In-Depth Exploration of Low-Latency Control Guarantee for Remote Surgical Robots by Industrial Personal Computers
In today's era of rapid medical technology development, remote surgical robots have emerged as a significant breakthrough direction in the medical field. They have broken down geographical barriers, enabling wider coverage of high-quality medical resources and bringing new hope to patients. However, for remote surgical robots to achieve safe and precise operations, low-latency control is the critical core. As the "nerve center" of remote surgical systems, industrial personal computers (IPCs) directly determine the success or failure of surgeries and the safety of patients through their low-latency control guarantee capabilities.
The concept of remote surgical robots is not new. As early as the 1990s, with the development of network and robotic technologies, this concept began to be proposed and explored. In 1995, the U.S. military successfully guided a transatlantic remote surgery via satellite connection in Germany, initiating preliminary exploration of remote surgeries. Entering the 21st century, robotic-assisted surgical systems such as the Da Vinci Surgical System began to be applied clinically, laying a solid foundation for remote surgeries. In 2019, China successfully performed the world's first remote brain surgery based on a 5G network, marking the advent of a new era for remote surgeries. Today, the domestically produced TuMi robot has achieved full coverage of complex remote surgeries across multiple departments using various communication methods such as dedicated lines, 5G networks, conventional networks, high-orbit satellites, and low-orbit satellites, and has obtained approval for remote commercial clinical use, becoming the first and only surgical robot globally.
Despite significant progress, remote surgical robots still face numerous challenges. Among them, low-latency control is one of the core difficulties. In remote surgeries, the operating instructions from the lead surgeon must be transmitted across regions, synchronized across multiple nodes, and executed by robotic arms within an extremely short timeframe. For example, in cardiac intervention surgeries, doctors require extremely high precision in operating robotic arms, and any minor delay can lead to surgical failure or even endanger the patient's life. Generally, end-to-end operational latency must be controlled within 300 milliseconds, posing extremely stringent requirements on network transmission and control systems.
Industrial personal computers are core components of remote surgical systems, functioning as the system's "brain." They are responsible for coordinating the work among various subsystems, enabling data collection, transmission, processing, and instruction sending. In remote surgeries, IPCs undertake the crucial task of connecting the doctor's operation terminal, the surgical robot, and the patient terminal, ensuring stable system operation and low-latency control.
Take the USR-EG628 industrial personal computer as an example. It features a rich array of interfaces that can connect to various medical sensors, such as force sensors, position sensors, and video sensors, enabling real-time collection of various data during surgeries, including force feedback from robotic arms, positional information, and the patient's vital signs. Simultaneously, it supports multiple communication protocols, such as Ethernet, Wi-Fi, and 4G/5G, allowing for rapid and stable transmission of the collected data to a remote control center and timely sending of the doctor's operating instructions to the surgical robot, achieving precise remote control.
5G network slicing technology is the foundation for achieving low-latency control in remote surgeries. By dividing wireless resources into three independent planes—eMBB (Enhanced Mobile Broadband), mMTC (Massive Machine-Type Communications), and URLLC (Ultra-Reliable Low-Latency Communications)—dedicated bandwidth channels can be reserved for surgical operation instructions. Experimental data shows that after adopting a dynamic slicing configuration strategy, the transmission latency of surgical instructions from Beijing to Shanghai dropped from 82ms to 28ms, with jitter controlled within ±3ms. This technological breakthrough has made data transmission in remote surgeries more stable and rapid, effectively reducing latency.
The deployment of intelligent edge computing nodes is another crucial means of reducing latency. By configuring MEC (Mobile Edge Computing) servers within a 50-meter radius of the operating room, computing tasks such as image preprocessing and instrument status verification can be offloaded, reducing the number of core network transmissions. For example, in remote cardiac surgeries, edge computing servers can process and analyze cardiac images in real-time, extract key information, and rapidly transmit the processed data to the doctor while promptly sending the doctor's operating instructions to the surgical robot, significantly shortening data processing and transmission times and reducing end-to-end latency.
