Fall-down detection alarm system based on Kalman filtering and KNN algorithm and method thereof

A technology of Kalman filtering and KNN algorithm, applied in alarms, instruments, etc., can solve the problems of not being able to notify the elderly who have fallen in real time, the detection method is single, and there is no communication function.

Active Publication Date: 2016-07-06
BEIJING UNIV OF TECH
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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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 determination of the acceleration threshold, but the threshold method has great limitations; prone to false posi

Method used

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  • Fall-down detection alarm system based on Kalman filtering and KNN algorithm and method thereof
  • Fall-down detection alarm system based on Kalman filtering and KNN algorithm and method thereof
  • Fall-down detection alarm system based on Kalman filtering and KNN algorithm and method thereof

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Embodiment 1

[0086] Embodiment 1: as Figure 1-2 , 5, the present invention provides a fall detection and alarm system based on Kalman filter and KNN algorithm, comprising: acquisition module 1, processing module 2, transmission module 3, identification module 4, judgment module 5 and notification module 6; wherein The identification module 4, the judgment module 5 and the notification module 6 constitute a monitoring terminal, and the identification module 4, the judgment module 5 and the notification module 6 are connected in sequence; the monitoring terminal can be a smart phone.

[0087] Acquisition module 1 includes a three-axis acceleration sensor and a three-axis gyroscope, the three-axis acceleration sensor and the three-axis gyroscope are installed on the upper torso of the human body, and the three-axis acceleration sensor and the three-axis gyroscope are respectively Real-time acquisition of the three-dimensional acceleration a of the upper torso during human activities x 、a y...

Embodiment 2

[0137] Embodiment 2: as Figure 3-5 As shown, the present invention also discloses a fall detection and alarm method based on Kalman filter and KNN algorithm, including:

[0138] Step 1. The three-axis acceleration sensor and the three-axis gyroscope are installed on the upper torso of the human body, and the three-axis acceleration sensor and the three-axis gyroscope respectively collect the three-dimensional acceleration of the upper torso during human activities in real time at a sampling frequency of 100 times per second a x 、a y 、a z Data and three-dimensional angular velocity ω x , ω y , ω z data; 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, such as Figure 5 shown;

[0139] Step 2, the microproce...

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Abstract

The invention discloses a fall-down detection alarm system based on Kalman filtering and a KNN algorithm and a method thereof. The system comprises an acquisition module, a processing module, a transmission module, an identification module, a judgment module and a notification module. The acquisition module is used for acquiring three-dimensional acceleration and three-dimensional angular velocity data of the upper body part in movement of a human body. The processing module calculates resultant acceleration and resultant angular velocity through the three-dimensional acceleration and three-dimensional angular velocity data. The identification module performs classified identification on the movement state of the human body based on Kalman filtering and the KNN algorithm so as to identify the movement type of the human body. The judgment module judges whether the movement type of the human body is a "fall-down" type, and the notification module notifies the set contact persons through the set alarm manner if the judgment result is the "fall-down" type. The movement state of the human body is identified based on Kalman filtering and the KNN algorithm so that detection accuracy is high and false alarm rate is low; and the system has a communication function and can notify the relatives of the fall-down elder in real time and determine the fall-down position.

Description

technical field [0001] The invention relates to the technical field of electronic detection, in particular to a fall detection and alarm system and method based on Kalman filter and KNN algorithm. 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] Now there are three main methods of fall detection for the elderly: the first one is based on video monitoring, where 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 ...

Claims

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Application Information

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IPC IPC(8): G08B21/04
CPCG08B21/043
Inventor 何坚周明我张岩张丞
Owner BEIJING UNIV OF TECH
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