ReviewJMIR cardio2018
Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis.
Review in JMIR cardio, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05504096 (Calibration and Evaluation of Non-Invasive Wireless Blood Glucose Monitoring), which is not on this map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Calibration and Evaluation of Non-Invasive Wireless Blood Glucose Monitoring
Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.
- Conducting clinical trials in heart failure during (and after) the COVID-19 pandemic: an Expert Consensus Position Paper from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC).European heart journal · 2020Guideline
- Comparative assessment of healthy tissue oxygenation using near-infrared imaging, transcutaneous oxygen measurement, and plethysmography.Scientific reports · 2025Trial
- Validation of smartphone-based heart rate variability measurement against ECG in patients with depression.European archives of psychiatry and clinical neuroscience · 2026Article
- Association and Agreement of Contact-Based Smartphone Photoplethysmography Compared With Electrocardiography: Protocol for a Systematic Review and Meta-Analysis.JMIR research protocols · 2026Article
- Multimodal pulse oximeters to support the integrated management of childhood illnesses: A usability and diagnostic accuracy assessment from a multi-country hybrid type 2 study.PLOS global public health · 2026Article
- Physiologically Interpretable Photoplethysmography Features Associated With Peripheral Artery Disease.IEEE open journal of engineering in medicine and biology · 2026Article
- Challenges and standardisation strategies for sensor-based data collection for digital phenotyping.Communications medicine · 2025Review
- Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors.JMIR mHealth and uHealth · 2024Article
- Advances and Opportunities of Mobile Health in the Postpandemic Era: Smartphonization of Wearable Devices and Wearable Deviceization of Smartphones.JMIR mHealth and uHealth · 2024Article
- Predicting cardiovascular disease risk using photoplethysmography and deep learning.PLOS global public health · 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
- Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data.Journal of personalized medicine · 2023Review
- The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review.JMIR mental health · 2023Article
- The electrocardiogram on the wrist: a frightening experience to the untrained consumer: a case report.Journal of medical case reports · 2023Article
- Validating cuffless continuous blood pressure monitoring devices.Cardiovascular digital health journal · 2023Review
- A calibration method for smartphone camera photophlethysmography.Frontiers in digital health · 2023Article
- From biorepositories to data repositories: Open-access resources accelerate early R&D and validation of equitable diagnostic tools.PLOS global public health · 2023Article
- Prospective validation of smartphone-based heart rate and respiratory rate measurement algorithms.Communications medicine · 2022Article
- Smartphone-Based VO2max Measurement With Heart Snapshot in Clinical and Real-world Settings With a Diverse Population: Validation Study.JMIR mHealth and uHealth · 2021Article
- A Heart Rate Monitoring App (FibriCheck) for Atrial Fibrillation in General Practice: Pilot Usability Study.JMIR formative research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSmartphone ownership is rising at a stunning rate. Moreover, smartphones prove to be suitable for use in health care due to their availability, portability, user-friendliness, relatively low price, wireless connectivity, far-reaching computing capabilities, and comprehensive memory. To measure vital signs, smartphones are often connected to a mobile sensor or a medical device. However, by using the white light-emitting diode as light source and the phone camera as photodetector, a smartphone could be used to perform photoplethysmography (PPG), enabling the assessment of vital signs.
objectiveThe objective of this meta-analysis was to evaluate the available evidence on the use of smartphone apps to measure heart rate by performing PPG in comparison with a validated method.
methodsPubMed and ISI Web of Knowledge were searched for relevant studies published between January 1, 2009 and December 7, 2016. The reference lists of included studies were hand-searched to find additional eligible studies. Critical Appraisal Skills Programme (CASP) Diagnostic Test Study checklist and some extra items were used for quality assessment. A fixed effects model of the mean difference and a random effects model of Pearson correlation coefficient were applied to pool the outcomes of the studies.
resultsIn total, 14 studies were included. The pooled result showed no significant difference between heart rate measurements with a smartphone and a validated method (mean difference -0.32; 99% CI -1.24 to 0.60; P=.37). In adults, the Pearson correlation coefficient of the relation between heart rate measurement with a smartphone and a validated method was always ≥.90. In children, the results varied depending on measuring point and heart rate. The pooled result showed a strong correlation that was significant (correlation coefficient .951; 95% CI 0.906-0.975; P<.001). The reported limits of agreement showed good agreement between a smartphone and a validated method. There was a moderately strong significant negative correlation between the year of publication of the included studies and the mean difference (r=-.69; P<.001).
conclusionsSmartphone apps measuring heart rate by performing PPG appear to agree with a validated method in an adult population during resting sinus rhythm. In a pediatric population, the use of these apps is currently not validated.
Indexed as
Identifiers
What OpenQuestion holds
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.