臺灣博碩士論文加值系統

隨著臺灣已邁入超高齡化社會，目前罹患巴金森氏病(Parkinson's disease，PD)之病患人數約為10萬人。巴病患者常有步態不穩等問題，使行走較一般人困難許多，於上下樓梯時更是艱難；其中為了幫助患者復建過程能夠有效使臨床醫師和研究人員可以瞭解並追蹤患者，因此須提供量化後之患者復健數據。本研究目的為開發一套基於慣性測量單元的系統，利用5個感測器配戴於醫師指定之身體部位，測量關節的特徵角度，記錄與追蹤患者復健時的身體姿態。此系統主要分為三大部分，第一為感測器對步態資訊的收集；第二為透過Unity 3D平臺整合感測裝置蒐集之資訊並提供互動功能，能夠記錄、追蹤患者姿體資訊：如髖關節及膝關節屈曲(flexion)、伸直(extension)等，最後則是對蒐集步態資訊計算步長、步數等步態資訊。根據實驗分析結果顯示：受測者於上下樓梯時，與行走於平地時比較，有角度較大的髖關節屈曲和膝關節屈曲角度。另外，下樓梯膝關節所承受力量也較上樓梯時還要大。藉由實驗分析結果，本系統可記錄巴病患者上下樓梯時的量化數據，提供醫生判斷步態資訊，並讓醫生能夠從其步態資訊中，取得適合患者之最佳復健方式，進而建議患者能夠依照其指示來達到正確的復健姿勢。

As Taiwan has become an aging society, the number of patients suffering from Parkinson’s disease (PD) is about hundred thousand people. PD patients often have problems such as gait instability, which made walking more difficult than the normal persons. It is even more difficult when ascending and descending stairs. In order to help the patient’s reconstruction process effectively and enable clinicians and researchers to monitor and track patients, it is necessary to provide quantified patient rehabilitation data. This study proposes a system based on inertial measurement units, consisting of 5 sensors worn on specific areas recommended by the doctor, and calculate the human joint angles, which can effectively record, track, and assist patients in rehabilitation. This system is divided into three parts. First is the collection of gait information by the sensors, and the second is the information collected by the Unity 3D platform integrated sensing device and provides interactive functions to record and track patient posture information. For example, we can collect information about hip and knee flexion, extension, etc. Finally, gait information such as step sizes and number of steps are calculated for collecting gait information. According to the experimental results, when the subject was stair ascending and descending, compared with walking on the ground, the hip flexion and knee flexion angles were larger. In addition, the system can record the quantitative data of PD patients for stair ascending and descending, provide doctors to determine gait information, and allow doctors to obtain the best rehabilitation method for patients from their gait information. Then, physical therapists can recommend patients how to follow the instructions to achieve the correct rehabilitation posture.

摘　要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 viii
圖目錄 ix
第一章 緒論 1
1.1 研究背景 1
1.2 研究目的 2
1.3 研究方法 3
1.4 論文架構 4
第二章 相關技術及運用探討 5
2.1姿態表示方法 5
2.1.1 尤拉角(Euler angle) 5
2.1.3 方向餘弦矩陣 7
2.1.2 軸規範 8
2.3 基於DCM之九軸感測器應用 11
2.3.1 由陀螺儀描述姿態 11
2.3.2 由加速度計與磁力計描述姿態 11
2.3.3 整合演算法 11
2.4 微機電系統 13
2.4.1 加速度計(Accelerometer) 13
2.4.2 陀螺儀(Gyroscope) 14
2.4.3 磁力計(Magnetometer) 15
2.5 Arduino微控制器 17
2.6 資料通訊介面 17
2.6.1 I2C介面 17
2.6.2 UART介紹 17
2.7藍牙(Bluetooth)技術 18
2.8 Unity 3D遊戲引擎 18
第三章 系統架構設計 19
3.1系統架構 19
3.1.1系統硬體介紹 19
3.1.1.1 Arduino微控制器 20
3.1.1.2 藍牙模組 22
3.1.1.3 慣性感測器模組 23
3.1.1.4 74HC4067 CMOS 16通道類比數位訊號多工器 25
3.1.2 系統軟體介紹 26
3.2 系統硬體設計 27
3.2.1 九軸姿態感測裝置 28
3.2.2 資料接收器 29
3.2.3 穿戴方式 31
3.3 慣性動作捕捉系統 32
3.4 動作捕捉系統設計 33
3.4.1 開發環境介紹 33
3.4.1.1 Arduino開發環境 33
3.4.1.2 Unity開發環境 34
3.4.1.3 系統介面 35
3.4.2 感測器校正 36
3.4.2.1 加速度計校正 36
3.4.2.2 陀螺儀校正 37
3.4.2.3 磁力計校正 37
3.4.4 訊號傳輸 39
3.4.5 角度特徵 40
3.4.5.1 人體解剖平面 40
3.4.5.2 關節角度 41
3.4.6 檔案儲存格式 44
3.4.7 訊號濾波 45
3.4.8 直線步距量測 48
3.4.9 上下樓梯之生物力學 49
3.4.9.1 上樓梯膝關節受力 49
3.4.9.2 下樓梯膝關節受力 52
第四章 實驗設計與結果 53
4.1 實驗流程與環境 53
4.1.1 受測者 53
4.1.1 實驗環境 55
4.2 實驗方式介紹 56
4.2.1 直線步幅驗證 57
4.2.2 上樓梯實驗 59
4.2.3 下樓梯實驗 60
4.3 實驗結果 61
4.3.1 上樓梯實驗 61
4.3.2 下樓梯實驗 67
第五章 結論與未來展望 71
5.1 結論 71
5.2 未來展望 72
參考文獻 73

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