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Wearable Product Design for Intelligent Monitoring of Basketball Training Posture Based on Image Processing
Author(s) -
Lei Zhang,
Yangjie Sun,
Meng Wang,
Pu Yan
Publication year - 2021
Publication title -
journal of sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.399
H-Index - 43
eISSN - 1687-7268
pISSN - 1687-725X
DOI - 10.1155/2021/8964433
Subject(s) - basketball , wearable computer , software , product (mathematics) , training (meteorology) , computer science , multimedia , human–computer interaction , wearable technology , simulation , artificial intelligence , embedded system , geometry , mathematics , archaeology , meteorology , history , programming language , physics
The algorithms of wearable image processing technology equipment have certain versatility and can be widely used in popular fields such as medical treatment, factories, drone development, human-computer interaction, virtual reality, and physical education. In order to deeply study the monitoring effect of smart wearable products based on the image processing technology on basketball training postures, this article uses the product manual comparison method, data collection method, and equipment development method to collect samples and analyze and develop intelligent monitoring equipment, streamlined algorithm. And it integrated and developed a wearable product that can monitor athletes’ training posture in real time during basketball training. After the product was researched, the training program of the product was used for low-handed dribbling. The first training lasted for 3 minutes and 10 seconds, and the second training lasted for 2 minutes and 45 seconds. The prototype and manual dribbles were studied in these two cases. The results showed that the prototype reminded the participants 31 times, while the coach only reminded them 13 times due to the large number of people. By comparing the satisfaction scores of the fitness software and the products developed in this article, the score ranges from 1 to 5 points, which is very consistent with the score of 5, and it is very inconsistent with the score of 1. Through the trial of this scene, positive information was obtained. The evaluation of the prototype is generally above that of the fitness software. The number of people eager to use the prototype again is 10 times more than that of the fitness software. These data are from the first combination chart and the third combination chart. The corresponding explanations and experimental methods will be introduced in the description of these two combination charts later. The prototype can widely cater to the public’s sport preferences. It is basically realized that starting from the image processing technology, a smart monitoring wearable product with high evaluation and good effect has been designed.

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