ArticleDigital health
Remote photoplethysmography for cardiorespiratory self-monitoring: A qualitative study of usability, convenience, and patient confidence.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Remote photoplethysmography (rPPG) is a non-contact method for measuring physiological parameters using smartphone cameras. While the potential for scalable self-monitoring is promising, little is known about its usability and acceptability among patients with chronic cardiac and respiratory conditions. Objective: This qualitative study explored the user experiences of a smartphone-based rPPG app (Vitacam) to assess its usability, acceptability, and perceived utility in real-world conditions. Methods: Seven adults with chronic heart or respiratory conditions used the app at home over one week. Semi-structured interviews were conducted and explored using reflexive thematic analysis. Results: Participants appreciated the app's simplicity, real-time guidance, and convenience. Key barriers included environmental sensitivity (e.g. lighting), technical limitations, vague error messaging, and lack of clinical integration. Users valued basic self-monitoring features but expressed concerns about accuracy and interpretation, especially for complex conditions like atrial fibrillation. Conclusions: rPPG via smartphone is a promising, low-burden option for basic self-monitoring in chronic disease management. To increase adoption and utility, future iterations should improve feedback clarity, algorithm sensitivity, and integration with clinical systems. These developments could enhance user trust, accuracy, and long-term engagement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.