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Laproscopic Grasping Experiment:


Experimentors

Primary researcher: Jacob Rosen <rosen AT u.washington.edu>

Publications*

[133]
C. Richards, J. Rosen, B. Hannaford, M. MacFarlane, C. Pellegrini, M. Sinanan, 'Skills Evaluation in Minimally Invasive Surgery Using Force/Torque Signatures,' Surgical Endoscopy, vol. 14, pp. 791-798, 2000.

[134]
J. Rosen, C. Richards, B. Hannaford, M. Sinanan, 'Hidden markov Models of Minimally Invasive Surgery,' Studies in Health Technology and Informatics - Medicine Meets Virtual Reality, vol. 70, pp. 279-285, January, 2000.

[135]
J. Rosen, M. Solazzo, B. Hannaford, M. Sinanan, 'Objective Evaluation of Laparoscopic Surgical Skills Using Hidden Markov Models Based on Haptic Information and Tool/Tissue Interactions,' American College of Surgeons Annual Meeting - Washington State Chapter, Lake Chelan, WA, June 2000.

[142]
J. Rosen, B. Hannaford, C. Richards, M. Sinanan, 'Markov Modeling of Minimally Invasive Surgery Based on Tool/Tissue Interaction and Force/Torque Signatures for Evaluating Surgical Skills,' IEEE Transactions on Biomedical Engineering, vol. 48, pp. 579-591, May 2001.

[145]
J. Rosen, M. Solazzo, B. Hannaford, M. Sinanan, 'Objective Laparoscopic Skills Assessments of Surgical Residents Using Hidden Markov Models Based on Haptic Information and Tool/Tissue Interactions,' Studies in Health Technology and Informatics - Medicine Meets Virtual Reality, vol. 81, pp. 417-423, Newport Beach, CA, January 2001.

[161]
J. Rosen, M. Solazzo, B. Hannaford, M. Sinanan, 'Task Decomposition of Laparoscopic Surgery for Objective Evaluation of Surgical Residents' Learning Curve Using Hidden Markov Model,' Computer Aided Surgery, vol. 7, pp. 49-61, July 2002.

Description of procedures

Equipment used

Endoscopic Grasper

Description of data

Column # Data Units
1 Force x N
2 Force y N
3 Force z N
4 Torque x N*M
5 Torque y N*M
6 Torque z N*M
7 Force grasper N

*Sampling Rate=1000 Hz

Data files


Laproscopic Cholecystectomy
lc_subj-10_1
lc_subj-10_21
lc_subj-10_2
lc_subj-10_3
lc_subj-1_1
lc_subj-1_2
lc_subj-1_3
lc_subj-2_1
lc_subj-2_2
lc_subj-2_3
lc_subj-3_1
lc_subj-3_2
lc_subj-3_3
lc_subj-4_1
lc_subj-4_2
lc_subj-4_3
lc_subj-5_1
lc_subj-5_2
lc_subj-5_3
lc_subj-6_1
lc_subj-6_2
lc_subj-6_3
lc_subj-7_1
lc_subj-7_2
lc_subj-7_3
lc_subj-8_1
lc_subj-8_2
lc_subj-8_3
lc_subj-9_1
lc_subj-9_2
lc_subj-9_3


Laproscopic Nissen Funtoplication
lnf_subj-10_3
lnf_subj-10_4
lnf_subj-10_5
lnf_subj-1_3
lnf_subj-1_4
lnf_subj-1_5
lnf_subj-2_3
lnf_subj-2_4
lnf_subj-2_5
lnf_subj-3_3
lnf_subj-3_4
lnf_subj-3_5
lnf_subj-4_3
lnf_subj-4_4
lnf_subj-4_5
lnf_subj-5_3
lnf_subj-5_4
lnf_subj-5_5
lnf_subj-6_3
lnf_subj-6_4
lnf_subj-6_5
lnf_subj-7_3
lnf_subj-7_4
lnf_subj-7_5
lnf_subj-8_3
lnf_subj-8_4
lnf_subj-8_5
lnf_subj-9_3
lnf_subj-9_4
lnf_subj-9_5

*file name=<experiment type>_<subject number>_<trial number>.TXT