A force-sensing semi-automated robotic needle driver for minimally invasive surgery

Armin Ehrampoosh; Bijan Shirinzadeh; Joshua Pinskier; Julian Smith; Randall Moshinsky; Yongmin Zhong

doi:10.1109/ICMT56556.2022.9997789

A force-sensing semi-automated robotic needle driver for minimally invasive surgery

Armin Ehrampoosh, Bijan Shirinzadeh, Joshua Pinskier, Julian Smith, Randall Moshinsky, Yongmin Zhong

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

1 Citation (Scopus)

Abstract

Teleoperated robotic surgery systems have enhanced surgical operations' efficiency. However, these systems have limitations, such as lack of force feedback to the surgeon and complicated manipulation for tasks such as suturing. In this paper, a force-sensing instrument is presented with a robotic needle driver that facilitates suturing. A rotating degree of freedom (DOF) enables the cable-driven end-effector to insert the needle through its curvature. Moreover, an indirect force estimation approach was developed to approximate the needle-tissue interaction force. A mapping between robot sensors' data and target interaction force was created using a data-based model. Next, experimental evaluations of the proposed instrument were conducted. According to the experimental results, the generated trajectory had a root mean square error (RMSE) of 0.59 mm and the accuracy of the force estimation model was 0.21 N RMSE. In conclusion, these results demonstrate the potential of the proposed instrument for bilateral control systems.

Original language	English
Title of host publication	ICMT 2022 - 25th International Conference on Mechatronics Technology
Editors	Yung-Tien Liu, JJ Chong, Trung Quang Dinh
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781665461955
DOIs	https://doi.org/10.1109/ICMT56556.2022.9997789
Publication status	Published - 2022
Event	International Conference on Mechatronics Technology 2022 - Kaohsiung, Taiwan Duration: 18 Nov 2022 → 21 Nov 2022 Conference number: 25th https://ieeexplore.ieee.org/xpl/conhome/9997567/proceeding (Proceedings)

Conference

Conference	International Conference on Mechatronics Technology 2022
Abbreviated title	ICMT 2022
Country/Territory	Taiwan
City	Kaohsiung
Period	18/11/22 → 21/11/22
Internet address	https://ieeexplore.ieee.org/xpl/conhome/9997567/proceeding (Proceedings)

Keywords

Data-based Force model
Force measurement
Medical Instrumentation
Robotic-assisted minimally invasive surgery (RAMIS)

Access to Document

10.1109/ICMT56556.2022.9997789

Cite this

Ehrampoosh, A., Shirinzadeh, B., Pinskier, J., Smith, J., Moshinsky, R., & Zhong, Y. (2022). A force-sensing semi-automated robotic needle driver for minimally invasive surgery. In Y.-T. Liu, JJ. Chong, & T. Q. Dinh (Eds.), ICMT 2022 - 25th International Conference on Mechatronics Technology IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICMT56556.2022.9997789

@inproceedings{5ddaaaa3c1bf4533b9d1d5c12bf6eb5c,

title = "A force-sensing semi-automated robotic needle driver for minimally invasive surgery",

abstract = "Teleoperated robotic surgery systems have enhanced surgical operations' efficiency. However, these systems have limitations, such as lack of force feedback to the surgeon and complicated manipulation for tasks such as suturing. In this paper, a force-sensing instrument is presented with a robotic needle driver that facilitates suturing. A rotating degree of freedom (DOF) enables the cable-driven end-effector to insert the needle through its curvature. Moreover, an indirect force estimation approach was developed to approximate the needle-tissue interaction force. A mapping between robot sensors' data and target interaction force was created using a data-based model. Next, experimental evaluations of the proposed instrument were conducted. According to the experimental results, the generated trajectory had a root mean square error (RMSE) of 0.59 mm and the accuracy of the force estimation model was 0.21 N RMSE. In conclusion, these results demonstrate the potential of the proposed instrument for bilateral control systems.",

keywords = "Data-based Force model, Force measurement, Medical Instrumentation, Robotic-assisted minimally invasive surgery (RAMIS)",

author = "Armin Ehrampoosh and Bijan Shirinzadeh and Joshua Pinskier and Julian Smith and Randall Moshinsky and Yongmin Zhong",

