TY - GEN
T1 - Human vs. robotic tactile sensing
T2 - 2010 IEEE Haptics Symposium, HAPTICS 2010
AU - Gwilliam, James C.
AU - Pezzementi, Zachary
AU - Jantho, Erica
AU - Okamura, Allison M.
AU - Hsiao, Steven
PY - 2010
Y1 - 2010
N2 - Humans can localize lumps in soft tissue using the distributed tactile feedback and processing afforded by the fingers and brain. This task becomes extremely difficult when the fingers are not in direct contact with the tissue, such as in laparoscopic or robot-assisted procedures. Tactile sensors have been proposed to characterize and detect lumps in robot-assisted palpation. In this work, we compare the performance of a capacitive tactile sensor with that of the human finger. We evaluate the response of the sensor as it pertains to robot-assisted palpation and compare the sensor performance to that of human subjects performing an equivalent task on the same set of artificial tissue models. Furthermore, we investigate the effects of various tissue parameters (lump size, lump depth, and surrounding tissue stiffness) on the performance of both the human finger and the tactile sensor. Using signal detection theory for determining tactile sensor lump detection thresholds, the tactile sensor outperforms the human finger in a palpation task.
AB - Humans can localize lumps in soft tissue using the distributed tactile feedback and processing afforded by the fingers and brain. This task becomes extremely difficult when the fingers are not in direct contact with the tissue, such as in laparoscopic or robot-assisted procedures. Tactile sensors have been proposed to characterize and detect lumps in robot-assisted palpation. In this work, we compare the performance of a capacitive tactile sensor with that of the human finger. We evaluate the response of the sensor as it pertains to robot-assisted palpation and compare the sensor performance to that of human subjects performing an equivalent task on the same set of artificial tissue models. Furthermore, we investigate the effects of various tissue parameters (lump size, lump depth, and surrounding tissue stiffness) on the performance of both the human finger and the tactile sensor. Using signal detection theory for determining tactile sensor lump detection thresholds, the tactile sensor outperforms the human finger in a palpation task.
KW - H.1.2 [models and principles]: user/machine systems - human information processing
KW - H.5.2 [information interfaces and presentation]: user interfaces - haptic I/O
KW - I.5.2 [pattern recognition]: design methodology - classifier design and evaluation
UR - http://www.scopus.com/inward/record.url?scp=77952726022&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952726022&partnerID=8YFLogxK
U2 - 10.1109/HAPTIC.2010.5444685
DO - 10.1109/HAPTIC.2010.5444685
M3 - Conference contribution
AN - SCOPUS:77952726022
SN - 9781424468218
T3 - 2010 IEEE Haptics Symposium, HAPTICS 2010
SP - 21
EP - 28
BT - 2010 IEEE Haptics Symposium, HAPTICS 2010
Y2 - 25 March 2010 through 26 March 2010
ER -