trapezius (UT) along with Anterior Deltoid during forward flexion and along with Middle Deltoid during abduction in able-bodied individuals. The underlying hypothesis was that it would result in an increased range and more natural reaching movement. In the first and second study we found that all objects of the TRI-HFT could be successfully 3D printed with an error margin of less than 10% except for the Paper and the Sponge objects. The 3D TRI-HFT showed high inter and intra-rater reliability in stroke and SCI.The 3D TRI-HFT showed strong criterion validity when compared to the Graded Redefined Assessment of Strength, Sensibility and Prehension test in the SCI population. The 3D TRI-HFT showed moderate to strong construct validity when compared to the Chedoke-McMaster Stroke Assessment-Arm and Hand and the Fugl Meyer Assessment-Hand in chronic stroke. In the third study, the LT, SA and UT could be successfully stimulated using surface FES. The maximum reach in abduction for FES of middle deltoid along with the interscapular muscles was 51.77°±17.54° compared to FES for middle deltoid alone which was 43.76°±15.32°. This work essentially builds on the current state of assessment and FES treatment of the upper extremity in the rehabilitation domain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".