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Wearable Seismocardiography-Based Assessment of Stroke Volume in Congenital Heart Disease
Venu G Ganti1, Asim H Gazi2, Sungtae An3
1Bioengineering Graduate Program Georgia Institute of Technology Atlanta GA.
Insights
Wearable sensors can now estimate stroke volume (SV) in children with congenital heart disease (CHD) using seismocardiogram and ECG signals. This technology offers a convenient, affordable way to monitor cardiac function remotely.
Area of Science:
- Biomedical Engineering
- Cardiology
- Wearable Technology
Background:
- Congenital heart disease (CHD) patients risk low cardiac output, requiring continuous stroke volume (SV) monitoring.
- Current SV measurement methods are invasive, location-specific, or unreliable.
- Wearable seismocardiogram offers a convenient, affordable alternative for continuous SV monitoring.
Purpose of the Study:
- To assess the feasibility of wearable SV estimation in a diverse pediatric CHD population.
- To compare wearable SV estimation against cardiac magnetic resonance imaging (CMR) as a gold standard.
- To evaluate the performance of multimodal wearable sensing for SV monitoring in CHD.
Main Methods:
- Utilized a chest-worn biosensor to capture ECG and seismocardiogram signals.
- Derived features, primarily systolic time intervals, from wearable signals.
- Employed ridge regression for SV estimation and validated against CMR data.
Main Results:
- Achieved acceptable SV estimation in CHD patients with 28% error compared to CMR.
- Reported a root-mean-square error of 11.48 mL and R² of 0.76.
- Demonstrated that combining electrical and cardiomechanical features improved SV estimation accuracy.
Conclusions:
- Wearable biosensors can conveniently estimate SV in children with CHD.
- This technology enables remote cardiac function monitoring.
- Potential to aid early detection of decompensation in CHD patients.
Abstract:
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 R2 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.
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