Abstract
Novel and Robust Vision- and System-on-chip-based Sensor for Fall Detection
Highlights
According to Ref. 1, the percentage of people aged 65 or older in the world will be 16% in 2050
In Taiwan, the percentage of elderly people aged 65 and above at the end of 2017 was 13.9%, and the percentage is expected to reach 20% in 2026.(2) The statistical data indicated that, on average, 28–35% of the elderly fall at least once a year, and these falls often lead to serious injuries, especially if the elderly patient falls at home.[3]. Once a fall event occurs for an elderly person, if a fall detection signal can be sent out in time to call for first aid, the person can be rescued
We propose a new, effective vision- and SoC-based fall detection method that consists of five steps: initial light stability confirmation, gradient-difference-based foreground detection, dilation- and multiframe-based foreground construction, false fall detection problem solving, and fall detection determination associated with a general-purpose input/output-based fall warning transmission
Summary
According to Ref. 1, the percentage of people aged 65 or older in the world will be 16% in 2050. The main reason is that the number of elderly people is increasing owing to the improvement in health care provided by hospitals and medical advancements. In Taiwan, the percentage of elderly people aged 65 and above at the end of 2017 was 13.9%, and the percentage is expected to reach 20% in 2026.(2) The statistical data indicated that, on average, 28–35% of the elderly fall at least once a year, and these falls often lead to serious injuries, especially if the elderly patient falls at home.[3] Once a fall event occurs for an elderly person, if a fall detection signal can be sent out in time to call for first aid, the person can be rescued. In the following brief survey of related works, we point out their weaknesses
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