Animesh Tandon

Country flagUnited States

Research Interests

Explore related searches

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Articles (7)

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 R 2 of 0.76. Additionally, we observed that using a combination of electrical and cardiomechanical features surpassed the performance of either modality alone. Conclusions A convenient wearable biosensor that estimates SV enables remote monitoring of cardiac function and may potentially help identify decompensation in patients with CHD.

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Collaborators (5)

Islam Abudayyeh

Assistant Professor

Loma Linda University

UNITED STATES
View details

Radomir Chabiniok

Assistant Professor

Southwestern Medical Center

UNITED STATES
View details

Martin Genet

Assistant Professor

Ecole Polytechnique

FRANCE
View details

Tarique Hussain

UT Southwestern

UNITED STATES
View details

Alexander R. Opotowsky

-

UNITED STATES
View details
ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.