Development of Modified Ride-On-Cars for Children with Mobility Impairments
Bibliographic record
Abstract
Introduction: The ability to move independently is an integral part of a child's development. Children with motor impairments often experience significant challenges with moving independently, resulting in expensive powered wheelchairs being purchased or having caregivers push them in strollers or wheelchairs. The purpose of this research is to adapt motorized ride-on-cars to enable children with motor impairments to explore their environment independently. Engineers, physiotherapists, and occupational therapists co-designed customized ride-on-cars with 10 children and their caregivers to support each child’s individual needs. Methods: Physiotherapists and occupational therapists led an initial diagnostic session to assess each child’s clinical needs. The engineers then brainstormed and implemented solutions. On the final day of testing, physiotherapists and occupational therapists conducted one further clinical assessment and made final changes. This process was repeated for 10 children ages 1-3 years old who had been identified as having mobility impairment. Results: The final cars were designed to minimize cost, weight, and size while prioritizing each child’s ability to operate the car independently and safely. The main modifications included replacing the original gas pedal with an assistive switch and constructing a support frame to ensure the child’s safety. Additional modifications such as adding a steering T-bar, adding LED lights, and varying the switch location were also implemented for specific children. Each modified car was tested to ensure client safety and car durability. Client feedback was positive, and caregivers expressed how their modified car will increase mobility for their child. Conclusions: The results from this iterative co-design process emphasize the importance of team assessment and implementation when creating assistive devices. It shows that modifying standard off-the-shelf toys to the specific needs of children with disabilities can be successful and improve their quality of life.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".