本課程為結合理論與實務之課程，有別於107年度之運動傳播內容結合社群數據分析教學課程，初階[109-1]運動健康大數據應用將有計畫性地結合各種政府運動開放資料來源及網路社群，介紹數據收集爬蟲技術，進而教授文本分析統計技術，最後結合流行之地理圖資技術，讓學生可以自由創作所需之運動社群地圖，供實際運動活動所需，此課程作為本課程之基礎，可以順利連接至本課程之[109-2]運健物聯網應用與分析。本課程為中高階內容，首先對運動生理原理進行介紹，尤其重視肌肉運動相關知識，接著介紹運動生理量測物聯裝置，進而介紹量測原理，特別對與人體生理之關聯性進行介紹，接著介紹人工智慧大數據分析學習技術，並結合雲端運算進行資源共享；進而學習以物聯數據量測預測運動生理反應，如疲勞及傷害之發生，最後以業界出題之運動員表現分析評估進行產學合作專題呈現，讓學生了解運動大數據應用的重要性，並應用到運動產業。使學生畢業後可以結合運動理論進行運動實務推廣，對國民之健康有莫大的助益。This course is a course that combines reasonable discussion and practice. It has the sports broadcast content combined with community data analysis teaching course in 2010. Initial [109-1] Sports Health Data Application will plan to combine various government sports and open up Data sources and online communities, introducing data collection and crawling technology , then teach text analysis statistical techniques, and finally combine popular geographical maps to allow students to freely create required sports community maps for the needs of international sports activities. This course serves as the foundation of this course and can be successfully connected to this course. Course [109-2] Health Network Application and Analysis. This course is a medium and high-level content. First, it introduces the physiological principles of sports, especially the knowledge related to muscle movement. Then it introduces the physiological physiological measurement device of sports, and then introduces the principle of quantification measurement, and specifically introduces the correlation with human physiology. Introduction to the AI large data analysis and learning technology, and Combining cloud computing for resource sharing; then learning to predict sports physiological reactions based on material-connected data, such as fatigue and damage, and finally, the topic of industry cooperation is presented through sports performance analysis and evaluation, so that students can understand the application of sports data and apply to the industry. This will enable students to combine sports management discussions to promote sports practice after graduation, which will greatly benefit the health of the people.
1、 簡易心電圖讀本(邱艶芬)華杏書局
2. 運動科學與訓練/林正常/銀禾文化事業公司
3. Deep Learning：用Python進行深度學習的基礎理論實作/歐萊禮出版社
1. Simple and easy-to-sense electronic picture book (Qiu Xiaofen) Hua Xing Book Bureau
2. Sports Science and Training/Lin Guan/Yanhe Cultural Affairs Company
3. Deep Learning: Basic Theory Implementation for In-depth Learning in Python/Olexun Publishing House
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 實作一實作一 Make a |
20 | 第一次作業配合第一階段練習運動生理專業概念， |
| 期中考期中考 Midterm exam |
10 | |
| 實作二實作二 Acting Two |
20 | 第二次作業配合第二階段練習物聯網生理量測裝置數據收集設計如Arduino及Garmin， |
| 實作三實作三 Implementation Three |
20 | 第三次作業配合第三階段練習運動大數據處理工具(Python+Kibana)， |
| 期末專題期末專題 Final topics |
30 |
