為了瞭解與研究腦波專注度與放鬆度於運動的影響與運動結合科技趨勢，本研究使用偵測腦波裝置與開發設計行動裝置的Android應用程式結合Azure雲端平台進行資料蒐集與即時監控以及運算分析，並且實作觀察心率的感測設備。最後，透過三種運動項目進行實驗，分別是健走、慢跑、飛輪，蒐集運動者運動時配戴穿戴式腦波裝置所偵測的腦波專注度及放鬆度之數據進行機器學習的預測，預測運動時的專注度與放鬆度。實驗結果，慢跑運動時專注度與放鬆度略為提升，健走與飛輪運動時專注度處於中等，而放鬆度中等略高。
Exercise has become an important indicator which people are in pursuit of health. Attention and meditation are the issues between busy modern people. It’s the better choice to improve the emotion by doing exercise, whatever mental state like absent-minded, life stress or depression. With the development of big data and IoT, it’s combined with exercise and technology. Through using the wearable technology device, make large of data combined with Cloud for storage and analysis to find out the value of information for exercise.
In order to understand the impact of attention and meditation in exercise and know the trend of exercise and technology combined. In this study, using brainwave detection device and developing the Android apps, after that, combining Azure cloud platform for real-time monitoring, data collection and analysis operations, moreover, implementation observed in heart rate sensing device. Finally, select the data during walking, jogging and flywheel to predict in machine learning, then to forecast the attention and meditation. The results of the experiment showed that the attention and meditation of jogging were slightly improved, while the attention was moderate and the meditation was moderately high in walking and flywheel.
