Photoplethysmography-Based Ambulatory Heartbeat Monitoring Embedded into a Dedicated Bracelet

dc.contributor.authorArberet, Simon
dc.contributor.authorLemay, Mathieu
dc.contributor.authorRenevey, Philippe
dc.contributor.authorSola, Josep
dc.contributor.authorGrossenbacher, Olivier
dc.contributor.authorAndries, Daniela
dc.contributor.authorSartori, Claudio
dc.contributor.authorBertschi, Mattia
dc.date.accessioned2022-02-14T17:07:57Z
dc.date.available2022-02-14T17:07:57Z
dc.date.issued2013-09-22
dc.description.abstractAmbulatory electrocardiogram (ECG) monitors have been intensely used since half century but are still associated to clinical/ambulatory cumbersome procedures. The question of this research is the following: what is the performance of a photoplethysmography (PPG)- based device located at the wrist in terms of heart rate variability (HRV) monitoring? PPG and ECG signals were recorded simultaneously on 4 subjects. Heart-beat (RR) intervals were estimated from both devices. For PPG signals, a multi-sensors approach based on the detection of local minima of the timederivative was used to estimate RR time series. For ECG signals, an approach based on adaptive threshold was used (gold standard). The normalized differences observed on time-domain and frequency-domain HRV features were computed. Results based on 1565 minutes of recordings (N=94’000) showed an averaged correlation around 0.9 between the HRV features extracted from the PPG and ECG-based device. In view of these results, it appears that the wrist sensor opens the door towards a new generation of comfortable and easy-to-use cardiac HRV tool especially well adapted for long-term monitoring.
dc.identifier.citationComputers in Cardiology 2013, Zaragoza (ES), pp. 4
dc.identifier.doihttps://doi.org/10.2316/p.2014.818-077
dc.identifier.isbn978-1-4799-0886-8
dc.identifier.urihttps://hdl.handle.net/20.500.12839/799
dc.titlePhotoplethysmography-Based Ambulatory Heartbeat Monitoring Embedded into a Dedicated Bracelet
dc.typeProceedings Article
dc.type.csemdivisionsDiv-E
dc.type.csemresearchareasDigital Health
Files