Can Artificial Intelligence Detect and Prevent Senior Falls?
Press Releases
Nov 15, 2019
AUSTIN, Texas, Nov. 15, 2019 /PRNewswire/ — VA2CS, the European leader in AI-Powered Fall Detection and Prevention, is launching its product at GSA 2019! The solution is already deployed in 2,700 rooms in 6 European countries. Artificial Intelligence uses visual and infrared sensors to automatically detect when a person is falling and trigger alarm to care-givers. A short recording of the fall allows care-givers to understand the reasons for the fall and to take corrective actions.
“Most existing solutions based on a press-button pendant or watch are not reliable; people just don’t wear them or forget to press the button when the fall happens,” says Ramzi Larbi, VA2CS CEO. “Our solution is non-intrusive – people don’t need to wear a device – and it reliably detects 85% of the falls. That’s the power of Artificial Intelligence!” continues Ramzi.
VA2CS is currently deployed in institutions, nursing homes, retirement homes and hospitals, as well as individual residences. Customers include institutions like Edenis, Domidep, Colisee, the Ehpad Jean Lachenaud and the Ehpad Solemnes. “We are very sensitive to the fall issue for our residents and we are using VA2CS all the time to detect them,” explains Nicolas Salandini, the CEO of the Solemnes group. “We particularly appreciate the recording of the event to analyze the cause of the falls so we can act accordingly,” adds Nicolas.
Jimmy Carter’s fall last week is just one of the 800,000 hospitalizations that results in 27,000 deaths every year in the U.S. Total cost is expected to reach $67 billion by 2020, according to the National Council on Aging. “Undiscovered falls can lead to a dramatic situation; we have to do something about this,” says Xavier Wartelle, founding partner at big bang factory, a growth accelerator that helps VA2CS in their US launch.
VA2CS will conduct live demonstrations at its booth #520 at GSA 2019.
For more information, please visit https://www.va2cs.fr/en/.
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SOURCE VA2CS