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  1. 学術雑誌論文
  2. 5 技術(工学)

Static Hand Gesture Recognition Based on Multi-Feature Extraction with Context for User Intension

http://hdl.handle.net/10228/0002001276
http://hdl.handle.net/10228/0002001276
41b7340a-d291-470d-8d25-890471c97440
名前 / ファイル ライセンス アクション
10448090.pdf 10448090.pdf (625 KB)
アイテムタイプ 共通アイテムタイプ(1)
公開日 2025-02-10
タイトル
タイトル Static Hand Gesture Recognition Based on Multi-Feature Extraction with Context for User Intension
言語 en
その他のタイトル
その他のタイトル STATIC HAND GESTURE RECOGNITION BASED ON MULTI-FEATURE EXTRACTION WITH CONTEXT FOR USER INTENSION
言語 en
著者 Ahmad, Khawaritzmi Abdallah

× Ahmad, Khawaritzmi Abdallah

en Ahmad, Khawaritzmi Abdallah

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Silpani, Dian Christy

× Silpani, Dian Christy

en Silpani, Dian Christy

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吉田, 香

× 吉田, 香

WEKO 27669
e-Rad_Researcher 60315174
Scopus著者ID 35321688600
九工大研究者情報 190

en Yoshida, Kaori

ja 吉田, 香

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著作権関連情報
権利情報 ICIC International Copyright (c) 2024
抄録
内容記述タイプ Abstract
内容記述 Dressing is a critical component of Activity of Daily Living (ADLs). The development of assistive technology for dressing tasks is urgently needed from the viewpoint of privacy, for example, to prevent the wearer from being seen in the nude. Despite their importance, these technologies are underutilized in garment donning compared to other ADLs. The reasons for the lack of utilization of assistive technology are that the task is complex, as it involves handling individuals with large individual differences in height and symptoms and requires manipulation of flexible clothing. Addressing these variances presents a formidable academic challenge. Our previous study identified periodic patterns in human movements during robot-assisted dressing and noted individual variability in these patterns. Capitalizing on this finding, we propose a novel control strategy for a robot that adapts to individual needs during dressing, employing the "Assist-As-Needed" (AAN) principle from physical therapy. The proposed control method uses Central Pattern Generators (CPG) that can be synchronously controlled in response to external forces, enabling model-free control without human modeling.
We utilize the Rowat-Selverston CPG model, which is recognized for its adaptive response to human motions in human-robot interactions such as with handshaking robots. A simulator of the Rowat-Selverston CPG was created. The output of the CPG was confirmed by inputting the data set obtained in previous studies, and the parameters were adjusted. The CPG output was then applied to the recorded target joint trajectory for the dressing assistance. We prepared a replay of the default trajectory, a trajectory with simple harmonic motion applied, and a trajectory with CPG output applied, and confirmed whether individual adaptation according to the AAN was possible through subject experiments. The experimental results showed that the Rowat-Selverston CPG control method enables individual adaptive dressing assistance according to the AAN principle. This study summarizes these methods and results and contributes to the realization of an individually adaptive system that follows the AAN principle, especially in developing assistive technology.
言語 en
書誌情報 en : ICIC Express Letters, Part B: Applications

巻 15, 号 8, p. 779-786, 発行日 2024-08
出版社
出版者 ICIC International
言語 en
キーワード
主題Scheme Other
主題 Human-Robot Interaction
キーワード
主題Scheme Other
主題 AAN principle
キーワード
主題Scheme Other
主題 Dressing Assistance Robot
キーワード
主題Scheme Other
主題 Rowat-Selverston CPG
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
識別子タイプ DOI
関連識別子 https://doi.org/10.24507/icicelb.15.08.779
ISSN
収録物識別子タイプ PISSN
収録物識別子 2185-2766
研究者情報
URL https://hyokadb02.jimu.kyutech.ac.jp/html/190_ja.html
論文ID(連携)
値 10448090
連携ID
値 12927
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