Scientists use machine learning to prevent senior falls

Researchers are developing intelligent devices that predict and prevent deadly falls among the elderly, by using machine learning that is supported by the cyberinfrastructure of the Pacific Research Platform (PRP) over the California Research and Education Network (CENIC). Wearable gadgets, such as smartwatches and smartphones, could be equipped with remote monitoring technology that detects balance impairments.

“We’re developing a wearable, wireless sensor that predicts the likelihood that someone is going to fall,” said Christopher Paolini, assistant professor of electrical and computer engineering at San Diego State University, during the second National Research Platform workshop in Bozeman, Montana, in August. The conference aimed to extend to a national scale the capacity of PRP, which supports a ‘big data freeway’ with high-performance network interoperability to a wide range of researchers at institutions across the Pacific region.