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

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Wearable Technology

Background:

• Continuous cardiovascular monitoring is crucial for managing heart disease, but current wearables struggle with motion artifacts.
• Existing methods often lack the ability to accurately capture cardiac events during physical activity.

Purpose of the Study:

• To develop and validate a wireless, chest-conformable sensor (e-tattoo) and signal processing framework for reliable cardiac time interval (CTI) extraction.
• To assess the system's performance in accurately measuring CTIs, such as left ventricular ejection time (LVET) and pre-ejection period (PEP), during various physical activities.

Main Methods:

• Developed a wireless chest e-tattoo integrating electrocardiography (ECG) and seismocardiography (SCG) for synchronous data acquisition.
• Implemented a multistage signal processing framework (FAD) combining adaptive filtering, ensemble averaging, and Empirical Mode Decomposition (EMD) to extract CTIs.
• Monitored nine participants during walking and cycling to evaluate system performance under motion conditions.

Main Results:

• The e-tattoo system successfully extracted key CTIs, including LVET, with strong agreement compared to an FDA-cleared bedside monitor.
• Measurements of the pre-ejection period (PEP) using the e-tattoo aligned with established findings.
• Accurate CTI extraction was achieved even during substantial body movements.

Conclusions:

• The bimodal chest e-tattoo, coupled with the FAD framework, provides a reliable method for measuring cardiac time intervals during diverse activities.
• This technology represents a significant advancement in ambulatory cardiovascular monitoring, offering enhanced heart stress response quantification.