A virtual surgical prototype system based on gesture recognition for virtual surgical training in maxillofacial surgery
Rattachement africain : cn, us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
BACKGROUND: Virtual reality (VR) technology is an ideal alternative of operation training and surgical teaching. However, virtual surgery is usually carried out using the mouse or data gloves, which affects the authenticity of virtual operation. A virtual surgery system with gesture recognition and real-time image feedback was explored to realize more authentic immersion. METHOD: Gesture recognition technology proposed with an efficient and real-time algorithm and high fidelity was explored. The recognition of hand contour, palm and fingertip was firstly realized by hand data extraction. Then, an Support Vector Machine classifier was utilized to classify and recognize common gestures after extraction of feature recognition. The algorithm of collision detection adopted Axis Aligned Bounding Box binary tree to build hand and scalpel collision models. What's more, nominal radius theorem (NRT) and separating axis theorem (SAT) were applied for speeding up collision detection. Based on the maxillofacial virtual surgical system we proposed before, the feasibility of integration of the above technologies in this prototype system was evaluated. RESULTS: Ten kinds of signal static gestures were designed to test gesture recognition algorithms. The accuracy of gestures recognition is more than 80%, some of which were over 90%. The generation speed of collision detection model met the software requirements with the method of NRT and SAT. The response time of gesture] recognition was less than 40 ms, namely the speed of hand gesture recognition system was greater than 25 Hz. On the condition of integration of hand gesture recognition, typical virtual surgical procedures including grabbing a scalpel, puncture site selection, virtual puncture operation and incision were carried out with realization of real-time image feedback. CONCLUSION: Based on the previous maxillofacial virtual surgical system that consisted of VR, triangular mesh collision detection and maxillofacial biomechanical model construction, the integration of hand gesture recognition was a feasible method to improve the interactivity and immersion of virtual surgical operation training.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A virtual surgical prototype system based on gesture recognition for virtual surgical training in maxillofacial surgery
- Date Crossref
- 23/11/2022
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Shanghai Jiao Tong University Department of Oral and Cranio-Maxillofacial Surgery pays non établi dans la noticeUniversité ou école supérieure
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Shanghai Ninth People's Hospital pays non établi dans la noticeÉtablissement de santé
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National Clinical Research pays non établi dans la noticeStructure de recherche
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Central Hospital of Zibo pays non établi dans la noticeÉtablissement de santé
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College of Stomatology pays non établi dans la noticeUniversité ou école supérieure
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National Center for Stomatology pays non établi dans la noticeInstitution
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Shanghai Key Laboratory of Stomatology pays non établi dans la noticeStructure de recherche
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School of Mechanical and Power Engineering pays non établi dans la noticeUniversité ou école supérieure
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The First Hospital of Zibo Department of Stomatology pays non établi dans la noticeÉtablissement de santé
Department of Oral and Cranio-Maxillofacial Surgery — Shanghai Jiao Tong University, Shanghai Ninth People's Hospital et National Clinical Research, avec 6 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.