Eye tracking communication devices in amyotrophic lateral sclerosis: Impact on disability and quality of life
Bibliographic record
Abstract
People with amyotrophic lateral sclerosis (PwALS) show progressive loss of voluntary muscle strength. In advanced disease, motor and phonatory impairments seriously hinder the patient's interpersonal communication. High-tech devices such as eye tracking communication devices (ETCDs) are used to aid communication in the later stages of ALS. We sought to evaluate the effect of ETCDs on patient disability, quality of life (QoL), and user satisfaction, in a group of 35 regular ETCD users in late-stage ALS with tetraplegia and anarthria. The following scales were administered: 1) the Individually Prioritized Problem Assessment (IPPA) scale, in three conditions: without device, with ETCD and, when applicable, with an Eye Transfer (ETRAN) board; 2) the Psychosocial Impact of Assistive Devices Scale (PIADS); and 3) the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0). With ETRAN, IPPA showed an increase in communicative abilities with respect to the condition without device, but ETCD produced a further significant increase. PIADS evidenced a large increase of QoL, and QUEST 2.0 showed high user satisfaction with ETCD use. In conclusion, ETCDs should be considered in late-stage ALS with tetraplegia and anarthria, since in these patients they can reduce communication disability and improve QoL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".