近年隨著穿戴式設備的發展，市面上越來越多穿戴式設備可以用以記錄使用者活動狀態，在眾多的穿戴式應用中，本論文專注於設計給予游泳愛好者使用之穿戴式應用，有別於目前偵測游泳資訊的穿戴式設備都是配戴於使用者的手腕，本論文的所使用之感測器則是配戴於使用者的後腦，並可與游泳者之泳鏡與泳帽搭配使用。本論文探討利用頭戴式穿戴式設備擷取游泳相關資訊，所設計之演算法能夠藉由頭戴式感測器所回報之加速度以及磁力計感測數據來判斷使用者的游泳相關數據，更明確的來說，我們透過抓取使用者非游泳狀態及游泳狀態的加速度感測器數據特徵來自動偵測使用者開始及結束游泳之時間點，並透過磁力感測器來判斷游泳轉身及計算游泳趟數，而加速度感測器的數據資料能用以判斷使用者的游泳姿勢，輔以所設計之峰值偵測法亦可以計算使用者之游泳划手次數。藉由上述所蒐集游泳相關資訊，能統整出使用者每趟游泳時間及游泳距離資訊。我們紀錄30位游泳愛好者之游泳數據來作為所設計之系統的參數訓練樣本，並邀請另外5位游泳程度不同的受試者來評估我們演算法的效能。由我們的實驗結果我們觀察到，所設計之系統已能正確的計算使用者的游泳趟數且能記錄使用者所有的游泳相關資訊，不過游泳時間、游泳划手次數和游泳姿勢的準確率還需要再提升，在未來我們會收集並觀察分析更多使用者的數據，透過調整本論文各個模組的參數，來提升使用者游泳相關資訊的準確率。

In recent years, with the development of wearable devices, more and more wearable devices on the market can be used to record the user's activity status. In many wearable applications, this paper focuses on designing wearable applications for swimming enthusiasts. Unlike the current wearable devices that detect swimming information, they are worn on the user's wrist. The sensor used in this paper is worn on the back of the user head and can be used with the swimmer's goggles and swimming cap. This thesis explores the use of head-mounted wearable devices to capture swimming-related information. The designed algorithm can determine the user's swimming related data by the acceleration reported by the head-mounted sensor and the magnetometer sensing data. Specifically, we automatically detect the time point at which the user starts and ends swimming by extracting the characteristics of the acceleration sensor data of the user's non-swimming state and swimming state, and determine the swimming turn and calculation through the magnetic sensor. The number of swimming strokes, and the data of the acceleration sensor can be used to determine the user's swimming style. The peak detection method can also calculate the number of swimming strokes by the user. Through the above-mentioned collection of swimming related information, the user's swimming time and swimming distance information can be integrated. We recorded swimming data from 30 swimmers as a parametric training sample for the designed system and invited five other subjects with different levels of swimming to assess the effectiveness of our algorithm. From our experimental results, we observed that the designed system has been able to correctly calculate the user's swimming parameters and can record all the swimming related information of the user, but the swimming time, the number of swimming strokes and the accuracy of the swimming style are also We need to upgrade again. In the future, we will collect and observe and analyze more users' data, and adjust the parameters of each module of this paper to improve the accuracy of users' swimming related information.

目錄
第一章 緒論	1
第二章 相關文獻	4
第三章 系統架構	7
第四章 演算法模組	11
4.1開始游泳偵測模組	11
4.1.1防開始偵測誤觸發模組	15
4.2划手次數偵測模組-峰值偵測法	17
4.2.1過濾非划手的波峰	22
4.3游泳方向變化偵測模組	24
4.3.1偵測游泳方向變化後的開始游泳偵測模組	28
4.4游泳休息偵測模組	29
4.5判斷游泳姿勢模組	30
第五章 實驗與評估	36
5.1 訓練資料	36
5.2 測試資料	37
第六章 結論	46
參考文獻	48
附錄-英文論文	50

圖目錄
圖表 1 系統架構	7
圖表 2 使用者開始游泳加速度數據波形	12
圖表 3 使用者游泳划手時的三軸感測器數值	17
圖表 4 使用者游泳划手時的三軸感測器和的數值	17
圖表 5 峰值偵測法噪聲	18
圖表 6 峰值偵測法流程圖	19
圖表 7 峰值偵測法區間示意圖	20
圖表 8 游泳划手補償	22
圖表 9 過濾非划手的波峰	23
圖表 10 磁力計變化量波形	25
圖表 11 磁力計角度數值波形	25
圖表 12 磁力計均值濾波法	26
圖表 13 使用者從游泳到站立休息波形圖	30
圖表 14 蝶式加速度數值波形	32
圖表 15 仰式加速度數值波形	33
圖表 16 蛙式加速度數值波形	34
圖表 17 自由式加速度數值波形	35
圖表 18 未調整參數的訓練樣本結果	37
圖表 19 評估標準	38
圖表 20 未調整參數的演算法的測試資料結果	40
圖表 21 調整演算法參數後的測試樣本結果	43

表目錄
表格 1 游泳姿勢準確率	43
表格 2 游泳時間誤差	44

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