Evidence map›Paper›PMID 36418763›Full record

ArticleInternational journal of computer assisted radiology and surgery2023

A virtual surgical prototype system based on gesture recognition for virtual surgical training in maxillofacial surgery.

Hanjiang Zhao, Mengjia Cheng, Jingyang Huang, Meng Li, Huanchong Cheng, Kun Tian, Hongbo Yu

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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hanjiang Zhao *Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Mengjia Cheng *Department of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Jingyang HuangDepartment of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Meng LiDepartment of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, No. 639 Zhizaoju Road, Shanghai, 200011, China.
Huanchong ChengSchool of Mechanical and Power Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Shanghai, 200240, China.
Kun TianDepartment of Stomatology, The First Hospital of Zibo, Zibo, 255200, Shandong Province, China. K120110@163.com.
Hongbo YuDepartment of Oral and Cranio-Maxillofacial Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, No. 639 Zhizaoju Road, Shanghai, 200011, China. yhb3508@163.com.ORCID http://orcid.org/0000-0001-8147-7246

Funding

National Natural Science Foundation of China 81571022
6 · The paper itself

Abstract

backgroundVirtual 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.

methodGesture 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.

resultsTen 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.

conclusionBased 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.

Indexed as

GesturesSurgery, OralAlgorithmsAnimalsHandMiceSoftwareUser-Computer InterfaceCollision detectionGesture recognitionVirtual realityVirtual surgery

Identifiers

PMID36418763
PMCPMC10113313

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.