Title: Acquiring and processing movement information from various sources using intelligent AI cognitive model for sports activities

Authors: Yingqing Guo; Xin Wang

Addresses: School of Physical Education, Shandong University, Ji'nan, Shandong, 250000, China ' School of Physical Education, Liaocheng University, Liaocheng, Shandong, 252059, China

Abstract: The overarching purpose of this research is to demonstrate the value of artificial intelligence (AI) strategies in sports for utilising weight lifting policies. In specific, the work centred on the use of pattern recognition techniques to test training system exercises conducted for weight lifting policies. To quantify critical displacement and strength, the determinants during workouts has the data acquisitions that have been carried out using optimised force sensors linked with different weight machines. Consequently, certain essential properties such as time intervals or travel rates may be deduced based on the data collected using artificial intelligence (AI) techniques. These parameters have been used to create smart methods that adapt traditional machine learning principles for automatic evaluation of the exercise technique and provide adequate feedback. The obtained modelling results showed good performance and forecast results, which indicated the feasibility and the capacity of AI techniques when automatically measuring performance on weight training equipment has been analysed.

Keywords: artificial intelligent; machine learning; cognitive; sports.

DOI: 10.1504/IJTM.2021.118317

International Journal of Technology Management, 2021 Vol.86 No.2/3/4, pp.110 - 124

Received: 19 Jun 2020
Accepted: 23 Nov 2020
Published online: 20 Oct 2021 *

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