Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease.
cardiac output
machine learning
multimodal
noninvasive
pediatrics
Journal
Journal of the American Heart Association
ISSN: 2047-9980
Titre abrégé: J Am Heart Assoc
Pays: England
ID NLM: 101580524
Informations de publication
Date de publication:
20 09 2022
20 09 2022
Historique:
pubmed:
15
9
2022
medline:
23
9
2022
entrez:
14
9
2022
Statut:
ppublish
Résumé
Background Patients with congenital heart disease (CHD) are at risk for the development of low cardiac output and other physiologic derangements, which could be detected early through continuous stroke volume (SV) measurement. Unfortunately, existing SV measurement methods are limited in the clinic because of their invasiveness (eg, thermodilution), location (eg, cardiac magnetic resonance imaging), or unreliability (eg, bioimpedance). Multimodal wearable sensing, leveraging the seismocardiogram, a sternal vibration signal associated with cardiomechanical activity, offers a means to monitoring SV conveniently, affordably, and continuously. However, it has not been evaluated in a population with significant anatomical and physiological differences (ie, children with CHD) or compared against a true gold standard (ie, cardiac magnetic resonance). Here, we present the feasibility of wearable estimation of SV in a diverse CHD population (N=45 patients). Methods and Results We used our chest-worn wearable biosensor to measure baseline ECG and seismocardiogram signals from patients with CHD before and after their routine cardiovascular magnetic resonance imaging, and derived features from the measured signals, predominantly systolic time intervals, to estimate SV using ridge regression. Wearable signal features achieved acceptable SV estimation (28% error with respect to cardiovascular magnetic resonance imaging) in a held-out test set, per cardiac output measurement guidelines, with a root-mean-square error of 11.48 mL and
Identifiants
pubmed: 36102243
doi: 10.1161/JAHA.122.026067
pmc: PMC9683676
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
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