Distance‐based time series classification approach for task recognition with application in surgical robot autonomy

Robotic‐assisted surgery allows surgeons to perform many types of complex operations with greater precision than is possible with conventional surgery. Despite these advantages, in current systems, a surgeon should communicate with the device directly and manually. To allow the robot to adjust parameters such as camera position, the system needs to know automatically what task the surgeon is performing.

[1]  Jian Pei,et al.  A brief survey on sequence classification , 2010, SKDD.

[2]  A. Cuschieri.  Whither minimal access surgery: tribulations and expectations. , 1995, American journal of surgery.

[3]  Gregory D. Hager,et al.  Task versus Subtask Surgical Skill Evaluation of Robotic Minimally Invasive Surgery , 2009, MICCAI.

[4]  Tak-Chung Fu,et al.  A review on time series data mining , 2011, Eng. Appl. Artif. Intell..

[5]  Ratna Babu Chinnam,et al.  Soft Boundary Approach for Unsupervised Gesture Segmentation in Robotic-Assisted Surgery , 2017, IEEE Robotics and Automation Letters.

[6]  Gregory D. Hager,et al.  Data-Derived Models for Segmentation with Application to Surgical Assessment and Training , 2009, MICCAI.

[7]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[8]  Hui Ding,et al.  Querying and mining of time series data: experimental comparison of representations and distance measures , 2008, Proc. VLDB Endow..

[9]  Li Wei,et al.  Fast time series classification using numerosity reduction , 2006, ICML.

[10]  Henry C. Lin,et al.  Review of methods for objective surgical skill evaluation , 2011, Surgical Endoscopy.

[11]  Donald J. Berndt,et al.  Finding Patterns in Time Series: A Dynamic Programming Approach , 1996, Advances in Knowledge Discovery and Data Mining.

[12]  Brady W King,et al.  Towards an autonomous robot for camera control during laparoscopic surgery. , 2013, Journal of laparoendoscopic & advanced surgical techniques. Part A.

[13]  Pierre Jannin,et al.  A Framework for the Recognition of High-Level Surgical Tasks From Video Images for Cataract Surgeries , 2012, IEEE Transactions on Biomedical Engineering.

[14]  Gregory D. Hager,et al.  Sparse Hidden Markov Models for Surgical Gesture Classification and Skill Evaluation , 2012, IPCAI.

[15]  Dimitrios Gunopulos,et al.  Discovering similar multidimensional trajectories , 2002, Proceedings 18th International Conference on Data Engineering.

[16]  Pierre Jannin,et al.  Surgical process modelling: a review , 2014, International Journal of Computer Assisted Radiology and Surgery.

[17]  Abhilash Pandya,et al.  A Review of Camera Viewpoint Automation in Robotic and Laparoscopic Surgery , 2014, Robotics.

[18]  Blake Hannaford,et al.  Markov modeling of minimally invasive surgery based on tool/tissue interaction and force/torque signatures for evaluating surgical skills , 2001, IEEE Transactions on Biomedical Engineering.

[19]  Mahtab Jahanbani Fard,et al.  Computational Modeling Approaches For Task Analysis In Robotic-Assisted Surgery , 2016 .

[20]  B. Hannaford,et al.  Task decomposition of laparoscopic surgery for objective evaluation of surgical residents' learning curve using hidden Markov model. , 2002, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[21]  Danail Stoyanov,et al.  Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions , 2016, International Journal of Computer Assisted Radiology and Surgery.

[22]  Jenny Dankelman,et al.  Discovery of high-level tasks in the operating room , 2011, J. Biomed. Informatics.

[23]  Eamonn J. Keogh,et al.  A Complexity-Invariant Distance Measure for Time Series , 2011, SDM.

[24]  Rajesh Aggarwal,et al.  Laparoscopic task recognition using Hidden Markov Models. , 2005, Studies in health technology and informatics.

[25]  Brady W King,et al.  Task analysis of laparoscopic camera control schemes , 2016, The international journal of medical robotics + computer assisted surgery : MRCAS.

[26]  Eamonn J. Keogh,et al.  Searching and Mining Trillions of Time Series Subsequences under Dynamic Time Warping , 2012, KDD.

[27]  A. Lanfranco,et al.  Robotic Surgery: A Current Perspective , 2004, Annals of surgery.

[28]  Henry C. Lin,et al.  Towards automatic skill evaluation: Detection and segmentation of robot-assisted surgical motions , 2006, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[29]  Germain Forestier,et al.  Classification of surgical processes using dynamic time warping , 2012, J. Biomed. Informatics.

[30]  R. Muradore,et al.  Robotic Surgery , 2011, IEEE Robotics & Automation Magazine.

[31]  Gregory D. Hager,et al.  Automatic Recognition of Surgical Motions Using Statistical Modeling for Capturing Variability , 2008, MMVR.

[32]  René Vidal,et al.  Surgical Gesture Classification from Video Data , 2012, MICCAI.

[33]  Dana Kulic,et al.  Segmenting human motion for automated rehabilitation exercise analysis , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[34]  Henry C. Lin,et al.  JHU-ISI Gesture and Skill Assessment Working Set ( JIGSAWS ) : A Surgical Activity Dataset for Human Motion Modeling , 2014 .

[35]  G. Fried,et al.  Proving the Value of Simulation in Laparoscopic Surgery , 2004, Annals of surgery.

[36]  Gregory D. Hager,et al.  Surgical gesture classification from video and kinematic data , 2013, Medical Image Anal..

[37]  Guang-Zhong Yang,et al.  HMM Assessment of Quality of Movement Trajectory in Laparoscopic Surgery , 2006, MICCAI.

[38]  Nassir Navab,et al.  Modeling and Online Recognition of Surgical Phases Using Hidden Markov Models , 2008, MICCAI.