An efficient capacitive sensing scheme for an ophthalmic regional anesthesia training system

Area of Science:

• Ophthalmology
• Medical Simulation
• Biomedical Engineering

Background:

• Ophthalmic regional blocks are essential for eye surgery, requiring precise needle placement to avoid ocular damage.
• Current training methods lack accurate anatomical representation and real-time feedback, posing risks to patients.

Purpose of the Study:

• To develop and validate a novel training system for ophthalmic regional blocks.
• To improve the safety and efficacy of anesthetic techniques through accurate anatomical simulation and feedback.

Main Methods:

• A capacitive sensing scheme was implemented using a rapid-prototyped, anatomically accurate eye model.
• Electrodes were placed along the orbital wall to detect syringe needle depth and proximity to extraocular muscles.
• A data acquisition system recorded displacement currents for real-time feedback.

Main Results:

• The system accurately detected needle depth and proximity to ocular muscles.
• Needle touch of muscles was identified with high accuracy.
• Validation on a prototype system demonstrated practical utility for training.

Conclusions:

• The developed capacitive sensing system offers a valuable tool for training ophthalmic regional blocks.
• This technology enhances trainee performance by providing accurate anatomical feedback and reducing risks.
• The system shows significant potential for improving surgical preparation and patient safety.