As the U.S. population age 65 and older continues to grow – the U.S. Census Bureau notes the demographic rose 38.6% from 2010 to 2020, the fastest rate since 1880 to 1890 – senior citizen health care is at the forefront of researchers and practitioners’ minds.
In a recent study published in the journal “Information Systems Research,” Texas Tech University’s Shuo Yu and his collaborators developed a generative machine learning model to detect instability before a fall occurs. The hope is that the model could work within fall detection devices, such as anti-fall airbag vests or medical alert systems, to minimize injuries, increase emergency response effectiveness and lower medical costs.