Efficacy and patients’ satisfaction with the ORCAM MyEye device among visually impaired people: a multicenter study
Bibliographic record
Abstract
Abstract Objective To evaluate usability of and satisfaction with OrCam MyEye, a finger-size wearable assistive technology device for visually impaired during real-world tasks. Methods This prospective multicenter study was conducted on visually impaired people recruited from 5 vision rehabilitation centers. Patients performed real-world tasks such as near and distance reading, money handling, colour identification and faces recognition in 2 different scenarios: without using any low vision aid and with OrCam. System Usability Scale (SUS), Patient’s Global Impression of Change (PGIC), the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) and the Psychosocial Impact of Assistive Devices Scale (PIADS) were administered after the use of the OrCam device. Results Among the 100 participants, use of OrCam MyEye device improved many daily-living tasks (F = 1.67, P < .05), and in particular reading and face recognition. Multivariate logistic regression showed that age and visual field defect explained 89% of the variation in efficacy of the device. Nearly half (45%) of the participants indicated a positive rating with the SUS. The PGIC rates showed a minimal improvement with a mean score of 4.2 (SD:1.8). The most highlighted parameter with the QUEST 2.0 test was “ease of use” in 58% (48 subjects). The PIADS indicator showed that the device positively impacted on the daily-living tasks of users (r2 = 0.72, P < .05). Regression modelling demonstrated a good relation between the questionnaires scores and demographic, disease and visual factors (P < .05). Conclusions OrCam MyEye allowed visually impaired people to read, handle money and face recognition independently. This device may offer to these subjects to be independent.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".