臺灣博碩士論文加值系統

這些年來醫療技術的進步，老年人口比例提升，現代人越來越重視生活品質，其中老化是高齡化社會必須面對的課題。隨著身體老化器官會慢慢退化，而適當的運動可以減緩退化症狀並且預防重大疾病，並且提升生活品質，減少老人醫療的支出。傳統檢測體適能的方式由於採用人工方式來進行處理，測驗過程中既耗時又耗費人力，需要查看測驗者的身分，測驗後又需要登記測驗的結果，造成看護人員的負擔。開發一個良好的老年體適能系統，可以有效的減少看護人員的人力與時間。
本研究以景深攝影機實現老年人體適能檢測與管理的系統，可以自動取得雲端上的個人資料，讓老年人不管是在居家或是社區福利機構都可以直接檢測，並利用景深攝影機使用臉部辨識功能來檢測老年人的生物特徵進行系統登入，結合Nuitrack SDK進行骨架的偵測與追蹤開發出適合老年人的人機互動介面。接著將測驗結果的資料上傳至網頁生成圖表可以方便老年人自身或看護人員管理老年人的體能是否有上升或下降的趨勢。

In recent years, the advancement of medical technology is getting better. Elderly people proportion is increase. Modern people care more about the quality of life, and ageing is an issue that an ageing society have to face. Since the organs will gradually degenerate as the body ages, appropriate exercise can relieve the symptoms of degradation and prevent major diseases, and improve the quality of life and reduce the medical expenses of the elderly. Because the traditional method of doing a physical fitness test is processed manually, the test process is time-consuming and labor-intensive. Caretakers have to verify the identity of each test taker and to register the result of the test after the test, which cause the burden on them. Developing a great physical fitness system of the elderly can effectively reduce the manpower and time of caretakers.
The study uses the depth-of-field camera to implement a system for the detection and management of physical fitness of the elderly, which can automatically obtain personal data on the cloud that makes the elderly can be directly detected at home or in community welfare agencies. In this study, the depth-of-field camera was used to detect the biosignatures of the elderly by using the facial recognition function to log in to the system, and Nuitrack SDK was used to detect and track the skeleton to develop a human-machine interactive interface suitable for the elderly. Afterwards, uploading the data of the test results to the web page to generate charts can facilitate the elderly or their caretakers to manage whether there is an upward or downward trend toward the physical fitness of the elderly.

摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 3
1.3論文架構 4
第二章 文獻與技術探討 5
2.1相關文獻 5
2.1.1人機互動技術的發展 5
2.2相關技術 7
2.2.1臉部辨識技術 7
2.2.2立體深度視覺 9
2.2.3 PHP(超文字預處理器) 10
2.2.4 MySQL 10
第三章 系統功能與設計 11
3.1系統簡介 11
3.2系統架構圖 11
3.3開發環境 12
3.3.1迷你電腦 12
3.3.2景深攝影機 13
3.3.3骨架追蹤 15
3.4老年人功能性體適能檢測項目 17
3.5 骨架姿勢動作研判 19
3.6體適能測量標準 29
第四章 實作與測試 32
4.1系統流程 32
4.2介面設計 33
4.3 功能實測 35
4.3.1 測驗者資料登記 35
4.3.2 新增臉部照片 37
4.3.3 臉部辨識登入 39
4.3.4 30秒椅子坐立測量 41
4.3.5 30秒肩關節測量 43
4.3.6 60秒站立抬膝測量 48
4.3.7 1.5秒坐立繞物測量 53
4.3.8 30秒二頭肌手臂屈舉測量 56
4.3.9 2分鐘單足立 58
4.3.10 測量評價 61
4.3.11 網頁圖表功能 61
4.3.12 臉部辨識效能測試 62
4.3.13 使用者滿意度調查 63
第五章 結論與未來展望 63
參考文獻 65

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