Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7594
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dc.contributor.authorHeng, Pheng-Annen_US
dc.contributor.authorWong, Tien-Tsinen_US
dc.contributor.authorYang, Rongen_US
dc.contributor.authorChui, Yim-Panen_US
dc.contributor.authorXie, Yong Mingen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorLeung, Ping-Chungen_US
dc.date.accessioned2023-03-27T03:01:39Z-
dc.date.available2023-03-27T03:01:39Z-
dc.date.issued2006-
dc.identifier.citationIEEE Transactions on Information Technology in Biomedicine, 2006, vol. 10 (1), pp. 28 - 41en_US
dc.identifier.issn10897771-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7594-
dc.description.abstractThis paper presents an intelligent virtual environment for Chinese acupuncture learning and training using state-of-the-art virtual reality technology. It is the first step toward developing a comprehensive virtual human model for studying Chinese medicine. Students can learn and practice acupuncture in the proposed 3-D interactive virtual environment that supports a force feedback interface for needle insertion. Thus, students not only "see" but also "touch" the virtual patient. With high performance computers, highly informative and flexible visualization of acupuncture points of various related meridian and collateral can be highlighted to guide the students during training. A computer-based expert system using our newly proposed intelligent fuzzy petri net is designed and implemented to train the students to treat different diseases using acupuncture. Such an intelligent virtual reality system can provide an interesting and effective learning environment for Chinese acupuncture. © 2006 IEEE.en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Information Technology in Biomedicineen_US
dc.titleIntelligent inferencing and haptic simulation for Chinese acupuncture learning and trainingen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doi10.1109/TITB.2005.855567-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
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