A starfish-inspired, bioelectronic wearable can capture cardiac electrical and mechanical systems while a patient is moving for real-time diagnosis of heart conditions, researchers have discovered.
The novel technology has five flexible sensing arms attached to a central electronic hub and can identify atrial fibrillation, myocardial infarction, and heart failure with greater than 90% accuracy when paired with machine learning (ML).
The findings open new avenues where bio-inspired device concepts can be combined with cutting-edge data science to boost bioelectronic performance and diagnostic precision, say the researchers.
“This starfish-like device represents a significant advancement in soft bioelectronics for precision health care, demonstrating the potential of bioinspired device designs and ML-enabled signal processing to enhance signal integrity and improve diagnostic precision in real-time conditions, thus expanding the potential of wearable health technologies,” they reported in the journal Science Advances.
Heart conditions can emerge during everyday activities and many are treatable with early detection and timely intervention, noted Sicheng Chen, PhD, from the University of Missouri, and co-workers.
This makes ambulatory cardiac monitoring essential for improving patient outcomes and reducing mortality, and monitoring cardiac electrical functions using an electrocardiogram (ECG) is widely used in clinical practice.
Simultaneously measuring cardiac mechanical activities through a seismocardiogram (SCG) and gyrocardiogram (GCG) can also offer extra information, tracking the translational and rotational components of cardiac-induced chest vibrations that an ECG cannot capture.
However, capturing cardiac mechanics has been challenging due to interference induced by movement, which led the researchers to develop the novel wearable inspired by the fivefold radial symmetry of a starfish.
The team noted that a starfish can operate its arms independently, each sensing its surroundings without interference from the others. In the same way, the freestanding arms of the device reduce motion interference, allowing accurate signal monitoring.
The novel system can collect three high-fidelity cardiac signal types during motion, comprising cardiac electrical (ECG) and mechanical (SCG and GCG) signals.
These data are wirelessly transmitted via Bluetooth and processed using ML algorithms on smartphones for real-time heart health evaluation.
The starfish-like wearable integrates signal compensation with ML-enabled motion recognition and adaptive filtering to achieve high-fidelity recording of cardiac signals during physical activities.
It was able to attain a real-time accuracy of over 91% in diagnosing heart conditions such as atrial fibrillation, myocardial infarction, and heart failure.
The investigators maintained that “our research harnesses the morphological brilliance of starfish to reshape the device configuration of soft bioelectronics, minimizing mechanical interference.”
They added: “This bioinspired approach establishes a solid foundation for next-generation soft bioelectronic systems capable of capturing high-fidelity biosignals, even under dynamic bodily conditions.”