In cross-regional multi-center collaboration scenarios, distributed transaction management faces the practical challenge of the Byzantine Generals' Problem. An improved three-phase commit protocol (3PC) combined with the RAFT consensus algorithm can compress the time required for instrument status synchronization to within 50ms. During implementation, the system uses logical clocks instead of physical clocks for event sequencing and precisely locates data conflicts through vector clock technology. When the primary and backup operating tables receive operating instructions simultaneously, a multi-copy consistency mechanism based on the Paxos protocol ensures that all nodes execute the same instruction sequence. This design enables the system to maintain a strong consistency level with an RPO (Recovery Point Objective) of 0 in the event of a single-region failure, ensuring surgical continuity and safety.
Ensuring service quality in multi-service stream parallel transmission scenarios requires the construction of a multi-level intelligent scheduling system. A QoS controller based on deep reinforcement learning can analyze the priority characteristics of different service streams, such as surgical operation instructions, 4K image streams, and vital sign data, in real-time. When network bandwidth utilization reaches an 85% warning threshold, the system automatically initiates a traffic shaping mechanism to prioritize the transmission bandwidth for robotic arm control signals. Practical tests show that this dynamic strategy can reduce the end-to-end latency standard deviation of critical service streams from 15.6ms to 2.3ms, significantly enhancing the surgical experience for surgeons.
Take a remote cardiac intervention surgery conducted at a tertiary grade-A hospital as an example. This surgery utilized a remote surgical system based on the USR-EG628 industrial personal computer. During the procedure, the USR-EG628 IPC collected real-time data such as cardiac images, force feedback from robotic arms, and positional information, and rapidly transmitted this data to the remote control center via 5G network slicing technology. Based on the real-time transmitted data, the doctor sent instructions to the surgical robot through the operating console. The USR-EG628 IPC promptly sent the doctor's instructions to the surgical robot while monitoring and providing feedback on the robot's execution in real-time.
During the surgery, the system employed edge computing technology to preprocess cardiac images locally in the operating room, extract key features, and reduce data transmission and processing times. Distributed transaction management technology ensured instruction synchronization and state consistency between the primary and backup operating tables. In the event of a primary operating table failure, the backup table could swiftly take over the surgery, ensuring surgical continuity. Intelligent QoS scheduling technology allocated network bandwidth reasonably based on the priority of different service streams, prioritizing the transmission of robotic arm control signals and ensuring precise surgical operations.
Through the application of these key technologies, the remote cardiac intervention surgery was successfully completed, with end-to-end operational latency controlled within 200 milliseconds, meeting surgical requirements. The patient recovered well postoperatively, fully demonstrating the feasibility and effectiveness of IPC low-latency control guarantee technology in remote surgeries.
With the continuous development of technologies such as the Internet of Things (IoT), 5G, and artificial intelligence (AI), low-latency control guarantee technologies for remote surgical robots will usher in new development opportunities. In the future, remote surgical systems will become more intelligent and automated, with IPCs possessing stronger computing power and data processing capabilities, enabling more precise control and decision-making.
On the one hand, the further evolution of 5G technology will provide faster and more stable network support for remote surgeries. The research and development of 6G technology are also progressing gradually, with the potential to achieve even lower latency and higher reliability, bringing new breakthroughs to the development of remote surgeries. On the other hand, AI technology will play a more significant role in remote surgeries. Through deep learning algorithms, IPCs can analyze and predict data during surgerries, identify potential risks and issues in advance, and provide decision support for doctors, improving surgical safety and success rates.
Furthermore, the application scenarios of remote surgical robots will continue to expand. In addition to current cardiac intervention surgeries and brain surgeries, they will find applications in more fields, such as orthopedic surgeries and ophthalmic surgeries, in the future. Simultaneously, remote surgeries will deeply integrate with smart healthcare, medical big data, and other fields, forming a more comprehensive medical ecosystem and providing patients with higher-quality and more efficient medical services.
Low-latency control guarantee for remote surgical robots is a crucial research direction in the medical technology field. As a key device for achieving low-latency control, the development and innovation of industrial personal computers will lay a solid foundation for the widespread application and promotion of remote surgeries. With continuous technological advancements, we have reason to believe that remote surgeries will become a vital model for future healthcare, bringing new blessings to human health.
