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篇名 |
A Low-cost Mobile Real-time Monitoring System for Analyzing Head Position and Breathing Patterns in Front Crawl Swimming
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並列篇名 | A Low-cost Mobile Real-time Monitoring System for Analyzing Head Position and Breathing Patterns in Front Crawl Swimming |
作者 | Cheng-Chang Jeng |
英文摘要 | Swimming posture analysis usually requires video-based equipment with high installation costs and time-consuming data processing. Wireless transmission and real-time monitoring data, by contrast, are much desired by swimming coaches, learners, and athletes. The objective of this study aims to modify an inertial measurement unit (IMU) using the Bluetooth Low Energy (BLE) wireless communication protocol and place it on the back of the swimmer’s head to measure the pitch and roll of the head during front crawl swimming. The data obtained from an IMU can be monitored on an Android mobile device in real time, stored in the mobile device’s built-in memory, and later uploaded to Google Drive for post analysis. An algorithm was also developed for counting the number of breaths taken to the left and to the right for breathing pattern analysis. To verify the feasibility of the proposed system, a case study was performed in which two swimmers of different abilities wore the proposed device while front crawl swimming. Analysis of the data obtained from the two swimmers indicates that the proposed system can successfully identify the pitch and roll angles of the head, while the proposed algorithm counts the number of breaths taken to the left and to the right. Further analysis of the descriptive statistics of the pitch and roll angles reveals the differences between the head position of the two swimmers when they took a breath during front crawl swimming, thereby providing the coaches and swimmers with objective reference data to help them improve their swimming technique and verifying the feasibility of the system developed in this study. |
起訖頁 | 008-022 |
關鍵詞 | Bluetooth Low Energy、inertial measurement unit、front crawl swimming、breathing pattern |
刊名 | 電腦學刊 |
期數 | 202104 (32:2期) |
DOI |
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