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Steady-Hand Eye Robot 3.0: Optimization and Benchtop Evaluation for Subretinal Injection.

Alireza Alamdar¹, David E Usevitch¹, Jiahao Wu¹

¹Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD USA.

IEEE Transactions on Medical Robotics and Bionics

|February 2, 2024

Summary

The Steady-Hand Eye Robot (SHER 3.0) enhances robotic surgery for retinal diseases, offering unprecedented precision for subretinal injections. This advancement aims to improve treatments for currently incurable eye conditions.

Keywords:

ophthalmology optimization subretinal injection surgical robotics system design and analysis

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Area of Science:

Ophthalmology
Robotics
Biomedical Engineering

Background:

Current subretinal injection techniques are limited by human motor control, restricting treatment options for many retinal diseases.
Developing precise robotic systems is crucial for advancing surgical interventions in ophthalmology.

Purpose of the Study:

To introduce and validate the Steady-Hand Eye Robot (SHER 3.0), a next-generation robotic platform for precise subretinal injections.
To demonstrate SHER 3.0's capability to achieve clinical standards for targeting accuracy and resolution in retinal procedures.

Main Methods:

Detailed system design and kinematic analysis of the SHER 3.0 robot.
Development and validation of a deflection model for the integrated delta stage, optimizing parameters for precision.
Performance evaluation through five tests measuring accuracy, repeatability, and deflection under load.

Main Results:

The optimized delta stage design achieved a tip accuracy of less than 30 μm and tip repeatability of 9.3 μm and 0.02°.
Measured deflections ranged from 20-350 μm/N, indicating high stability and predictability.
The SHER 3.0 platform meets clinical standards for targeting accuracy and resolution essential for subretinal injections.

Conclusions:

The SHER 3.0 represents a significant advancement in robotic-assisted eye surgery, overcoming limitations of human dexterity.
This robotic platform shows great promise for improving the efficacy and accessibility of treatments for severe retinal conditions.
Future research will focus on refining control models and conducting in vivo testing for clinical translation.