Falling detection and early-warning method based on smart wearable device

A smart wearable device and alarm signal technology, applied in the field of data processing, can solve the problem of difficult to distinguish between the dangerous state and the normal state of falling, and achieve the effect of protecting safety

Active Publication Date: 2018-07-06
广州爱牵挂数字科技有限公司
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Problems solved by technology

First of all, the data collection uses the pressure sensor on the sole of the foot; secondly, there is a big difference between the gait characteristics of Parkinson's patients and

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  • Falling detection and early-warning method based on smart wearable device
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  • Falling detection and early-warning method based on smart wearable device

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[0029] The specific embodiments of the present invention will be further described below in conjunction with the drawings:

[0030] Reference figure 1 , A fall detection and early warning method based on smart wearable devices, including the following steps:

[0031] A. Read in training data, the training data includes multiple sets of healthy people's gait data and multiple sets of abnormal gait data, and the training data is the acceleration of the hand swing during walking;

[0032] First of all, the acceleration data of the hand swing can accurately reflect the state of the hand swing under the state of uniform motion. figure 2 The ideal model of healthy human gait data shown, when the time is 0, the acceleration is the maximum, the arm swings forward from the end, the arm swings the maximum speed when the first zero point is reached, and then starts to decelerate until the arm swings to the foremost position. The first half cycle of a gait; then the second half cycle of a gait ...

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Abstract

The invention discloses a falling detection and early-warning method based on a smart wearable device. The method comprises the following steps: reading training data; extracting characteristic parameters; training an SVM classifier; collecting sensing data; testing the collected data by using an SVM classifier, determining whether a falling risk occurs and carrying out prompting; and detecting whether falling occurs and carrying out early warning. According to the invention, the SVM classifier is trained based on characteristic parameters extracted from gait data of the healthy person and abnormal gait data; and whether the gait is in an abnormal state is distinguished and identified accurately, so that the possible falling situation is prompted in advance; and if the falling may occur, real-time falling detection is carried out on the user to protect the safety of the user. The falling detection and early-warning method based on a smart wearable device can be applied to the field ofdata processing widely.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a fall detection and early warning method based on smart wearable devices. Background technique [0002] With the aging of the population, the population over the age of 60 in my country has exceeded 230 million. The health and safety of the elderly has attracted widespread attention from the society. The daily life ability of the elderly has declined, and problems such as falls, trends, sudden illnesses, and forgetting to take medicine are common. . Existing smart wearable devices can detect static parameters such as blood pressure and heart rate, and detect dynamic parameters such as falls, and then get more feedback during product use. For the elderly, a fall may cause joint damage or even a fracture. The current fall detection technology can only realize the detection after the fall, and it is difficult to meet other functional requirements. [0003] In terms of gait recogniti...

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Application Information

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IPC IPC(8): G08B21/04
CPCG08B21/0446G08B21/0453
Inventor 陈震郭伟斌皮亦然陈文声王锦章
Owner 广州爱牵挂数字科技有限公司
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