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As it happens, the particular frequencies of the waves that LIGO can detect fall within the range of human hearing, between about thirty-five and two hertzed and fifty hertz.
Anderson et al. [5] also applied the aspect ratio of the silhouette to detect fall incidents.
The primary function of this device is to detect fall incidents through video monitoring [9, 10].
These devices are enhanced with information and communication technology to detect fall incidents, fall prevention, and also ameliorate alarming system.
Experimental results demonstrate that the proposed method outperforms the other state-of-the-art methods and can effectively detect fall incidents even when multiple subjects are moving together.
Different from the other researches, the experimental results in Section 4.3 demonstrate that the proposed method can effectively detect fall incidents even when multiple persons overlap.
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Finally, a prototype [ 40] was presented to detect falls of elderly by using a visual fall detection system and combining this with context information, e.g., patient's general condition, location and duration of patient's inactivity.
Our results showed that narrative text data on image order entries were the most valuable data for rapid detection of injurious falls when using the NLP method to detect falls in a hospital.
It is, therefore, difficult to use supervised learning methods to automatically detect falls.
The effectiveness of the proposed method to detect falls, localize, and track is verified by experiment.
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