Effect of Neural Network Algorithm Based Core Stabilization on Adverse Spinal Posts in Children

Abstract

Based on the neural network algorithm, this paper studies the influence of the neural
network algorithm's core stability on the poor spinal posture of 3-6-year-old children,
and mainly studies an algorithm to monitor the poor posture of the spine in children.
Firstly, the basic requirements and selection methods for feature selection and extraction
in sleeping position recognition are introduced. The Haar-like method is used to extract
the required features. Finally, a statistic-based BP neural network algorithm is used to
identify the sleeping position. Face classifier and side face classifier to be tested to detect
the image, the test results show that: The recognition algorithm of the high efficiency,
according to the child every time the real-time adjustment of the airbag to support the
child's posture.