Scientists unveil starfish-inspired wearable tech for heart monitoring
Peer-Reviewed Publication
Updates every hour. Last Updated: 4-Sep-2025 18:11 ET (4-Sep-2025 22:11 GMT/UTC)
When we move, it’s harder for existing wearable devices to accurately track our heart activity. But University of Missouri researchers found that a starfish’s five-arm shape helps solve this problem. Inspired by how a starfish flips itself over — shrinking one of its arms and using the others in a coordinated motion to right itself — Sicheng Chen and Zheng Yan in Mizzou’s College of Engineering and collaborators have created a starfish-shaped wearable device that tracks heart health in real time. Because the starfish-inspired device has multiple points touching the skin near the heart, it stays more stable than traditional wearables built as a single, unified structure, such as a smartwatch. This allows the device to collect clearer, more accurate heart data — even while someone is moving. The device conveniently pairs with a smartphone app to provide the user with health insights and help detect potential heart problems.
World leaders should look to existing international law on the use of force to address the threat of space becoming ever more militarized, a new study shows.
Kenneth Merz, PhD, of Cleveland Clinic's Center for Computational Life Sciences, and his team are testing quantum computing’s abilities in chemistry through integrating machine learning and quantum circuits.
Chemistry is one of the areas where quantum computing shows the most potential because of the technology’s ability to predict an unlimited number of possible outcomes. To determine quantum computing's ability to perform complex chemical calculations, Dr. Merz and Hongni Jin, PhD, decided to test its ability to simulate proton affinity, a fundamental chemical process that is critical to life.
Dr. Merz and Dr. Jin focused on using machine learning applications on quantum hardware. This is a critical advantage over other quantum research which relies on simulators to mimic a quantum computer’s abilities. In this study, published in the Journal of Chemical Theory and Computation, the team was able to demonstrate the capabilities of quantum machine learning by creating a model that was able to predict proton affinity more accurately than classical computing.
When spring arrives and the heating season comes to an end, keeping warm becomes less of an issue. However, scientists remind us that it is not just a seasonal necessity – heat is also a valuable energy resource that can be stored and used when needed most. Researchers at Kaunas University of Technology (KTU) have discovered an innovative solution beneath our feet: using soil as an efficient thermal energy storage system.