Research on the intelligent model of progress in physical education training based on motion sensor

被引：0

作者：

Du, Jingtao ^{[1
]}

Nan, Zichun ^{[2
]}

机构：

[1] Department of P. E., Shijiazhuang Posts and Telecommunications Technical College, Shijiazhuang,Hebei,050021, China

[2] Institute of Physical Education, Xingtai University, Xingtai,Hebei,054001, China

来源：

Microprocessors and Microsystems | 2021年 / 82卷

关键词：

Energy utilization - Students - Neural networks - Field programmable gate arrays (FPGA) - Education computing - Wearable sensors;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Physical activity characteristics indicate the degree of mobility that underlies the chronic disease and aging process. Accelerometers have been broadly acknowledged as helpful and viable sensors as wearable gadgets that quantify and assess actual movement. It will consider developing a wearable accelerometer-based motion detector. The proposed Artificial Neural Network (ANN) system operates on the principle of accelerometer measurement. Sensor qualities and sensor show positions are first presented. Different investigations were audited utilizing accelerometer-based wearable movement identifiers and assessed utilizing actual action checking and evaluation, including postural and movement arrangement, energy consumption, fall identification, and assessment of equilibrium control appraisals. Finally, this work is evaluated compared to the current development status provided by a comprehensive outlook of possible technologies with existing commercial products based on the Field Programmable Gate Array (FPGA) tool. Technological advances have created new opportunities to strengthen education and improve the delivery of acquired Physical Education (PE) gaming skills. Determining Location Availability for Students with Practical Background Motion tracking systems can provide the right skills to support motor skills education in athletic teaching. © 2021

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