DocumentCode
716329
Title
Feed forward incision control for laser microsurgery of soft tissue
Author
Fichera, Loris ; Pardo, Diego ; Illiano, Placido ; Caldwell, Darwin G. ; Mattos, Leonardo S.
Author_Institution
Dept. of Adv. Robot., Ist. Italiano di Tecnol., Genoa, Italy
fYear
2015
fDate
26-30 May 2015
Firstpage
1235
Lastpage
1240
Abstract
In this paper we present a feed forward controller to regulate the depth of laser incisions in soft tissue. Such a controller is compatible with the requirements of laser microsurgery, where space constraints limit the use of sensing devices. The controller is based on an inverse model that maps the desired incision depth to the required laser exposure time. This model is extracted from experimental data through the use of statistical learning methods. To prove the concept, the controller is implemented in a robot-assisted laser microsurgery system that enables precision control of exposure time and laser motion. The validity and the accuracy of the controller is verified experimentally on ex-vivo muscle tissue (chicken breast), revealing an RMSE of 0.12 mm for incisions ranging up to 1 mm. In addition, we demonstrate how the model can be used to implement the automatic ablation of entire volumes of tissue, through the superposition of controlled laser incisions.
Keywords
biocontrol; biological tissues; feedforward; laser applications in medicine; learning (artificial intelligence); medical robotics; microrobots; motion control; statistical analysis; surgery; controlled laser incision superposition; ex-vivo muscle tissue; feedforward incision control; inverse model; laser exposure time control; laser incision depth regulation; laser motion control; robot-assisted laser microsurgery system; sensing devices; soft tissue; space constraints; statistical learning methods; Laser ablation; Laser beams; Laser modes; Measurement by laser beam; Microsurgery;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation (ICRA), 2015 IEEE International Conference on
Conference_Location
Seattle, WA
Type
conf
DOI
10.1109/ICRA.2015.7139349
Filename
7139349
Link To Document