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Tumble detection method and system based on class imbalance signal

A technology of balancing signals and detection methods, applied in the field of behavior recognition, can solve the problems of difficulty in identifying fall event signals, unbalanced fall detection categories, etc., and achieves the effects of good detection ability, reduced missed detection, and high detection accuracy.

Pending Publication Date: 2022-04-12
INST OF MICROELECTRONICS CHINESE ACAD OF SCI
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Problems solved by technology

[0006] In view of the above analysis, the embodiment of the present invention aims to provide a method and system for fall detection based on category imbalance signals to solve the problem that it is difficult to accurately identify a fall from a large number of daily activities due to category imbalance in existing fall detection. Issues with Fall Event Signaling

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  • Tumble detection method and system based on class imbalance signal
  • Tumble detection method and system based on class imbalance signal
  • Tumble detection method and system based on class imbalance signal

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Embodiment Construction

[0060] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

[0061] like figure 1 As shown, a specific embodiment of the present invention discloses a fall detection method based on category imbalance signals, including:

[0062] S10. Acquire the user's action test data collected by the smart wearable device in real time; the action test data includes: acceleration data and angular velocity values; specifically, according to the accelerometer and gyroscope acquisition of the smart wearable device on the user Acceleration data and angular velocity values ​​of various types of actions of the user in daily life. Specifically, the accelerometer and gyrosc...

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Abstract

The invention relates to a tumble detection method and system based on class imbalance signals, belongs to the technical field of behavior recognition, and solves the problem that tumble event signals are difficult to accurately recognize from a large number of daily activities due to class imbalance of tumble detection in the prior art. The method comprises the following steps: acquiring action test data of a user acquired by the intelligent wearable equipment in real time; the action test data comprises acceleration data and an angular velocity value; inputting the action test data into an optimal deep learning model, carrying out action category recognition on the action test data, and obtaining a probability value of each action category; comparing the probability value of each action category with an optimal threshold value, and predicting the action category corresponding to the action test data; wherein the optimal threshold value is used for enabling the prediction result to shift to the action category with the low occurrence probability according to the unbalance rate of a sample data set used during deep learning model training. Fall detection based on class imbalance data is realized.

Description

technical field [0001] The invention relates to the technical field of behavior recognition, in particular to a fall detection method and system based on class imbalance signals. Background technique [0002] It is well known that falls can lead to serious consequences such as paralysis, fractures, head injuries, etc., especially in the elderly. Cardiovascular and cerebrovascular diseases and gait disorders that the elderly often suffer from may lead to falls, causing the patient to lose consciousness and faint. Falling has become the biggest hidden danger that threatens the life safety of the elderly. In addition, the aging population is becoming more and more serious around the world. The number of elderly people and the proportion of living alone are increasing year by year. Once the elderly living alone fall, it is difficult to save themselves. In this case, the fall detection of the elderly is very important. application meaning. [0003] At present, fall detection c...

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Application Information

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IPC IPC(8): G06F3/01G06K9/00G06K9/62G06N3/04G06N3/08
Inventor 张静李佳王玮冰
Owner INST OF MICROELECTRONICS CHINESE ACAD OF SCI