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 theory and practice. It is different from the 107-year sports communication content combined with social data analysis teaching course. The preliminary [109-1] Sports and Health Big Data Application will be planned and combined with various government campaigns. Data sources and online communities, introducing data collection crawler technology , and then teach text analysis statistical techniques, and finally combine it with popular geographical mapping technology, allowing students to freely create the required sports community maps for actual sports activities. This course serves as the basis of this course and can be smoothly connected to this course. Course [109-2] Yunjian Internet of Things Application and Analysis. This course is an intermediate-to-high-level course. It first introduces the principles of exercise physiology, with special emphasis on knowledge related to muscle movement. Then it introduces the exercise physiology measurement IoT device, and then introduces the measurement principles, especially the correlation with human physiology. Then Introduce artificial intelligence big data analysis and learning technology, and Combined with cloud computing for resource sharing; and then learn to use IoT data to measure and predict sports physiological reactions, such as fatigue and injury occurrences. Finally, an industry-university collaboration presentation will be conducted on athlete performance analysis and evaluation proposed by the industry, allowing students to understand the application of sports big data. importance and its application to the sports industry. After graduation, students can combine sports theory to promote sports practice, which will be of great help to 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 ECG Reader (Qiu Chanfen) Huaxing Bookstore
2. Sports Science and Training/Lin Changshang/Yinhe Cultural Enterprise Company
3. Deep Learning: Basic theoretical implementation of deep learning with Python/O'Reilly Press
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 實作一實作一 Implementation 1 |
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 Practice 2 |
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 Practice 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 topic |
30 |
