Evidence map›Paper›PMID 31300964›Full record

ArticleInternational journal of computer assisted radiology and surgery2019

The development of non-contact user interface of a surgical navigation system based on multi-LSTM and a phantom experiment for zygomatic implant placement.

Chunxia Qin, Xingchen Ran, Yiqun Wu, Xiaojun Chen

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Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. 3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.International journal of computer assisted radiology and surgery · 2023
    Article
  2. Article
  3. A Novel Guided Zygomatic and Pterygoid Implant Surgery System: A Human Cadaver Study on Accuracy.International journal of environmental research and public health · 2021
    Article
  4. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chunxia QinSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xingchen RanCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Zhejiang, China.
Yiqun WuShanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaojun ChenRoom 805, School of Mechanical Engineering, Shanghai Jiao Tong University, Dongchuan Road 800, Minhang District, Shanghai, 200240, China. xiaojunchen@sjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeImage-guided surgical navigation system (SNS) has proved to be an increasingly important assistance tool for mini-invasive surgery. However, using standard devices such as keyboard and mouse as human-computer interaction (HCI) is a latent vector of infectious medium, causing risks to patients and surgeons. To solve the human-computer interaction problem, we proposed an optimized structure of LSTM based on a depth camera to recognize gestures and applied it to an in-house oral and maxillofacial surgical navigation system (Qin et al. in Int J Comput Assist Radiol Surg 14(2):281-289, 2019).

methodsThe proposed optimized structure of LSTM named multi-LSTM allows multiple input layers and takes into account the relationships between inputs. To combine the gesture recognition with the SNS, four left-hand signs waving along four directions were designed to correspond to four operations of the mouse, and the motion of right hand was used to control the movement of the cursor. Finally, a phantom study for zygomatic implant placement was conducted to evaluate the feasibility of multi-LSTM as HCI.


results3D hand trajectories of both wrist and elbow from 10 participants were collected to train the recognition network. Then tenfold cross-validation was performed for judging signs, and the mean accuracy was 96% ± 3%. In the phantom study, four implants were successfully placed, and the average deviations of planned-placed implants were 1.22 mm and 1.70 mm for the entry and end points, respectively, while the angular deviation ranged from 0.4° to 2.9°.

conclusionThe results showed that this non-contact user interface based on multi-LSTM could be used as a promising tool to eliminate the disinfection problem in operation room and alleviate manipulation complexity of surgical navigation system.

Indexed as

User-Computer InterfaceGesturesHumansModels, TheoreticalOperating RoomsPhantoms, ImagingProstheses and ImplantsProsthesis ImplantationSurgery, Computer-AssistedZygomaDepth cameraGesture recognitionSurgical navigation systemZygomatic implants

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Registered trials

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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.