Therapist-Assisted Rehabilitation of Visual Function and Hemianopia after Brain Injury: Intervention Study on the Effect of the Neuro Vision Technology Rehabilitation Program
Bibliographic record
Abstract
BACKGROUND: Serious and often lasting vision impairments affect 30% to 35% of people following stroke. Vision may be considered the most important sense in humans, and even smaller permanent injuries can drastically reduce quality of life. Restoration of visual field impairments occur only to a small extent during the first month after brain damage, and therefore the time window for spontaneous improvements is limited. One month after brain injury causing visual impairment, patients usually will experience chronically impaired vision and the need for compensatory vision rehabilitation is substantial. OBJECTIVE: The purpose of this study is to investigate whether rehabilitation with Neuro Vision Technology will result in a significant and lasting improvement in functional capacity in persons with chronic visual impairments after brain injury. Improving eyesight is expected to increase both physical and mental functioning, thus improving the quality of life. METHODS: This is a prospective open label trial in which participants with chronic visual field impairments are examined before and after the intervention. Participants typically suffer from stroke or traumatic brain injury and will be recruited from hospitals and The Institute for the Blind and Partially Sighted. Treatment is based on Neuro Vision Technology, which is a supervised training course, where participants are trained in compensatory techniques using specially designed equipment. Through the Neuro Vision Technology procedure, the vision problems of each individual are carefully investigated, and personal data is used to organize individual training sessions. Cognitive face-to-face assessments and self-assessed questionnaires about both life and vision quality are also applied before and after the training. RESULTS: Funding was provided in June 2017. Results are expected to be available in 2020. Sample size is calculated to 23 participants. Due to age, difficulty in transport, and the time-consuming intervention, up to 25% dropouts are expected; thus, we aim to include at least 29 participants. CONCLUSIONS: This investigation will evaluate the effects of Neuro Vision Technology therapy on compensatory vision rehabilitation. Additionally, quality of life and cognitive improvements associated to increased quality of life will be explored. TRIAL REGISTRATION: ClinicalTrials.gov NCT03160131; https://clinicaltrials.gov/ct2/show/NCT03160131 (Archived by WebCite at http://www.webcitation.org/6x3f5HnCv).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".