Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease.


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
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

e026067

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Auteurs

Venu G Ganti (VG)

Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA.

Asim H Gazi (AH)

School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA.

Sungtae An (S)

School of Interactive Computing Georgia Institute of Technology Atlanta GA.

Adith V Srivatsa (AV)

The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA.

Brandi N Nevius (BN)

School of Mechanical Engineering Georgia Institute of Technology Atlanta GA.

Christopher J Nichols (CJ)

The Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA.

Andrew M Carek (AM)

Department of Biomedical Engineering, McCormick School of Engineering Northwestern University Evanston IL.
Department of Anesthesiology, Feinberg School of Medicine Northwestern University Evanston IL.

Munes Fares (M)

Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX.

Mubeena Abdulkarim (M)

Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX.

Tarique Hussain (T)

Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX.

F Gerald Greil (FG)

Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX.

Mozziyar Etemadi (M)

Department of Biomedical Engineering, McCormick School of Engineering Northwestern University Evanston IL.
Department of Anesthesiology, Feinberg School of Medicine Northwestern University Evanston IL.

Omer T Inan (OT)

Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA.
School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA.

Animesh Tandon (A)

Department of Pediatrics University of Texas Southwestern Medical Center Dallas TX.
Cleveland Clinic Children's Cleveland OH.

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