Better knee surgery results | A flexible skin sensor for monitoring health conditions
Better knee surgery results
DURHAM, NC–Knee pain is a common complaint among adults. When treatment with physical therapy and steroid injections fails, the usual next step is surgery. A Duke University-led team says they’ve created the first gel-based cartilage substitute that is even stronger and more durable than the real thing. The hydrogel, made up of water-absorbing polymers — can be pressed and pulled with more force than natural cartilage, and is three times more resistant to wear and tear.
A flexible skin sensor for monitoring health conditions
CINCINNATI, OH–A new sweat sensor created by a University of Cincinnati electrical engineer represents a leap forward in wearable technology. Assistant professor Yeongin Kim and a team from MIT developed the lightweight skin sensor to monitor conditions such as heart disease, depression, or diabetes. The device fits like a Band-Aid and relies on surface acoustic wave tech to transmit health data wirelessly.
Looking at sleep apnea a different way
MINNEAPOLIS, MN–GEM Health, a startup focused on sleep apnea, has launched its first product offering: a digital platform called GEM Sleep that aims to help potential sleep apnea sufferers navigate diagnosis and treatment in a one-stop virtual hub.
COLUMBUS, OH–A “smart sock” that prevents patient falls developed by Palarum has been the subject of a research study by nurses at The Ohio State University Wexner Medical Center. The PUP smart sock has built-in pressure sensors that detect when a patient is trying to stand up and exchanges that data over a wireless network. it was tested on 569 patients who were in the hospital on a fall-risk protocol and the nurses recorded no falls.
Using data and AI to improve patient outcomes
ST. LOUIS, MO–A professor of computer science and engineering in the Washington University in St. Louis McKelvey School of Engineering is combining artificial intelligence with data to improve patient care and outcomes. Chenyang Lu’s team is using novel algorithms to predict who would be in surgery for longer and who was likely to develop delirium after surgery. The team is also using data of activity logs to extrapolate patterns of workload and predict burnout in doctors.