ArticleBiosensors2022
A Real-Time PPG Peak Detection Method for Accurate Determination of Heart Rate during Sinus Rhythm and Cardiac Arrhythmia.
Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Regional tissue perfusion index (RTPI): a new optical-based metric for quantifying regional tissue perfusion.Journal of clinical monitoring and computing · 2026Article
- Multimodal Detection of Pain and Anticipation Anxiety from Ultra-Short Duration Wearable Sensors Measurements.Sensors (Basel, Switzerland) · 2026Article
- Multiclass Arrhythmia Classification Using Multimodal Smartwatch Photoplethysmography Signals Collected in Real-Life Settings.IEEE transactions on bio-medical engineering · 2026Article
- ECG and PPG Signals-Based Premature Ventricular Contraction Detection Methods: A Review, Key Challenges, and Future Directions.Cardiovascular engineering and technology · 2026Review
- Development of an efficient deep learning model for arrhythmia detection from consumer smartwatches.Frontiers in artificial intelligence · 2026Article
- Reliable wrist PPG monitoring by mitigating poor skin sensor contact.Scientific reports · 2025Article
- The MSPTDfast photoplethysmography beat detection algorithm: design, benchmarking, and open-source distribution.Physiological measurement · 2025Article
- REM sleep-related bradyarrhythmia syndrome.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life.Sensors (Basel, Switzerland) · 2024Article
- Photoplethysmography based atrial fibrillation detection: a continually growing field.Physiological measurement · 2024Review
- Sex differences in autonomic functions and cognitive performance during cold-air exposure and cold-water partial immersion.Frontiers in physiology · 2024Article
- On the Reliability of Wearable Technology: A Tutorial on Measuring Heart Rate and Heart Rate Variability in the Wild.Sensors (Basel, Switzerland) · 2023Article
- Evaluating the Potential of an Oral-Based Bioguard to Estimate Heart Rate Using Photoplethysmography.Biosensors · 2023Article
- Accuracy of a Smartwatch to Assess Heart Rate Monitoring and Atrial Fibrillation in Stroke Patients.Sensors (Basel, Switzerland) · 2023Article
- A Smartwatch System for Continuous Monitoring of Atrial Fibrillation in Older Adults After Stroke or Transient Ischemic Attack: Application Design Study.JMIR cardio · 2023Article
- Edge-Enabled Heart Rate Estimation from Multisensor PPG Signals.Journal of healthcare engineering · 2023Article
- Detecting beats in the photoplethysmogram: benchmarking open-source algorithms.Physiological measurement · 2022Article
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Authors and funding
14 authors.
Funding
Abstract
objectiveWe have developed a peak detection algorithm for accurate determination of heart rate, using photoplethysmographic (PPG) signals from a smartwatch, even in the presence of various cardiac rhythms, including normal sinus rhythm (NSR), premature atrial contraction (PAC), premature ventricle contraction (PVC), and atrial fibrillation (AF). Given the clinical need for accurate heart rate estimation in patients with AF, we developed a novel approach that reduces heart rate estimation errors when compared to peak detection algorithms designed for NSR.
methodsOur peak detection method is composed of a sequential series of algorithms that are combined to discriminate the various arrhythmias described above. Moreover, a novel Poincaré plot scheme is used to discriminate between basal heart rate AF and rapid ventricular response (RVR) AF, and to differentiate PAC/PVC from NSR and AF. Training of the algorithm was performed only with Samsung Simband smartwatch data, whereas independent testing data which had more samples than did the training data were obtained from Samsung's Gear S3 and Galaxy Watch 3.
resultsThe new PPG peak detection algorithm provides significantly lower average heart rate and interbeat interval beat-to-beat estimation errors-30% and 66% lower-and mean heart rate and mean interbeat interval estimation errors-60% and 77% lower-when compared to the best of the seven other traditional peak detection algorithms that are known to be accurate for NSR. Our new PPG peak detection algorithm was the overall best performers for other arrhythmias.
conclusionThe proposed method for PPG peak detection automatically detects and discriminates between various arrhythmias among different waveforms of PPG data, delivers significantly lower heart rate estimation errors for participants with AF, and reduces the number of false negative peaks. SIGNIFICANCE: By enabling accurate determination of heart rate despite the presence of AF with rapid ventricular response or PAC/PVCs, we enable clinicians to make more accurate recommendations for heart rate control from PPG data.
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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.