| DOI | Resolve DOI: https://doi.org/10.1007/s10489-020-01910-1 |
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| Author | Search for: Cheng, Qiangqiang1; Search for: Sun, Pengyu1; Search for: Yang, Chunsheng1; Search for: Yu, Runqiao1; Search for: Liu, Peter Xiaoping |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Article |
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| Subject | virtual surgery; haptic interaction; cutting force simulation; artificial intelligence; particle filtering |
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| Abstract | An accurate and realistic force feedback is very important in determining the realism of virtual surgery. In order to improve the accuracy of force simulation in cutting procedures, we proposed a novel method for forecasting and simulating the cutting force based on a particle filtering (PF) technique. Since the probability density function (PDF) is represented by particles, it is able to estimate accurately the interaction force between the surgical tool and soft tissue during cutting processes. The root mean square error (RMSE) of the PF-based method ranges from 0.0014 to 0.0034, and the mean absolute error (MAE) is less than 0.0399. Comparison of the experiment results with other methods demonstrated that the PF-based method can achieve a higher accuracy with different cutting speeds and angles. The application of the PF-based method to a virtual liver cutting procedure confirmed the effectiveness and accuracy of this method. |
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| Publication date | 2020-10-20 |
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| Publisher | Springer Nature |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 27392e4b-725c-4e27-854e-9ca4ee207615 |
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| Record created | 2020-11-19 |
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| Record modified | 2020-11-30 |
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