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Using two-Third power law for segmentation of hand movement in robotic assisted surgery

  • SUNY Buffalo
  • Roswell Park Cancer Institute

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

In this study, we have developed a robust and accurate algorithm based on concept of two-Third power law in human motor control to segment the hand trajectory of robotic surgeons into smaller segments. We hypothesis that tracking a longer trajectory is subjected to higher cognitive workload that may lead in to an imperfect CNS performance in programming muscle activation which will lead to more number of segment trajectories and pause points in hand movements. To test our hypothesis, after segmenting the trajectory, we determine the correlation between affine velocity and workload extracted from Surgeon's Electroencephalography (EEG) features. EEG features are extracted by using brain waves recorded by wireless brain computer interface (B-Alert X-10 system). In our experimental study, 2 groups of participants three "experts" and five "Competent and Proficient" performed Urethro-vesical Anastomosis on an inanimate model, using the da-Vinci Surgical System® (Sunnyvale, CA).

Original languageEnglish
Title of host publication39th Mechanisms and Robotics Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791857144
DOIs
StatePublished - 2015
EventASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015 - Boston, United States
Duration: Aug 2 2015Aug 5 2015

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume5C-2015

Conference

ConferenceASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015
Country/TerritoryUnited States
CityBoston
Period08/2/1508/5/15

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