Markets Insider: Future of intelligent assisted living

UC engineers use AI to help caregivers respond quickly to falls

Markets Insider highlighted research by the University of CIncinnati to develop better sensor detection of falls among the elderly so caregivers can respond more quickly.

Nirmalya Thakur portrait.

Nirmalya Thakur

Falls are one of the leading causes of injury. More than 2.8 million older Americans are treated each year in emergency rooms for injuries sustained in a fall. More than 30,000 people 65 or older die in falls each year, according to the Centers for Disease Control and Prevention.

Medicare spent an estimated $52 billion last year covering injuries sustained in falls.

UC College of Engineering and Applied Science associate professor emeritus Chia Han and UC researcher Nirmalya Thakur developed a more reliable machine learning method to detect falls. The system can be used to alert caregivers to a fall so they can respond immediately.

Their approach identified a fall with more than 99% accuracy using two datasets.

The study was published in the Journal of Sensor and Actuator Networks.  

Thakur said UC's fall-detection system can be integrated into wearable sensors or smart homes and assisted living centers that increasingly use technology to keep residents safe.

Read the Markets Insider story.

Featured image at top: UC's College of Engineering and Applied Science came up with a more reliable system for detecting when someone falls. Photo/Claudia van Zyl/Unsplash