Hand Extension Robot Orthosis (HERO) Grip Glove: enabling independence amongst persons with severe hand impairments after stroke
Bibliographic record
Abstract
Abstract Background The Hand Extension Robot Orthosis (HERO) Grip Glove was iteratively designed to meet requests from therapists and persons after a stroke who have severe hand impairment to create a device that extends all five fingers, enhances grip strength and is portable, lightweight, easy to put on, comfortable and affordable. Methods Eleven persons who have minimal or no active finger extension (Chedoke McMaster Stage of Hand 1–4) post-stroke were recruited to evaluate how well they could perform activities of daily living and finger function assessments with and without wearing the HERO Grip Glove. Results The 11 participants showed statistically significant improvements ( p < 0.01), while wearing the HERO Grip Glove, in the water bottle grasp and manipulation task (increase of 2.3 points, SD 1.2, scored using the Chedoke Hand and Arm Inventory scale from 1 to 7) and in index finger extension (increase of 147 o , SD 44) and range of motion (increase of 145 o , SD 36). The HERO Grip Glove provided 12.7 N (SD 8.9 N) of grip force and 11.0 N (SD 4.8) of pinch force to their affected hands, which enabled those without grip strength to grasp and manipulate blocks, a fork and a water bottle, as well as write with a pen. The participants were ‘ more or less satisfied’ with the HERO Grip Glove as an assistive device (average of 3.3 out of 5 on the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 Scale). The highest satisfaction scores were given for safety and security (4.6) and ease of use (3.8) and the lowest satisfaction scores were given for ease of donning (2.3), which required under 5 min with assistance. The most common requests were for greater grip strength and a smaller glove size for small hands. Conclusions The HERO Grip Glove is a safe and effective tool for enabling persons with a stroke that have severe hand impairment to incorporate their affected hand into activities of daily living, which may motivate greater use of the affected upper extremity in daily life to stimulate neuromuscular recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".