A questionnaire for the evaluation of physical assistive devices (QUEAD): Testing usability and acceptance in physical human-robot interaction
Bibliographic record
Abstract
Many novel physical assistance devices are beginning to incorporate intelligent robotic systems and mechatronic components. In terms of a human-centered design it is crucial to assess the perceived subjective usability and acceptance of these systems. A questionnaire was thus designed to evaluate novel physically assisting devices in order to support developers in their design decisions as well as users during individualizing of their assistive devices. Two studies (m = 9, n2 = 21), using two different devices, were conducted to analyze objectivity, reliability, and validity. The results show an overall high internal consistency (Cronbach's α > 0.8), which indicates reliability and applicability of the QUEAD. Criterion validity was tested applying correlations with established objective measures for efficiency (time to task completion), effectivity (errors and collisions), and commitment (mean force). Construct validity was applied using a proposed model and correlations to verify convergence. The results show that the QUEAD is able to assess perceived usability and acceptance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".