Robotic Electrode Implantation via Fluorescence Triangulation

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Solution Overview

Problem

Conventional surgical techniques, including robotic surgery, face challenges in precisely targeting and inserting implantable devices into biological tissue due to limitations in depth of field, glare, and reflective elements, which hinders the reliable and efficient implantation of devices like brain-computer interface electrodes.

Innovation Solution

A robotic surgery system utilizing fluorescence, specialized lighting, and computer vision techniques to facilitate the implantation of micro-manufactured bio-compatible electrodes in biological tissue, including neurological tissue, by triangulating the 3D location of the electrode using near-UV light and visible light imaging, and engaging it with an insertion needle for precise positioning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If conventional robotic surgery techniques are used, then robotic automation is achieved, but precision in determining positioning and targeting is degraded due to limited depth of field, glare, and reflective elements

Engineering Contradiction:
Improverobotic automationVSAvoidpositioning precision
Core Design Contradiction:
Extent of automationVSMeasurement precision

Solution Approach 1:

The patent applies fluorescence imaging to change the optical properties of tissues during surgery. Fluorescent dyes are introduced to highlight specific tissue structures, blood vessels, and anatomical features, enabling the robotic system to distinguish between different tissue types with high precision despite the presence of glare and reflective elements in conventional imaging

Inventive Principle:
Principle #32Color changes

Solution Approach 2:

The patent introduces an intermediary imaging system that combines fluorescence imaging with robotic control. This intermediary system processes fluorescent signals to generate enhanced visual information that the robotic system can use for precise positioning and targeting, bridging the gap between automation and precision

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If human surgeons perform surgical procedures, then precision in targeting and positioning is achieved, but productivity and scalability are degraded due to manual limitations

Engineering Contradiction:
Improvetargeting precisionVSAvoidsurgical throughput
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces manual surgical manipulation with an automated robotic system that uses fluorescence imaging guidance. The robotic system performs precise targeting, tissue navigation, and implant placement operations automatically, eliminating the productivity constraints of manual surgery while maintaining surgical precision through computer-vision-based control

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If standard imaging techniques are used in robotic surgery, then real-time control is attempted, but reliability is degraded due to limited depth of field and optical interference

Engineering Contradiction:
Improvereal-time controlVSAvoidcontrol reliability
Core Design Contradiction:
Ease of operationVSReliability

Solution Approach 1:

The patent uses fluorescence imaging to change the optical contrast of tissues in real-time during surgery. Fluorescent signals provide high-contrast visualization of tissue boundaries, blood vessels, and anatomical structures, enabling reliable real-time control of the robotic system without the optical interference problems of standard imaging techniques

Inventive Principle:
Principle #32Color changes

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The system enables precise and efficient implantation of electrodes by enhancing the ability to distinguish tissue features and avoid damage to blood vessels, allowing for reliable and repeated insertions of implantable devices, such as electrodes, in biological tissues like the brain.

Implementation Method 1

The system irradiates a polymer portion of the electrode using a near-ultraviolet (near-UV) wavelength of light. The near-UV wavelength is between 300 nanometers (nm) and 425 nanometers. The first light source is a first light emitting diode (LED) or a first laser. The system and/or a first camera obtains a first image of the polymer portion with light fluoresced from the polymer portion in response to the irradiating.

Methodology Applied
Scientific EffectFluorescence: Fluorescence

Implementation Method 2

The system and/or a second light source comprising a second LED or a second laser illuminates an insertion needle using visible light. The system and/or the first camera obtains a third image of the insertion needle illuminated by the visible light.

Methodology Applied
Scientific EffectReflection: Reflection

Data Source

PatentEP3849434B1Computer vision techniques
Publication Date: 2024.09.18 NEURALINK CORP
  • EP3849434B1 patent drawingFigure 1A
  • EP3849434B1 patent drawingFigure 1B
  • EP3849434B1 patent drawingFigure 2

AI summary

Systems and methods that use computer vision techniques in connection with robotic surgery are discussed. A robotic surgery system may 'include an implantable device engagement sub-system, a targeting sub-system, and/or an insertion verification sub-system. The system may use computer vision techniques to facilitate implanting a micro-manufactured bio-compatible electrode device in biological tissue (e.g., neurological tissue such as the brain) using robotic assemblies. The system can attach, via robotic manipulation, the electrode to an engagement element of an insertion needle. The system can further irradiate the electrode using a near-ultraviolet (near-UV) wavelength of light, obtain images of the electrode with light fluoresced from the polymer portion in response to the irradiating, triangulate a 3D location of the electrode, analyze a target tissue contour using computer vision, select an insertion site, and surgically implant the micron-scale electrode at the insertion site via robotic assembly and based on the triangulated location.