Volume 35, Issue 3 pp. 258-267
ORIGINAL ARTICLE

Correlation between intraosseous thermal change and drilling impulse data during osteotomy within autonomous dental implant robotic system: An in vitro study

Ruifeng Zhao

Ruifeng Zhao

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

Department of Stomatology, 960 Hospital of the Chinese People's Liberation Army, Jinan, Shandong, China

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Rui Xie

Rui Xie

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

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Nan Ren

Nan Ren

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

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Zhiwen Li

Zhiwen Li

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

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Shengrui Zhang

Shengrui Zhang

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

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Yuchen Liu

Yuchen Liu

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

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Yu Dong

Yu Dong

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

Department of Stomatology, Xi'an No.3 Hospital, the Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China

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An-An Yin

Corresponding Author

An-An Yin

Department of Plastic and Reconstructive Surgery, Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China

Correspondence

An-An Yin, Department of Plastic and Reconstructive Surgery, Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi, China.

Email: [email protected]

Yimin Zhao, State Key Laboratory of Military Stomatology, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

Shizhu Bai, Digital Dentistry Center, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

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Yimin Zhao

Corresponding Author

Yimin Zhao

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

Correspondence

An-An Yin, Department of Plastic and Reconstructive Surgery, Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi, China.

Email: [email protected]

Yimin Zhao, State Key Laboratory of Military Stomatology, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

Shizhu Bai, Digital Dentistry Center, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

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Shizhu Bai

Corresponding Author

Shizhu Bai

Digital Center, School of Stomatology, The Fourth Military Medical University, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Xi'an, Shaanxi, China

Correspondence

An-An Yin, Department of Plastic and Reconstructive Surgery, Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi, China.

Email: [email protected]

Yimin Zhao, State Key Laboratory of Military Stomatology, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

Shizhu Bai, Digital Dentistry Center, School of Stomatology, The Fourth Military Medical University, Changle west road 169, Xi'an, Shaanxi 710032, China.

Email: [email protected]

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First published: 29 November 2023
Citations: 4

Ruifeng Zhao, Rui Xie, and Nan Ren contributed equally to this work.

Abstract

Objectives

This study aims at examining the correlation of intraosseous temperature change with drilling impulse data during osteotomy and establishing real-time temperature prediction models.

Materials and Methods

A combination of in vitro bovine rib model and Autonomous Dental Implant Robotic System (ADIR) was set up, in which intraosseous temperature and drilling impulse data were measured using an infrared camera and a six-axis force/torque sensor respectively. A total of 800 drills with different parameters (e.g., drill diameter, drill wear, drilling speed, and thickness of cortical bone) were experimented, along with an independent test set of 200 drills. Pearson correlation analysis was done for linear relationship. Four machining learning (ML) algorithms (e.g., support vector regression [SVR], ridge regression [RR], extreme gradient boosting [XGboost], and artificial neural network [ANN]) were run for building prediction models.

Results

By incorporating different parameters, it was found that lower drilling speed, smaller drill diameter, more severe wear, and thicker cortical bone were associated with higher intraosseous temperature changes and longer time exposure and were accompanied with alterations in drilling impulse data. Pearson correlation analysis further identified highly linear correlation between drilling impulse data and thermal changes. Finally, four ML prediction models were established, among which XGboost model showed the best performance with the minimum error measurements in test set.

Conclusion

The proof-of-concept study highlighted close correlation of drilling impulse data with intraosseous temperature change during osteotomy. The ML prediction models may inspire future improvement on prevention of thermal bone injury and intelligent design of robot-assisted implant surgery.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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