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Details of Grant 

EPSRC Reference: EP/P013872/1
Title: Understanding Laparoscopic Skills for Robotic Training and Assistance
Principal Investigator: Erden, Dr M
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Sch of Engineering and Physical Science
Organisation: Heriot-Watt University
Scheme: First Grant - Revised 2009
Starts: 01 April 2017 Ends: 31 March 2018 Value (£): 100,776
EPSRC Research Topic Classifications:
Human-Computer Interactions Med.Instrument.Device& Equip.
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Dec 2016 Engineering Prioritisation Panel Meeting 1 and 2 December 2016 Announced
Summary on Grant Application Form
How do surgeons maintain the fine manipulations in a Minimally Invasive Surgery (MIS)? How do they get the feeling of how to move the hand, how much force to apply, and when? We know that surgeons gain these skills through years of training and experience. However, we do not have a complete understanding of "what is learned" and "what underlying mechanisms are developed" to guide manipulation of the hand or how to quantify these issues. This suggests some specific questions we need to address: what are the task-specific tactile/visual/sequential conditions that trigger specific hand-arm movements? How is hand-impedance controlled for these movements?

Training for conventional MIS with a co-manipulated robot (robotic training) and assistance for conventional MIS with a collaborative robot (robotic assistance) can significantly benefit surgeons as in both cases the natural haptic feedback to the surgeon is preserved. To this end, we need to understand how the hand and arm are used during conventional MIS. Hand-impedance and arm-muscle activity measurements are required to develop the quantitative knowledge of skilled manipulation. This knowledge can be used to build a framework that links arm muscle activation to hand-impedance control for fine force and position contact at the hand. Such a framework could offer insights in training level of surgeons and help support the lack of skilled personnel. In my global research agenda, which extends beyond this project, I aim to (i) identify skilled and unskilled type movements by monitoring the tool movement, (ii) measure the hand-impedance in complex movements with an interactive robot, (iii) measure arm muscle activity with electromyography (EMG) and find out muscle activation patterns of skilled manipulation, (iv) develop a robotic trainer with such knowledge, (v) develop a robotic assistant with impedance compensation using this knowledge. This project, which constitutes the backbone of my research agenda, covers the items (i), (ii), and partially (iv):

My goal in this project is to identify the MIS skills based on tool-position tracking, to perform hand-impedance measurements during the complex hand-manipulations, to develop a co-manipulated robotic trainer for MIS where the subject gets real-time feedback and assessment through tool movement tracking and hand-impedance measurements.

We will study three basic procedures in laparoscopic MIS: suturing, knot-tying, and bimanual carrying. The experimental setup will build upon my previous work - impedance measurements with an admittance controlled interactive robot - as well as my current work - on EMG based MIS skill identification and development of a mechanical adaptor to interface a MIS training platform to a robot. For the full research that directly relates to this project (items i, ii, iv), we need to understand on one hand, the skilled type tool manipulation and the corresponding hand-impedance levels (topic of this project), and on the other hand, the muscle activation patterns that generate these effects (topic of an accompanying PhD study). I will be contributing the accompanying PhD student to the proposed research, who is not funded by this project. The results of the work of this PhD student will be used in the funded project.

The robotic trainer will detect unskilled type movements and provide real-time feedback to notice those. The trainer will also assess the skill level of the subject by performing hand-impedance measurements besides evaluating tool movements. We will use a robot arm by attaching a MIS handle to its end-effector and an improved control/impedance measurement scheme that extends beyond my previous work. Subjects (professional-surgeons and novices) will perform MIS procedures with the tool attached to the end effector of the robot arm. The robot arm will passively follow and monitor the surgeon-hand movements and intervene from time to time for impedance measurements by introducing disturbances.

Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.hw.ac.uk