In a 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.
Researcher develops generative learning model to predict falls
