Integrating user perceptions of socio-emotional aspects in wheelchair design: A pilot study using Kansei Engineering
Bibliographic record
Abstract
Comfort in wheelchair use is influenced not only by ergonomic factors but also by socio-emotional aspects that shape the user's experience. This study aims to explore how socio-emotional factors can be integrated into the representational aspects of wheelchairs. A cross-sectional study was conducted with 37 wheelchair users using Kansei Engineering methods. Participants provided data on semantic and product spaces through a questionnaire covering demographics, aesthetic importance, symbolic importance, and social communication challenges. They also rated four distinct wheelchairs using Kansei words (KWs). Then, Quality Function Deployment (QFD) linked users' insights to specific wheelchair properties. Aesthetic (76%) and Symbolic (56%) importance, as well as age, were significantly associated with social communication challenges (57%) (p < 0.05). Age was significantly associated with both Aesthetic and Symbolic importance, while gender was only linked to Aesthetic importance (p < 0.05). Descriptive analysis indicated that advanced manual and powered wheelchair designs scored higher than conventional ones. Accordingly, three key components were identified for both categories, with the highest loadings of KW in each. QFD results prioritized adjustable frame design, with 8.61% for manual and 10.44% for powered models, as key to enhancing socio-emotional aspects. Beyond analyzing the dynamics of aesthetics, symbolism, and social challenges, this study uncovers users' perceptions of wheelchair design characteristics. It proposes principal components to guide designers and includes computational analysis to connect these insights with wheelchair properties, aspects often overlooked in assistive device literature. However, redesign effectiveness also hinges on understanding social factors like stereotypes, and wheelchair-related metaphors. • The aesthetic and symbolic meaning of wheelchairs, along with age, is significantly related to experiences of social communication challenges. • While age is a significant factor associated with perceptions of the aesthetic and symbolic importance of wheelchairs, gender is only linked to aesthetic importance. • The socio-emotional design of advanced wheelchairs is guided by three key components with the highest KW loadings. For AMW, these include: 1) Secure Navigation with Advanced Representation, 2) Manoeuvrability with Pleasant Social Representation, and 3) Reliability and Respectful Social Interaction. For APW, the components are: 1) Self-Reliance and Pleasant Social Representation, 2) Self-Confidence with Social Respect, and Flexibility in Mobility. 3) Together, these factors encourage designs that enhance the social and emotional polish of advanced wheelchairs. • The QFD model identifies optimizing adjustable frame design as the top priority for enhancing socio-emotional aspects in both manual and powered wheelchairs. • KE identifies essential steps for wheelchairs to meet WUs' socio-emotional needs, while redesign must also address societal perceptions and stereotypes.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".