TY - CHAP
T1 - IoT-Based Remote Control Study of a Robotic Trans-Esophageal Ultrasound Probe via LAN and 5G
AU - Wang, Shuangyi
AU - Hou, Xilong
AU - Housden, James
AU - Hou, Zengguang
AU - Singh, Davinder
AU - Rhode, Kawal
PY - 2020
Y1 - 2020
N2 - A robotic trans-esophageal echocardiography (TEE) probe has been recently developed to address the problems with manual control in the X-ray environment when a conventional probe is used for interventional procedure guidance. However, the robot was exclusively to be used in local areas and the effectiveness of remote control has not been scientifically tested. In this study, we implemented an Internet-of-things (IoT)-based configuration to the TEE robot so the system can set up a local area network (LAN) or be configured to connect to an internet cloud over 5G. To investigate the remote control, backlash hysteresis effects were measured and analysed. A joystick-based device and a button-based gamepad were then employed and compared with the manual control in a target reaching experiment for the two steering axes. The results indicated different hysteresis curves for the left-right and up-down steering axes with the input wheel’s deadbands found to be 15° and 8°, respectively. Similar magnitudes of positioning errors at approximately 0.5° and maximum overshoots at around 2.5° were found when manually and robotically controlling the TEE probe. The amount of time to finish the task indicated a better performance using the button-based gamepad over joystick-based device, although both were worse than the manual control. It is concluded that the IoT-based remote control of the TEE probe is feasible and a trained user can accurately manipulate the probe. The main identified problem was the backlash hysteresis in the steering axes, which can result in continuous oscillations and overshoots.
AB - A robotic trans-esophageal echocardiography (TEE) probe has been recently developed to address the problems with manual control in the X-ray environment when a conventional probe is used for interventional procedure guidance. However, the robot was exclusively to be used in local areas and the effectiveness of remote control has not been scientifically tested. In this study, we implemented an Internet-of-things (IoT)-based configuration to the TEE robot so the system can set up a local area network (LAN) or be configured to connect to an internet cloud over 5G. To investigate the remote control, backlash hysteresis effects were measured and analysed. A joystick-based device and a button-based gamepad were then employed and compared with the manual control in a target reaching experiment for the two steering axes. The results indicated different hysteresis curves for the left-right and up-down steering axes with the input wheel’s deadbands found to be 15° and 8°, respectively. Similar magnitudes of positioning errors at approximately 0.5° and maximum overshoots at around 2.5° were found when manually and robotically controlling the TEE probe. The amount of time to finish the task indicated a better performance using the button-based gamepad over joystick-based device, although both were worse than the manual control. It is concluded that the IoT-based remote control of the TEE probe is feasible and a trained user can accurately manipulate the probe. The main identified problem was the backlash hysteresis in the steering axes, which can result in continuous oscillations and overshoots.
UR - http://www.scopus.com/inward/record.url?scp=85092729959&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-60334-2_17
DO - 10.1007/978-3-030-60334-2_17
M3 - Conference paper
AN - SCOPUS:85092729959
SN - 9783030603335
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 171
EP - 179
BT - Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis - 1st International Workshop, ASMUS 2020, and 5th International Workshop, PIPPI 2020, Held in Conjunction with MICCAI 2020, Proceedings
A2 - Hu, Yipeng
A2 - Licandro, Roxane
A2 - Noble, J. Alison
A2 - Hutter, Jana
A2 - Melbourne, Andrew
A2 - Aylward, Stephen
A2 - Abaci Turk, Esra
A2 - Torrents Barrena, Jordina
A2 - Torrents Barrena, Jordina
PB - Springer Science and Business Media Deutschland GmbH
T2 - 1st International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2020, and the 5th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020
Y2 - 4 October 2020 through 8 October 2020
ER -