Wearable home body posture detection Internet of Things terminal

Abstract

The invention relates to a wearable home body posture detection Internet of Things terminal which is characterized by comprising a posture detection node for collecting and sending body posture data information, wherein the posture detection node and an upper computer communicate through a ZigBee wireless serial port; the upper computer performs two-way communication with a remote cloud service platform through the Internet; and multiple sensor signal collection modules which can be worn on the body parts are arranged in the posture detection node. In the invention, a three-axis acceleration sensor, a three-axis angular velocity sensor and a gyroscope are adopted, and the information collected by the sensors is used for performing data preprocessing, time domain analysis and frequency domain analysis to realize detection of the body home postures, namely, the walking, standing and sitting postures; and the upper computer transfers the collected information to the remote cloud service platform, big data management is supported by a cloud server, and the detection analysis feedback of the data is realized to implement intervention in the body posture and offer improvement advices.

Description

technical field [0001] The invention relates to the technical field of detection of human body motion posture information at home, in particular to a wearable household human body posture detection IoT terminal. Background technique [0002] With the development of society and the continuous improvement of people's living standards, people pay more and more attention to their own health, especially the physical health of teenagers. Today's teenagers have many lesions in the spine, shoulders, etc. due to incorrect sitting and walking postures. [0003] At present, the means of human home posture detection mainly include video recognition, that is, image analysis and acceleration analysis. Among them, the cost of video recognition is relatively high, and the algorithm of image analysis is complicated, the system is complicated, and the real-time performance is poor; the acceleration analysis algorithm is relatively simple and the system is small. , good real-time performanc...

AI Technical Summary

Problems solved by technology

[0003] At present, the means of human home posture detection mainly include video recognition, that is, image analysis and acceleration analysis. Among them, the cost of video recognition is relatively high, and the algorithm of image analysis is complicated, the system is complicated, and the real-time performance is poor; the acceleration analysis algorithm is relatively simple and the system is small. , good real-time performance

At present, there are many theoretical studies on the use of acceleration signals to study human body posture recognition and classification in China, but most of these theories only detect postures, and do not constitute an Internet of Things to intervene and suggest postures.

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