| 研究生: |
陳奕璋 Chen, Yi-Zhang |
|---|---|
| 論文名稱: |
穴道定位技術使用虛擬實境實現於智慧型手機 Localization of Acupoints on a Smartphone using Augmented Reality |
| 指導教授: |
藍崑展
Lan, Kun-chan |
| 共同指導教授: |
胡敏君
Hu, Min-Chun |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 資訊工程學系 Department of Computer Science and Information Engineering |
| 論文出版年: | 2017 |
| 畢業學年度: | 105 |
| 語文別: | 英文 |
| 論文頁數: | 35 |
| 中文關鍵詞: | 擴增實境 、穴道 、穴位 、穴位預估 、3D變形模型 、臉部對齊 、影像變形 |
| 外文關鍵詞: | Augmented Reality, Acupoint, Acupoint Estimation, 3D Morphable Model, Face Alignment, Image Deformation |
| 相關次數: | 點閱:107 下載:1 |
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中醫針灸與穴位按摩是中醫常用的療法,根據病患不同症狀可以針對對應的穴位做針灸或穴位按摩來緩解病患症狀。由於有龐大的穴位點的數量,並且穴位點有多樣化、複雜性與專一性,除非經由一段時間的專業訓練,常人很難記得每個穴位點的位置以及對應的治療用途。我們系統藉由擴真實境,穴位點會顯示在人體的輸入影像上,相比傳統使用穴位點量測電阻值,我們的系統透過軟體的方式,使用已有的智慧型手機,不需要額外的硬體支出。在輕微症狀如頭痛、睡眠障礙,透過我們的系統能幫助病人快速定位穴位點用於按摩達到緩解症狀,而不需中醫專家的幫助。我們的提出新的穴位預估系統以人臉為範例,利用人臉特徵標記點和3D變形模型達到可以適應不同臉型與臉部角度,在預估穴位的精準度方面,提出的系統比起現有的系統提昇高達170%之多。系統也被實作在Android平台上,以展示真實的穴位應用用於緩解症狀。
Acupuncture therapy is one of the main modalities of treatment in Traditional Chinese Medicine (TCM). Based on the different symptoms of the patient, needling or massaging is applied to the corresponding acupuncture points to relieve the symptoms. However, given that the large number of acupuncture points and the complexity of their specificity, it is difficult for one to remember the location and purpose of each acupuncture point without a period of professional training. In our system, through the use of augmented reality, the acupuncture points will be displayed directly on the image of human body. Compared to the traditional acupoint probe devices that work by measuring the skin conductivity, our system does not require any additional hardware and is purely software-based. In the case of mild symptoms (e.g. headache, sleep disorder), with the aid of our proposed system, the patient can quickly locate the corresponding acupuncture points for the application of massage, and relieve his/her symptoms without the the help from TCM physicians. We proposed a new approach for acupoints estimation, human face is taken as an example in our work, we leverage the facial landmark points and the 3D morphable model (3DMM), and have shown the proposed system is capable of estimating acupoints on different face shapes with various input face angles, the tracking mechanism is added to mitigate face detection failure when some of the face area is occluded by hand when do the acupuncture. Our system is shown to outperform the existing work by 170% in terms of estimation precision. A prototype system based on Android is also presented to demonstrate the application of real-life symptoms relief.
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校內:2022-08-31公開