ArticleSensors (Basel, Switzerland)2020
Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Frequency-Preserving Readout Design and Error Characterization for CWT-Based rPPG Heart-Rate Estimation.Sensors (Basel, Switzerland) · 2026Article
- Assessing Mental Health and Emotional States by Using Smartphone Photoplethysmography-Based Digital Pulse Waveform Analysis: Cross-Sectional Observational Study.JMIR mHealth and uHealth · 2026Observational
- Feasibility of an AI-Enabled Smart Mirror Integrating MA-rPPG, Facial Affect, and Conversational Guidance in Realtime.Sensors (Basel, Switzerland) · 2025Article
- A finger on the pulse of cardiovascular health: estimating blood pressure with smartphone photoplethysmography-based pulse waveform analysis.Biomedical engineering online · 2025Article
- Comparative Assessment of Multimodal Sensor Data Quality Collected Using Android and iOS Smartphones in Real-World Settings.Sensors (Basel, Switzerland) · 2024Article
- Your blush gives you away: detecting hidden mental states with remote photoplethysmography and thermal imaging.PeerJ. Computer science · 2024Article
- Validity of resting heart rate derived from contact-based smartphone photoplethysmography compared with electrocardiography: a scoping review and checklist for optimal acquisition and reporting.Frontiers in digital health · 2024Article
- Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?Bioengineering (Basel, Switzerland) · 2023Article
- Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview.Frontiers in physiology · 2022Review
- The Vagal Autonomic Pathway of COVID-19 at the Crossroad of Alzheimer's Disease and Aging: A Review of Knowledge.Journal of Alzheimer's disease reports · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland-Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.
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Registered trials
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