A gesture driven robotic scrub nurse. Jacob, M., G., M., Li, Y., T., & Wachs, J., J., P. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, pages 2039-2044, 10, 2011. IEEE. Website doi abstract bibtex A gesture driven robotic scrub nurse (GRSN) for the operating room (OR) is presented. The GRSN passes surgical instruments to the surgeon during surgery which reduces the workload of a human scrub nurse. This system offers several advantages such as freeing human nurses to perform concurrent tasks, and reducing errors in the OR due to miscommunication or absence of surgical staff. Hand gestures are recognized from a video stream, converted to instructions, and sent to a robotic arm which passes the required surgical instruments to the surgeon. Experimental results show that 95% of the gestures were recognized correctly. The gesture recognition algorithm presented is robust to changes in scale and rotation of the hand gestures. The system was compared to human task performance and was found to be only 0.83 seconds slower on average. © 2011 IEEE.
@inproceedings{
title = {A gesture driven robotic scrub nurse},
type = {inproceedings},
year = {2011},
keywords = {Accuracy,GRSN,Gesture recognition,Grippers,Humans,Instruments,Robots,Surgery,gesture driven robotic scrub nurse,gesture recognition,hand gesture recognition algorithm,health care,healthcare robotics,human robot interaction,human scrub nurse,human-robot interaction,medical robotics,operating room,robotic scrub nurse,surgery,surgical instruments,surgical robotics,video stream,video streaming,workload reduction},
pages = {2039-2044},
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month = {10},
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abstract = {A gesture driven robotic scrub nurse (GRSN) for the operating room (OR) is presented. The GRSN passes surgical instruments to the surgeon during surgery which reduces the workload of a human scrub nurse. This system offers several advantages such as freeing human nurses to perform concurrent tasks, and reducing errors in the OR due to miscommunication or absence of surgical staff. Hand gestures are recognized from a video stream, converted to instructions, and sent to a robotic arm which passes the required surgical instruments to the surgeon. Experimental results show that 95% of the gestures were recognized correctly. The gesture recognition algorithm presented is robust to changes in scale and rotation of the hand gestures. The system was compared to human task performance and was found to be only 0.83 seconds slower on average. © 2011 IEEE.},
bibtype = {inproceedings},
author = {Jacob, Mithun George M.G. and Li, Yu-Ting Ting and Wachs, J.P. Juan P.},
doi = {10.1109/ICSMC.2011.6083972},
booktitle = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics}
}
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