Automatic Identification for Laparoscopic Surgical Procedure for Ligation and Online Distinction of Abnormal Manipulation for Thread Knotting
Affiliation(s)
1 Department of Mechanical Engineering, Faculty of Science and Engineering, Hosei Universitty, Tokyo, Japan. 2 Nihon Kohden Corporation, Tokyo, Japan. 3 Gastroenterological Surgery, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
1 Department of Mechanical Engineering, Faculty of Science and Engineering, Hosei Universitty, Tokyo, Japan. 2 Nihon Kohden Corporation, Tokyo, Japan. 3 Gastroenterological Surgery, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
ABSTRACT
Laparoscopic surgery is a difficult surgical procedure compared with laparotomy. In particular, considerable skills and care are required for thread knotting in laparoscopic surgery. In this paper, a method for automatic identification of a laparoscopic surgical procedure for ligation and online distinction of an abnormality, defined as any unusual manipulation, in the identified surgical procedure is proposed. Ligation is divided into several individual surgical procedures, and on the basis of the threshold criteria, each surgical procedure is identified. Next, the identified surgical procedure, thread knotting, is classified as either normal or abnormal using a self-organizing map. Finally, to reduce surgical error, an abnormality warning system which warns detection of an unusual manipulation in the surgical procedure to the operator is constructed.
Laparoscopic surgery is a difficult surgical procedure compared with laparotomy. In particular, considerable skills and care are required for thread knotting in laparoscopic surgery. In this paper, a method for automatic identification of a laparoscopic surgical procedure for ligation and online distinction of an abnormality, defined as any unusual manipulation, in the identified surgical procedure is proposed. Ligation is divided into several individual surgical procedures, and on the basis of the threshold criteria, each surgical procedure is identified. Next, the identified surgical procedure, thread knotting, is classified as either normal or abnormal using a self-organizing map. Finally, to reduce surgical error, an abnormality warning system which warns detection of an unusual manipulation in the surgical procedure to the operator is constructed.
KEYWORDS
Automatic Identification of Surgical Procedure, Distinction of Abnormal Manipulation in Surgical Procedure, Abnormality Warning System, Surface Electromyogram (SEMG), Self-Organizing Map (SOM)
Automatic Identification of Surgical Procedure, Distinction of Abnormal Manipulation in Surgical Procedure, Abnormality Warning System, Surface Electromyogram (SEMG), Self-Organizing Map (SOM)
Cite this paper
Ishii, C. , Sato, T. , Murano, K. and Kawamura, H. (2015) Automatic Identification for Laparoscopic Surgical Procedure for Ligation and Online Distinction of Abnormal Manipulation for Thread Knotting. International Journal of Clinical Medicine, 6, 887-898. doi: 10.4236/ijcm.2015.612116.
Ishii, C. , Sato, T. , Murano, K. and Kawamura, H. (2015) Automatic Identification for Laparoscopic Surgical Procedure for Ligation and Online Distinction of Abnormal Manipulation for Thread Knotting. International Journal of Clinical Medicine, 6, 887-898. doi: 10.4236/ijcm.2015.612116.
References
[1] Chen, X., Zhang, X., Zhao, Z.Y., et al. (2007) Multiple Hand Gesture Recognition Based on Surface EMG Signal. Proceedings of International Conference on Bioinformatics and Biomedical Engineering, Boston, 14-17 October 2007, 506-509. [2] Nakaya, Y., Nakakuki, T., Hikita, M. and Ishii, C. (2010) A Practical Approach for Recognition of Hand Gesture and Distinction of Its Singularity. Proceedings of 2010 IEEE International Conference on Automation and Logistics, Hong Kong and Macau, 16-20 August 2010, 474-479.
http://dx.doi.org/10.1109/ICAL.2010.5585329 [3] Kumagai, T., Yamashita, J., Yokoyama, K., Fujimaki, S., Konishi, T., et al. (2008) Distance Education System for Teaching Manual Skills in Endoscopic Paranasal Sinus Surgery Using Hyper Mirror Telecommunication Interface. Proceedings of IEEE Virtual Reality, Reno, 8-12 March 2008, 233-236.
http://dx.doi.org/10.1109/vr.2008.4480779 [4] Horeman, T., Rodrigues, S.P., Jansen, F.W., Dankelman, J. and van den Dobbelsteen, J.J. (2012) Force Parameters for Skills Assessment in Laparoscopy. IEEE Transactions on Haptics, 5-4, 312-322.
http://dx.doi.org/10.1109/TOH.2011.60 [5] Kurita, Y., Hayama, Y., Kawahara, T., Okajima, M., Egi, H., et al. (2012) Skill Assessment Based on Automatic Classification of Forceps Manipulations. Proceedings of Complex Medical Engineering, Kobe, 1-4 July 2012, 56-59.
http://dx.doi.org/10.1109/iccme.2012.6275610 [6] Kohonen, T. (2000) Self-Organizing Maps. Sprin-ger-Verlag, Berlin Heidelberg. [7] Sato, T., Ishii, C. and Kawamura, H. (2013) Identification and Singularity Distinction of Surgical Operation in Endoscopic Surgery. Proceedings of the 16th International Conference on Advanced Robotics, Montevideo, 25-29 November 2013, 1-6.
[1] Chen, X., Zhang, X., Zhao, Z.Y., et al. (2007) Multiple Hand Gesture Recognition Based on Surface EMG Signal. Proceedings of International Conference on Bioinformatics and Biomedical Engineering, Boston, 14-17 October 2007, 506-509. [2] Nakaya, Y., Nakakuki, T., Hikita, M. and Ishii, C. (2010) A Practical Approach for Recognition of Hand Gesture and Distinction of Its Singularity. Proceedings of 2010 IEEE International Conference on Automation and Logistics, Hong Kong and Macau, 16-20 August 2010, 474-479.
http://dx.doi.org/10.1109/ICAL.2010.5585329 [3] Kumagai, T., Yamashita, J., Yokoyama, K., Fujimaki, S., Konishi, T., et al. (2008) Distance Education System for Teaching Manual Skills in Endoscopic Paranasal Sinus Surgery Using Hyper Mirror Telecommunication Interface. Proceedings of IEEE Virtual Reality, Reno, 8-12 March 2008, 233-236.
http://dx.doi.org/10.1109/vr.2008.4480779 [4] Horeman, T., Rodrigues, S.P., Jansen, F.W., Dankelman, J. and van den Dobbelsteen, J.J. (2012) Force Parameters for Skills Assessment in Laparoscopy. IEEE Transactions on Haptics, 5-4, 312-322.
http://dx.doi.org/10.1109/TOH.2011.60 [5] Kurita, Y., Hayama, Y., Kawahara, T., Okajima, M., Egi, H., et al. (2012) Skill Assessment Based on Automatic Classification of Forceps Manipulations. Proceedings of Complex Medical Engineering, Kobe, 1-4 July 2012, 56-59.
http://dx.doi.org/10.1109/iccme.2012.6275610 [6] Kohonen, T. (2000) Self-Organizing Maps. Sprin-ger-Verlag, Berlin Heidelberg. [7] Sato, T., Ishii, C. and Kawamura, H. (2013) Identification and Singularity Distinction of Surgical Operation in Endoscopic Surgery. Proceedings of the 16th International Conference on Advanced Robotics, Montevideo, 25-29 November 2013, 1-6.