Assistive robotic arm: Evaluation of the performance of intelligent algorithms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
People with upper body disabilities may be limited in their activities of daily living. Robotic arms, such as JACO, are assistive devices that could improve their abilities, independent living, and social participation. However, performing complex tasks with JACO can be time-consuming or tedious. Therefore, some advanced functionalities have been developed to enhance the performance of users. The main objective of this study is to evaluate the performance, in terms of ease of use, task completion time, and participants' perception of usability, of three new algorithms applied to the JACO robotic arm: (1) predefined position, (2) fluidity filter, and (3) drinking mode. The secondary objective is to evaluate differences in performance variables between proportional and non-proportional control modes. Fourteen participants with upper body disabilities completed various tasks with and without these functionalities. Using JACO with the algorithms led to a significant decrease of up to 72% in task completion time and improvements of 2.3 and 2.9 on a 7-point Likert scale for perceived ease of use and usability, respectively. There was no significant difference between control modes. Our results demonstrate that algorithms could produce significant improvements in performing daily living activities.
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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 | 0.000 | 0.000 |
| 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 it