Ophthalmic Handpiece Stabilization via Motion Sensor Feedback
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Solution Overview
Problem
Current microsurgical techniques, particularly in ophthalmic surgery, face challenges in performing precise and stable movements due to involuntary hand tremors and movements, which can lead to damage to delicate structures within the eye.
Innovation Solution
A system comprising a handpiece with an end effector for manipulating tissues, a motion sensor to detect handpiece movement, and stabilizing actuators to compensate for tremors and involuntary movements, controlled by a controller that processes the motion sensor data to instruct the actuators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual manipulation is used for microsurgery, then surgical freedom and adaptability are maintained, but movement stability and precision deteriorate due to hand tremors
Solution Approach 1:
A robotic intermediary system is introduced between the surgeon's hand and the surgical instrument. The handpiece contains a motion sensor to detect hand movements and stabilizing actuators to compensate for tremors, creating a mediator that translates intentional hand movements into stable instrument movements while filtering out unwanted vibrations.
Solution Approach 2:
The patent replaces pure mechanical hand manipulation with an electromechanical system. Electrical signals from motion sensors control actuators that mechanically compensate for hand tremors, substituting the mechanical control loop with an automated electromechanical stabilization system.
2Manufacturing precision
If stabilizing actuators are added to the handpiece, then movement precision is improved, but the weight and complexity of the handpiece increase
Solution Approach 1:
The patent changes the parameters of the handpiece by integrating stabilizing actuators with specific weight characteristics. The actuators are designed to provide sufficient stabilization force while minimizing added weight, and the system parameters (actuator strength, sensor sensitivity) are optimized to achieve precision without excessive weight gain.
3Reliability
If motion sensing and active compensation are implemented, then tremor reduction is achieved, but system complexity and control difficulty increase
Solution Approach 1:
The handpiece implements a closed-loop feedback system where motion sensors continuously monitor hand movements, the controller processes this information to identify tremor patterns, and stabilizing actuators actively compensate in real-time. This feedback loop enables automatic tremor reduction without requiring complex manual control from the surgeon.
Data Source
AI summary
A system for performing ophthalmic treatments includes a handpiece configured to be held by a hand of a surgeon. An end effector is mounted to the handpiece and configured to manipulate tissue of a patient, such tissues of the eye when performing an ophthalmic treatment. The system includes a motion sensor configured to sense movement of the handpiece and one or more stabilizing actuators configured to stabilize movement of the handpiece in response to movement of the hand of the surgeon. A controller is coupled to the motion sensor and the one or more stabilizing actuators and is configured to instruct the one or more stabilizing actuators to compensate for motion detected by the motion sensor. The controller may include a high-pass filer with the output of the high-pass filter used to control the stabilizing actuators. The parameters of the high pass filter may be adjusted throughout an ophthalmic treatment.