Inclusive Contactless Monitoring – Perspectives of Older Adults from Diverse Backgrounds (Preprint)
Bibliographic record
Abstract
Background: As Canada's population ages, accessible tools for chronic health monitoring are increasingly needed. Traditional and contact-based devices pose barriers for underserved populations due to cost, maintenance, and usability. Contactless sensing technologies offer a promising alternative, but equitable development requires inclusive engagement and diverse data collection. Objective: This study aimed, first, to gather perspectives from culturally and health-diverse older adults on innovative contactless vital sign monitoring technology and, second, to build on a diverse dataset for developing and testing the contactless sensing software VitalSeer by the National Research Council of Canada. Methods: A mixed methods study was conducted with older adults from diverse backgrounds across 3 sites. Participants were asked to respond to a questionnaire that had closed- and open-ended questions regarding their perspectives on contactless sensing technology. Video and reference vital sign data were collected from each participant using a portable system designed specifically for gathering controlled data. Results: We collected data from 48 participants (mean age 70, SD 8 years), of whom 98% (n=47) expressed a positive perception of the usefulness of a contactless sensing system. We also identified four themes from the qualitative analysis of the open-ended questions: (1) perceived value-system potential and clinical relevance; (2) ease of use-noninvasiveness and comfort; (3) trust and transparency-data security and clarity of design; and (4) inclusion and improvement-accessibility, functionality, and feature expansion. Finally, the collected data, 288 minutes of concurrent video and reference vital sign data, will be used to test and enhance contactless sensing software for diverse older adult populations. Conclusions: This work advances the goal of inclusive medical device research and development. It highlights the potential for contactless sensing to be adopted to support independent living for older, diverse adults. Research is ongoing to adapt the technology for widespread adoption.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".