Scottish university claims mobile net breakthrough for remote medicine

Researchers from the James Watt School of Engineering in Glasgow are claiming to have constructed a new development in affordable, open-source mobile networks that enables near-real-time control of robotic arms. The technology could help doctors work on patients in remote locations in the years to come.

The first demonstration of the medical innovation has seen the research team use the system to perform mock dental exams on a pair of dentures, highlighting its potential for use in medical procedures.

The system is based on off-the-shelf hardware that has been used to build a 4G LTE mobile network which connects a haptic controller to a robot arm, with the network allowing users to direct the arm’s movements with very low latency, enabling a high level of control.

The research team built their framework using the Open Radio Access Network (O-RAN) framework, which uses open-source software to control mobile network hardware. They repurposed a USB network dongle, more commonly used for consumer mobile internet, to create stable connections between the haptic input device, the robotic arm and a computer configured to act as an intelligent base station.

The system’s signal quality, data rates and latency were monitored and fine-tuned using specialised xApps software.

Its mobile dongle also helped the team create a network that drew considerably less power than comparable connections using the software-defined radio (SDR) more commonly used in similar tasks. The system used 4.5 watts, a 90% reduction on the 45 watts required by traditional SDRs to perform the same activities.

From a performance basis during lab tests, the researchers enabled communications between the base station, the controller and the robotic arm with a bandwidth of 10Mbps. They said that such a connection allowed them to control the arm to simulate a dental exam on dentures with less than a second of latency and minimal signal loss.

The James Watt School of Engineering is part of the University of Glasgow, which was the first institution in the UK to confer degrees in engineering, and established the first chair of engineering in the UK in 1840. Its research environment includes coverage of a broad range of engineering subjects, as well as the interfaces with biology, chemistry, computer science, medicine and physics. 

The college claims its research and teaching is “at the forefront of discovery, creation and practice that is internationally leading in education, innovation and new capability”.

Commenting on the project and its aims in a paper outlining the research, Saber Hassouna of the James Watt School of Engineering said: “The O-RAN framework holds a great deal of potential for enabling intelligent, data-driven, programmable and virtualised networks, but a significant amount of work remains to be done to demonstrate that potential being achieved in the real world, beyond theoretical modelling.

“The testbed we’ve developed here using commercially available hardware shows that O-RAN can be used to enable excellent performance in robotic teleoperation, which is a complex task. For applications like dental procedures, the robotic arm must move very smoothly, which requires high data throughput and low latency, both of which we’ve been able to achieve for the first time with O-RAN.”

Qammer Abbasi, head of the University of Glasgow’s communications, sensing and imaging hub, added: “This is a very encouraging demonstration of the potential of O-RAN to enable fine-grained, close-to-real-time control of a robotic arm. [This] showcases the performance we’ve been able to deliver in a single room with a direct line of sight between the base station and the arm, and we’re currently working on developing the system further to ensure it can deliver the same level of performance at greater distances.

“Ultimately, this could be a step towards creating reliable, affordable methods of performing complex tasks remotely, opening up new applications in medicine, automation, industry and beyond.”

The research was supported by funding from the Communications Hub for Empowering Distributed Cloud Computing Applications and Research and the Engineering and Physical Sciences Research Council.