note = "Funding Information: This work was supported by Australian Research Council Discovery Projects grants DP180103852 and Monash Institute of Medical Engineering. Publisher Copyright: {\textcopyright} 2022 IEEE.; International Conference on Mechatronics Technology 2022, ICMT 2022 ; Conference date: 18-11-2022 Through 21-11-2022",

year = "2022",

doi = "10.1109/ICMT56556.2022.9997789",

language = "English",

editor = "Yung-Tien Liu and JJ Chong and Dinh, {Trung Quang}",

booktitle = "ICMT 2022 - 25th International Conference on Mechatronics Technology",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

url = "https://ieeexplore.ieee.org/xpl/conhome/9997567/proceeding",

}

Ehrampoosh, A, Shirinzadeh, B, Pinskier, J, Smith, J, Moshinsky, R & Zhong, Y 2022, A force-sensing semi-automated robotic needle driver for minimally invasive surgery. in Y-T Liu, JJ Chong & TQ Dinh (eds), ICMT 2022 - 25th International Conference on Mechatronics Technology. IEEE, Institute of Electrical and Electronics Engineers, International Conference on Mechatronics Technology 2022, Kaohsiung, Taiwan, 18/11/22. https://doi.org/10.1109/ICMT56556.2022.9997789

A force-sensing semi-automated robotic needle driver for minimally invasive surgery. / Ehrampoosh, Armin; Shirinzadeh, Bijan; Pinskier, Joshua et al.
ICMT 2022 - 25th International Conference on Mechatronics Technology. ed. / Yung-Tien Liu; JJ Chong; Trung Quang Dinh. IEEE, Institute of Electrical and Electronics Engineers, 2022.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other

TY - GEN

T1 - A force-sensing semi-automated robotic needle driver for minimally invasive surgery

AU - Ehrampoosh, Armin

AU - Shirinzadeh, Bijan

AU - Pinskier, Joshua

AU - Smith, Julian

AU - Moshinsky, Randall

AU - Zhong, Yongmin

N1 - Conference code: 25th

PY - 2022

Y1 - 2022

N2 - Teleoperated robotic surgery systems have enhanced surgical operations' efficiency. However, these systems have limitations, such as lack of force feedback to the surgeon and complicated manipulation for tasks such as suturing. In this paper, a force-sensing instrument is presented with a robotic needle driver that facilitates suturing. A rotating degree of freedom (DOF) enables the cable-driven end-effector to insert the needle through its curvature. Moreover, an indirect force estimation approach was developed to approximate the needle-tissue interaction force. A mapping between robot sensors' data and target interaction force was created using a data-based model. Next, experimental evaluations of the proposed instrument were conducted. According to the experimental results, the generated trajectory had a root mean square error (RMSE) of 0.59 mm and the accuracy of the force estimation model was 0.21 N RMSE. In conclusion, these results demonstrate the potential of the proposed instrument for bilateral control systems.

AB - Teleoperated robotic surgery systems have enhanced surgical operations' efficiency. However, these systems have limitations, such as lack of force feedback to the surgeon and complicated manipulation for tasks such as suturing. In this paper, a force-sensing instrument is presented with a robotic needle driver that facilitates suturing. A rotating degree of freedom (DOF) enables the cable-driven end-effector to insert the needle through its curvature. Moreover, an indirect force estimation approach was developed to approximate the needle-tissue interaction force. A mapping between robot sensors' data and target interaction force was created using a data-based model. Next, experimental evaluations of the proposed instrument were conducted. According to the experimental results, the generated trajectory had a root mean square error (RMSE) of 0.59 mm and the accuracy of the force estimation model was 0.21 N RMSE. In conclusion, these results demonstrate the potential of the proposed instrument for bilateral control systems.

KW - Data-based Force model

KW - Force measurement

KW - Medical Instrumentation

KW - Robotic-assisted minimally invasive surgery (RAMIS)

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DO - 10.1109/ICMT56556.2022.9997789

M3 - Conference Paper

AN - SCOPUS:85144599422

BT - ICMT 2022 - 25th International Conference on Mechatronics Technology

A2 - Liu, Yung-Tien

A2 - Chong, JJ

A2 - Dinh, Trung Quang

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - International Conference on Mechatronics Technology 2022

Y2 - 18 November 2022 through 21 November 2022

ER -

A force-sensing semi-automated robotic needle driver for minimally invasive surgery

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