A novel computational signal processing framework towards multimodal vital signs extraction using neck-worn wearable devices.
Accelerometer (Acc)
Exponentially weighted moving average (EWMA)
Neck
Photoplethysmography (PPG)
Vital signs
Wearable devices
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
27 Sep 2024
27 Sep 2024
Historique:
received:
05
03
2024
accepted:
04
09
2024
medline:
28
9
2024
pubmed:
28
9
2024
entrez:
27
9
2024
Statut:
epublish
Résumé
Pulse rate (PR) and respiratory rate (RR) are two of the most important vital signs. Monitoring them would benefit from easy-to-use technologies. Hence, wearable devices would, in principle, be ideal candidates for such systems. The neck, although highly susceptible to artifacts, presents an attractive location for a diverse pool of physiological biomarkers monitoring purposes such as airflow sensing in a non-obstructive manner. This paper presents a methodology for PR and RR estimation using photoplethysmography (PPG) and accelerometry (Acc) sensors placed on the neck. Neck PPG and Acc signals were recorded from 22 healthy participants for RR estimation, where the resting subjects performed guided breathing following a visual metronome. Neck PPG signals were obtained from 16 healthy participants who breathed through an altitude generator machine in order to acquire a wider range of PR readings while at rest. The proposed methodology was able to provide rate estimates via a combination of recursive FFT-based dominance scoring coupled with an exponentially weighted moving average (EWMA)-driven aggregation scheme. The recursion aimed at bypassing sudden intra-window amplitude deviations caused by momentary artifacts, while the EWMA-based aggregation was utilized for handling inter-window artifact-induced deviations. To further improve estimation stability and confidence, estimates were calculated in the form of rate bands taking into account the relevant clinically acceptable error margins, and results when considering rate values and rate bands are presented and discussed. The framework was able to achieve an overall pulse rate value accuracy of
Identifiants
pubmed: 39333140
doi: 10.1038/s41598-024-72184-7
pii: 10.1038/s41598-024-72184-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
22368Subventions
Organisme : European Research Council
ID : 724334
Pays : International
Organisme : European Research Council
ID : 724334
Pays : International
Informations de copyright
© 2024. The Author(s).
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