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dc.contributor.authorTarniceriu, Adrian
dc.contributor.authorHarju, Jarkko
dc.contributor.authorVehkaoja, Antti
dc.contributor.authorParak, Jakub
dc.contributor.authorDelgado-Gonzalo, Ricard
dc.contributor.authorRenevey, Philippe
dc.contributor.authorYli-Hankala, Arvi
dc.contributor.authorKorhonen, Ilkka
dc.date.accessioned2022-02-14T17:07:49Z
dc.date.available2022-02-14T17:07:49Z
dc.date.issued2018
dc.identifier.citation2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Las Vegas, NV (USA), pp. 133-136
dc.identifier.isbn978-1-5386-2405-0
dc.identifier.urihttps://yoda.csem.ch/handle/20.500.12839/696
dc.description.abstractWrist photoplethysmography (PPG) allows unobtrusive monitoring of the heart rate (HR). PPG is affected by the capillary blood perfusion and the pumping function of the heart, which generally deteriorate with age and due to presence of cardiac arrhythmia. The performance of wrist PPG in monitoring beat-to-beat HR in older patients with arrhythmia has not been reported earlier. We monitored PPG from wrist in 18 patients recovering from surgery in the post anesthesia care unit, and evaluated the inter-beat interval (IBI) detection accuracy against ECG based R-to-R intervals (RRI). Nine subjects had sinus rhythm (SR, 68.0y ± 10.2y, 6 males) and nine subjects had atrial fibrillation (AF, 71.3y ± 7.8y, 4 males) during the recording. For the SR group, 99.44% of the beats were correctly identified, 2.39% extra beats were detected, and the mean absolute error (MAE) was 7.34ms. For the AF group, 97.49% of the heartbeats were correctly identified, 2.26% extra beats were detected, and the MAE was 14.49ms. IBI from the PPG were hence in close agreement with the ECG reference in both groups. The results suggest that wrist PPG provides a comfortable alternative to ECG and can be used for long-term monitoring and screening of AF episodes.
dc.titleDetection of beat-to-beat intervals from wrist photoplethysmography in patients with sinus rhythm and atrial fibrillation after surgery
dc.typeProceedings Article
dc.type.csemdivisionsDiv-E
dc.type.csemresearchareasDigital Health
dc.identifier.urlhttp://ieeexplore.ieee.org/document/8333387/
dc.identifier.doi10.1109/BHI.2018.8333387


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