Cardiac Time Intervals Under Motion Using Bimodal Chest E-Tattoos and Multistage Processing

Goal: We present a wireless, lightweight, stretchable, and chest-conformable sensor, known as the chest e-tattoo, coupled with an advanced signal processing framework to accurately identify various cardiac events, and thereby extract cardiac time intervals (CTIs) even during body motion.

Methods: We developed a wireless chest e-tattoo featuring synchronous electrocardiography (ECG) and seismocardiography (SCG), with SCG capturing chest vibrations to complement ECG. Motion artifacts often compromise the efficacy of SCG, but the e-tattoo's slim, stretchy design allows strategic placement near the xiphoid process for improved signal quality. Nine participants were monitored during walking and cycling. To accurately extract CTIs, we implemented a multistage signal processing framework, named the FAD framework, combining adaptive Normalized Least Mean Squares (NMLS) filtering, ensemble averaging, and Empirical Mode Decomposition (EMD).

Results: Key CTIs, especially left ventricular ejection time (LVET), were successfully extracted by our hardware-software system and showed strong agreement with those reported by an FDA-cleared bedside monitor even during substantial movements. The pre-ejection period (PEP) measured by the e-tattoo also aligned with previous findings.

Conclusion: The bimodal chest e-tattoo combined with the FAD framework enables reliable CTI measurements during various activities.

Significance: Managing cardiovascular disease at home necessitates continuous monitoring, which has been challenging with wearables due to signal sensitivity to motion. Accurately extracting cardiac events from synchronous SCG and ECG during motion can significantly enhance heart stress response quantification, offering a more comprehensive cardiac health assessment than ECG alone and marking a significant advancement in ambulatory cardiovascular monitoring capabilities.