Fall detection method and device based on multi-sensor data fusion
A data fusion and multi-sensor technology, applied in the direction of instruments, alarms, etc., can solve the problems of great influence on the recognition rate and high complexity of the recognition model, and achieve the effect of improving recognition ability, improving reliability and reducing false alarms
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Embodiment 1
[0035] Such as figure 1 with figure 2 As shown, a method of fall detection based on multi-sensor data fusion provided in this embodiment includes the following steps:
[0036] S1. Collect a sufficient number of human motion state data samples.
[0037] In order to build a support vector machine-based human fall recognition model, the support vector machine model is trained, and multiple groups of sample data of human motion states are collected, including fall action data and ADL (human daily behavior activities, Activity of daily livings) data.
[0038] The fall actions include fall forward, fall backward, fall left, fall right, fall on the back, fall on the stomach and other fall types. ADL data includes normal walking, up and down stairs, running, and posture changes such as standing, sitting, and squatting.
[0039] S2. Extract the feature vector of the plantar pressure of the human fall from the sample data, and establish a human fall recognition model based on the s...
Embodiment 2
[0059] Such as image 3 As shown, a fall detection device based on multi-sensor data fusion disclosed in this embodiment includes a pressure sensor, a triaxial acceleration sensor, a wireless sending module, a wireless receiving module, a microprocessor, and a help module. The pressure sensor, The triaxial acceleration sensors are respectively connected to the wireless sending module, the wireless sending module is connected to the wireless receiving module by wireless, the wireless receiving module is connected to the microprocessor, and the microprocessing module according to the pressure The sensor and the triaxial acceleration data are analyzed and judged to determine whether the human body has fallen; the microprocessor is connected to the distress module, and the distress module sends a distress signal according to the judgment result.
[0060] In a specific embodiment, the pressure sensor and the triaxial acceleration sensor are arranged on the sole of the human body. ...
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Abstract
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