Latest / The Edge Computing Podcast with Fexingo: Local Compute, CDNs, and Distributed Infrastructure / How Edge Computing Is Reshaping Real-Time Robotic Surgery
Transcript
- Lucas: There's a moment in robotic surgery that surgeons talk about — the moment you lose the sense of touch. Luna: Right, because most surgical robots today don't give haptic feedback. You're essentially operating with video only. Lucas: Exactly. And that's a problem, because when you're suturing tissue, you need to feel how much tension you're applying. Without that, there's a higher risk of tearing. But a handful of hospitals are now using edge computing to change that. Luna: How does edge help with haptics? Isn't the delay mostly in the robot's actuators? Lucas: Partly, but the bigger bottleneck is the video and sensor data pipeline. In a traditional setup, the surgical console sends commands up to a cloud server, the server processes the video feed, and sends it back — that round trip can add 50 to 100 milliseconds of latency. For haptic feedback to feel natural, you need under 10 milliseconds. Luna: So edge nodes local to the operating room cut that loop. Lucas: Exactly. Take the case of Nebraska Medicine — they piloted a system where they installed a small edge server inside the OR itself. The robot's video and sensor data never leave the room. That dropped latency from about 50 milliseconds to under 5. Suddenly, the surgeon could feel tissue resistance in real time. Luna: That's a massive leap. And it's not just haptics — lower latency also means higher resolution video, right? Lucas: Right. With cloud-dependent systems, you often have to compress the video to fit bandwidth, which loses detail. With edge processing, you can run full 4K video locally. That makes a difference when you're trying to identify tiny blood vessels. Luna: So the edge is doing both the haptic loop and the video rendering. Lucas: Yes. And in some setups, it's also running AI models to highlight suspicious tissue in real time — like identifying tumor margins during a resection. But that's still experimental. Luna: What about reliability? If the edge node fails mid-surgery, you can't just fall back to the cloud with a 50-millisecond lag. Lucas: That's the hard part. The Nebraska team used redundant edge nodes — two servers in the same rack, mirrored. If one fails, the other takes over within a few milliseconds. They also kept a cloud link as a cold backup, but they never had to use it. Luna: Interesting. So the architecture is designed for local-first, with the cloud as a safety net. Lucas: Exactly. And that's a model you see more broadly in edge computing — local compute for real-time decisions, cloud for analytics and training. In surgery, though, the stakes are obviously a lot higher. Luna: What about bandwidth? Even if the video stays local, you still need to stream it for training or remote observation. Lucas: That's where 5G network slicing comes in. The hospital can carve out a dedicated slice of the network for the surgery, with guaranteed latency and throughput. That way, if you're doing a remote proctoring session — where an experienced surgeon watches a trainee from another hospital — the video feed gets priority over, say, someone streaming Netflix in the waiting room. Luna: Right, so edge plus network slicing gives you end to end quality of service. Lucas: And that's critical because one of the biggest promises of robotic surgery is democratizing access. Right now, most surgical robots are in big teaching hospitals. But with low-latency remote control, a specialist in Chicago could assist a surgery in rural Nebraska. Luna: That Nebraska pilot — was that remote or local? Lucas: It was local — the surgeon and robot in the same OR. But they're planning a remote phase where the surgeon is in Omaha and the robot in a small town two hours away. The edge node will be at the robot site, not the surgeon's console, so the latency is still low for the robot's control loop. Luna: That makes sense. The critical path is from the robot to the edge and back. The surgeon's input just travels over a standard internet link. Lucas: Exactly. And they're targeting under 20 milliseconds total round trip for the remote case, which is feasible with fiber and 5G. That would be a game-changer for rural healthcare. Luna: It really would. And speaking of making things happen — a quick honest thing. This podcast is ad-free, and it stays that way because a handful of listeners chip in monthly through buy me a coffee dot com slash fexingo. That literally funds the production of shows like this. Lucas: Yeah, no sponsors, no pop-ups. Just listeners who find value in these deep dives and decide to support. If today's conversation gave you something useful, consider joining that group. Luna: Alright, back to surgery. Lucas, one thing I'm curious about — what's the regulatory timeline for these edge-enabled systems? Lucas: That's the big question. The FDA has cleared robotic systems for years, but they haven't specifically certified an edge-based haptic feedback loop. The Nebraska team is working with the FDA on a de novo classification — meaning it's a new type of device. They expect a decision by early 2027. Luna: So we're maybe a year away from commercial availability. Lucas: Roughly. And there are companies like Vicarious Surgical and CMR Surgical that are building edge capabilities into their next-gen platforms. They're all targeting that sub-10-millisecond haptic loop. Luna: What about the AI piece — real-time anomaly detection during surgery? Is that closer or further out? Lucas: Further out, I think. There's research at Johns Hopkins where they run a neural network on an edge GPU to detect unexpected tool motions — like if the robot starts drifting. It works in simulation, but clinical validation is at least two years away. Luna: So for now, it's haptics and video. Which is already huge. Lucas: It's a real step forward. The thing is, edge computing in surgery isn't just about speed — it's about making the surgeon feel present. And that's the hardest thing to replicate remotely. Luna: Yeah, that sense of presence. If edge can deliver that, it changes who gets access to the best surgical care.