detecting falls
CDC reports the death rate from falls among older adults has increased by 42% from 2000 to 2006. Over 21,700 older Americans die annually from injuries related to unintentional falls. In 2012, over 2.4 million older adults were treated in emergency departments for falls; more than 722,000 or 30% of these patients had to be hospitalized (Centers for Disease Control and Prevention, 2014a). The total cost of fall injuries for older Americans was estimated to be $36.4 billion (in 2010 dollars). By 2020, the annual direct and indirect cost of fall injuries is expected to reach $54.9 billion. - See more at NCOA.org. You can read a summary of the current technology and challenges for fall detection here.
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automatic alertsOur system is very accurate at detecting falls. It is the first solution that works during the night -commonly falls occur under low light condition.
The activities at the top of the video (left) were automatically detected by our system. |
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common falls |
The following are real images of fall consequences in 2015 -read the description of the images-. In our survey we did find 3 interesting scenarios: 1) Seniors fall of bed a lot. This mainly happens when they try to get out of bed with poor light conditions. -generally during winter time-. 2) If seniors fall in at home, it can pass hours until someone realizes about the event. 3) Falls are recurrent.
The prediction of falls could be achieved by understanding the deviations in the participant's balance over time. Once an elderly person has experienced the serious consequences of a fall, the fear of falling again is present. Knowing that a fall will be detected and there is a mechanism ready to intervene can have a positive impact, the participants could regain confidence [1].
[1] K.L. Courtney, G. Demitris, M. Rantz, M. Skubic, Needing smart home technologies: the perspectives of older adults in continuing care retirement communities. Informatics in primary care 16 (2008), 195-201.
[1] K.L. Courtney, G. Demitris, M. Rantz, M. Skubic, Needing smart home technologies: the perspectives of older adults in continuing care retirement communities. Informatics in primary care 16 (2008), 195-201.