Challenges and Opportunities of the Human-Centered Design Approach: Case Study Development of an Assistive Device for the Navigation of Persons With Visual Impairment
Bibliographic record
Abstract
BACKGROUND: Visual impairment (VI) significantly impacts quality of life, particularly in autonomous pedestrian navigation. Limitations in independent navigation lead to frustration, diminished confidence, and risks to bodily integrity for individuals with VI. In Colombia, the pilot country of this study, approximately 2 million people live with some form of visual disability. Globally, only 1 in 10 people requiring assistive devices have access to them, with factors such as deficient product design stemming from limited knowledge of user expectations, local needs, and environmental constraints, posing significant challenges, particularly in low- and middle-income countries. OBJECTIVE: We aimed to evaluate the feasibility and limitations of applying the human-centered design (HCD) principles outlined by the International Organization for Standardization (ISO) 9241-210:2019 standard in assistive technology (AT) development for individuals with VI in Colombia. METHODS: We developed a prototype navigation device using the HCD principles, emphasizing a thorough analysis of user needs and environmental contexts. The project leveraged multidisciplinary collaboration to address challenges associated with user engagement and design adaptability while managing legal and bureaucratic constraints. The navigation system integrates artificial intelligence algorithms, specifically developed by the research team as part of this work, to enhance its adaptability and responsiveness to diverse environments. The development process featured iterative prototyping cycles, incorporating user feedback at each stage, all within the boundaries of applicable regulatory frameworks. RESULTS: The development and evaluation of the initial prototype highlighted both the feasibility and key limitations of applying the ISO 9241-210:2019 HCD principles in AT for individuals with VI in the Colombian context. The prototype met several user-defined expectations by prioritizing affordability; extended battery life; autonomy in internet-constrained environments; and improved ergonomics, concealability, aesthetics, and obstacle detection. These achievements demonstrated the potential of HCD to guide context-sensitive innovation. However, the process also revealed significant barriers: limited legal and procedural clarity for engaging users in design phases, difficulties navigating ethics committees, and a lack of practical guidance within the ISO standard itself. These constraints, compounded by challenges in interdisciplinary collaboration, limited the depth and adaptability of user involvement across development stages. CONCLUSIONS: Implementing HCD principles in AT development shows promise for creating effective and affordable solutions tailored to user needs and contexts. However, legislative and methodological barriers must be addressed to fully realize HCD's potential. Future efforts should focus on aligning research methodologies with hardware and software development practices while integrating legislative frameworks to enhance the accessibility and effectiveness of AT innovations.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".