33

med

Precision at the
Speed of Light.

Replacing mechanical saws with robotic cold-laser osteotomy and bionic integration to safely dismantle 22 years of spinal fusion.

Discover the Roadmap

I. The Novel Approach

Leaving the Bone Saw in the Past.

The legacy approach to orthopedic surgery relies on spinning mechanical drills and saws. These tools cause massive friction, heat-induced tissue necrosis, and bone dust debris that fundamentally impairs healing.

33med is pioneering the use of Cold Laser Osteotomy for complex spinal interventions. Utilizing an Er:YAG (Erbium-doped Yttrium Aluminum Garnet) laser mounted on a robotic arm and guided by an optical navigation system, we induce a photothermal effect that results in the precise photoablation of bone.

The Biological Win
100% Non-Contact

Completely vibration-free execution, eliminating the mechanical trauma of traditional milling.

Cellular Preservation

Zero heat-induced necrosis and drastically reduced carbonization.

Architectural Integrity

Preserves the trabecular architecture and pores of the bone, resulting in biologically open cut surfaces primed for hardware integration.

Zero Debris

Eliminates bone dust, protecting the highly sensitive dural sac and spinal cord from surgical fallout.

II. Open-Source Surgical Robotics

Standing on the Shoulders of Robotic Giants.

We do not need to invent robotic hardware from scratch. The global research community has already open-sourced the equivalents of the most advanced surgical robots. 33med leverages these foundational platforms, wiring them into our proprietary AI-agent framework:

The Raven-II

The gold standard open-source surgical robot platform. Built for tele-robotic surgery and running on the Robot Operating System (ROS), we utilize its architecture to test autonomous tool motions and integrate multi-degree-of-freedom force sensors directly into instrument tips.

The da Vinci Research Kit (dVRK)

Utilizing common APIs and ROS, we leverage the dVRK to train machine learning algorithms that estimate physical force. This grants our robotic framework a digital sense of "touch," ensuring microscopic precision in highly constrained spatial environments.

III. The Digital Twin Surgical Roadmap

From Cloud Computation to Physical Execution.

How do we safely mill away 22 years of fused syndesmophytes without severing the spinal cord? We execute the surgery in the cloud before a single physical cut is made.

1
The Navigation Map

We import a high-resolution 3D CT scan of the fused spine directly into a Gazebo/ROS 2 physics simulation.

2
The Vector Planning

Within the software, we map the exact geometric trajectories required to separate fused bone from healthy vertebrae. Because a laser can execute complex 3D geometries, we plan interlocking "puzzle piece" cuts for our new titanium hardware to seamlessly slot into.

3
The Simulation Execution

We run a digital simulation of a Raven-II style arm executing the cuts. The cloud instance runs a continuous tracking algorithm—if the "digital patient" breathes or shifts by a single millimeter, the optical tracking instantly adjusts the robotic arm to keep the laser focused on the exact microscopic coordinate.

4
The Robotic Milling

Powered by ROS 2 and MoveIt 2 motion planning, the physical robotic arms flawlessly mirror the simulated collision-free trajectories to safely extract the diseased osteogenic structure.

IV. The Bionic Spinal Endoskeleton

Bridging Biological Intent with Synthetic Architecture.

We are not just removing diseased bone; we are replacing the mechanical chassis with an articulated, biocompatible robotic framework that mimics a healthy 6-degrees-of-freedom spine.

Neural Integration (The Actuation Bridge)

Utilizing an OpenBCI headset and the BrainFlow library, we acquire and parse EEG/EMG data. We train local machine learning models to map specific neural firing patterns to intended physical movements, creating a seamless software bridge between biological intent and the synthetic chassis.

Biomaterials Discovery (The Integration Layer)

Using open-source AI chemistry tools like RDKit and the Materials Project API, we computationally screen for advanced metamaterials and surface coatings. Our goal is to synthesize structures that encourage existing back musculature to anchor to the new hardware, while actively repelling the inflammatory AS pathways that cause unwanted bone growth.

The paradigm shift in hard-tissue robotics.

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