Fall detection and alarm system and method based on KNN algorithm

A KNN algorithm and axial direction technology, applied to alarms, instruments, etc., can solve the problems of not being able to notify the elderly who have fallen in real time, having no communication function, and high false alarm rate

Inactive Publication Date: 2015-03-04
BEIJING UNIV OF TECH
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Problems solved by technology

However, for the monitoring of human body posture and movement, the current research trend at home and abroad is mainly based on the judgment of the acceleration threshold. This detection method is relatively simple, resulting in a relatively high false alarm rate, and it does not have a communication function. Relatives, locate fall

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  • Fall detection and alarm system and method based on KNN algorithm

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Embodiment Construction

[0063] The present invention is a kind of fall detection and alarm method based on KNN algorithm, such as figure 1 shown, including the following steps:

[0064] Step 1. The three-axis acceleration sensor and the three-axis gyroscope respectively collect the three-dimensional acceleration a of the upper torso in real-time at a sampling frequency of 100 times per second. x 、a y 、a z Data and three-dimensional angular velocity ω x , ω y , ω z data,

[0065] where a x is the acceleration along the x-axis direction, a y is the acceleration along the y-axis direction, a z is the acceleration along the z-axis direction, ω x is the angular velocity along the x-axis, ω y is the angular velocity along the y-axis direction, ω z is the angular velocity along the z-axis direction;

[0066] Step 2, the microprocessor calculates the combined acceleration and angular velocity ω = ω x ...

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Abstract

The invention discloses a fall detection and alarm system and a method based on KNN algorithm and belongs to the electronic information field. The fall detection and alarm method includes following steps: a three-axis acceleration sensor and a three-axis acceleration sensor respectively collect the three-dimensional accelerated speed data and three-dimensional angular speed data for human body upper torso at real time; a microprocessor calculates the sum of accelerated speed and the sum of the angular speed; a Bluetooth device transmits the sum of accelerated speed and the sum of the angular speed to a smart phone; the smart phone initializes the data sliding window of the sum of accelerated speed and the sum of the angular speed; the smart phone receives the sum of accelerated speed and the sum of the angular speed; the smart phone judges whether the sliding window is filled in; the smart phone calculates the distance between the test sample and the training sample and finds k nearest neighbors for the test sample; the smart phone judges whether there is fall according to the k nearest neighbors; the smart phone informs the set contact person according to the setting alarm mode. The fall detection and alarm system and the method are high in detection precision, low in error alarm rate, real-time in detection, and convenient and easy to use.

Description

technical field [0001] The invention relates to a fall detection and alarm system and method based on a KNN algorithm, belonging to the technical field of electronic detection. Background technique [0002] With the increasing aging of the population, falls have become a serious problem affecting the health of the elderly. It not only seriously affects the physical health and independent living ability of the elderly, but also causes the psychological burden and fear of the elderly, sometimes causing The consequences can even be fatal. Taking appropriate measures for fall detection and alarm can enable them to get timely rescue, avoid unnecessary troubles, and reduce medical expenses at the same time. [0003] The current fall detection methods for the elderly are mainly divided into three types: the first one is based on video monitoring, and a video monitor is installed in a specific area, and the human body is tracked and monitored in this area; the second is based on vi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08B21/04G08B25/10
CPCG08B21/043G08B25/08
Inventor 何坚胡晨王刚刘金伟余立
Owner BEIJING UNIV OF TECH
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