博碩士論文 108526018 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator胡瑄zh_TW
DC.creatorHsuan Huen_US
dc.date.accessioned2022-8-1T07:39:07Z
dc.date.available2022-8-1T07:39:07Z
dc.date.issued2022
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=108526018
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract隨著人口老齡化,衰弱症的問題越來越嚴重。許多研究指出,運動可以有效減緩衰弱症狀。與劇烈運動相比,八段錦相當適合衰弱症患者。它由八個簡單的動作組成。許多物理治療師也使用這種常見的氣功來訓練體弱的病人。為了給他們提供更好的訓練方法,本文提出了一種輕量級的基於家庭的衰弱症訓練系統。在系統中,我們設計了一個虛擬八段錦教練。為了達到輕量化的目的,我們使用網路攝影機作為主要設備。該系統還支持 Kinect 框架。我們使用姿勢估計和運動識別方法來分析使用者的運動。除此之外我們提出了一種新的遷移學習方法。我們設計了一個名為“Skeleton Mapnet”的映射模型。其目的是轉換不同框架的骨架數據。該方法使不同框架的數據集能夠共享分類模型。它還可以混合不同框架的骨架數據,解決網路攝影機數據集的不足。這樣的設計提供了系統輕鬆移植到其他平台的能力。此外,該系統還適用於物聯網人工智能的使用。它可以使衰弱症的患者更容易學習和操作。zh_TW
dc.description.abstractThe problem of frailty is becoming more and more serious with the aging of the population. Many studies have pointed out that exercise can effectively slow down frailty. Compared with vigorous exercise, Baduanjin is quite suitable for frailty patients. It is a traditional Chinese qigong and consists of eight simple movements. Many physical therapists also use this exercise for training frailty patients. To provide them with a better training method, this paper proposes a lightweight family-based frailty training system. In the system, we designed a virtual Baduanjin coach. To achieve the purpose of being lightweight, we use a webcam as the main device. The system also supports the Kinect framework. We use pose estimation and motion recognition methods to analyze the user′s movements. In addition, a novel transfer learning method is proposed. We designed a mapping model called "Skeleton Mapnet". Its purpose is to convert skeleton data of different frameworks. This method enables datasets of different frameworks to share classification models. It can also mix skeleton data of different frameworks to solve the lack of webcam datasets. Such a design provides the ability of the system to be easily ported to other platforms. In addition, the system is also suitable for the use of the Artificial Intelligence of Things. It can make it easier for frailty patients to learn and operate.en_US
DC.subject衰弱症zh_TW
DC.subject虛擬現實zh_TW
DC.subject姿態估算zh_TW
DC.subject動作辨識zh_TW
DC.subject遷移式學習zh_TW
DC.subjectFrailtyen_US
DC.subjectVirtual Realityen_US
DC.subjectPose Estimationen_US
DC.subjectAction Recognitionen_US
DC.subjectTransfer Learningen_US
DC.title使用映射模型和跨資料集遷移式學習的輕量化居家衰弱症訓練系統zh_TW
dc.language.isozh-TWzh-TW
DC.titleA Lightweight Home-Based Frailty Training System using Mapping Model and Cross-Dataset Transfer Learningen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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