Application of microsensors and support vector machines in the assessment of lower limb posture correction in adolescents

Abstract

SummaryAutomatic monitoring of physical activity provides reliable data support for the maintenance of people's physical health and provides more scientific data for studying the relationship between physical activity and disease. In this article, a research on the evaluation of adolescent lower limb posture correction based on collaborative filtering and microsensors is carried out. Aiming at the problem that the human body posture monitoring system needs multiple nodes, this article simplifies the existing human body posture monitoring model and establishes a human body model with four degrees of freedom of the lower limbs. On this basis, the micro‐sensor assembly scheme and monitoring node layout scheme for obtaining model description parameters are determined. Methods such as collaborative filtering and support vector machines are used in the process of sensor data processing and correction effect evaluation. Finally, this article uses the constructed human body posture monitoring system to carry out the recognition test of the specific posture of the human body. The experimental results show that the evaluation scheme can effectively monitor and evaluate the effect of lower limb posture correction in adolescents.