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Assisted Probe Positioning for Ultrasound Guided Radiotherapy Using Image Sequence Classification
Effective transperineal ultrasound image guidance in prostate external b...
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Pengaruh Perangkat Server Terhadap Kualitas Pengontrolan Jarak Jauh Melalui Internet
Internet greatly assist people in improving their quality of life. Almos...
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The Penetration of Internet of Things in Robotics: Towards a Web of Robotic Things
As the Internet of Things (IoT) penetrates different domains and applica...
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A concept of a measuring system for probe kinesthetic parameters identification during echocardiography examination
Echocardiography is the most commonly used imaging technique in clinical...
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RADIS: Remote Attestation of Distributed IoT Services
Remote attestation is a security technique by which a potentially untrus...
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ZoomTouch: Multi-User Remote Robot Control in Zoom by DNN-based Gesture Recognition
We present ZoomTouch - a breakthrough technology for multi-user control ...
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MAC Address De-Anonymisation
This project is an exploration into analysing WiFi probe requests, a man...
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IoT-based Remote Control Study of a Robotic Trans-esophageal Ultrasound Probe via LAN and 5G
A robotic trans-esophageal echocardiography (TEE) probe has been recently developed to address the problems with manual control in the X-ray envi-ronment 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 re-mote control, backlash hysteresis effects were measured and analysed. A joy-stick-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 deg and deg, respectively. Similar magnitudes of positioning errors at approximately 0.5 deg and maximum overshoots at around 2.5 deg 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.
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