DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Motion Primitive Learning for Robot-Assisted Surgery

Karademir, Ertugrul (2018) Motion Primitive Learning for Robot-Assisted Surgery. Master's, Technical University of Munich.

[img] PDF - Only accessible within DLR


Although Minimally Invasive Robotic Surgery (MIRS) had been researched for more than 25 years, and commercial and advanced research systems exist, Artificial Intelligence and Big Data approaches open up new fields of research. For instance, the collection of Big Data from procedures aid the new field of research on surgical activity recognition (SAR). SAR could be the basis to provide assistance functions to the operating surgeon to increase performance. SAR is in essence a problem of recognizing repeatedly incoming sequential data. This has been previously approached using Hidden Markov Models (HMMs). In this work, a motion recognition approach, called Incremental Motion Primitive Learning (MPL), and two Linear Discriminant Analysis (LDA) based methods are adapted and implemented to aid SAR. These methods are compared to methods proposed in the literature, by evaluating them on a publicly available dataset (JIGSAWS). The LDA based approaches show promising results up to 94% accuracy, while the MPL approaches perform not as well. Shortcomings and possible improvements are discussed and future work on the methods have been identified. Additionally, a new surgical activity dataset using the DLR MiroSurge System is collected. This dataset augments the commonly used kinematic data with dynamic, contextual and low-level hardware data. This dataset can be a basis to support the research on SAR, e.g. on feature selection.

Item URL in elib:https://elib.dlr.de/195104/
Document Type:Thesis (Master's)
Title:Motion Primitive Learning for Robot-Assisted Surgery
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Robot Assisted Surgery, Motion Primitive Learning, Surgical Gesture Recognition
Institution:Technical University of Munich
Department:Huma-centered Assistive Robotics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Terrestrial Assistance Robotics, R - Medical Assistance Systems [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Analysis and Control of Advanced Robotic Systems
Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Deposited By: Klodmann, Julian
Deposited On:22 May 2023 07:25
Last Modified:12 Jul 2023 17:02

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.