Output Power Computation and Adaptation Strategy of an Electrosurgery Inverter for Reduced Collateral Tissue Damage.

Area of Science:

• Biomedical Engineering
• Electrical Engineering
• Surgical Technology

Background:

• Electrosurgery faces limitations in sampling speed and arcing nonlinearity, impacting power computation accuracy and leading to collateral tissue damage.
• Accurate power monitoring is crucial for effective electrosurgery and minimizing unintended tissue injury.

Purpose of the Study:

• To investigate sparse- and multi-sampling-based methods for overcoming electrosurgery sampling speed limitations and arcing nonlinearity.
• To explore an impedance-based power adaptation strategy for reducing collateral tissue damage during electrosurgery.
• To demonstrate novel power computation techniques using low-end processors for high-frequency, nonlinearly distorted outputs in biomedical research.

Main Methods:

• Experimental investigation of sparse-sampling and multi-sampling power computation methods on a gallium-nitride (GaN)-based high-frequency inverter prototype (390 kHz output frequency).
• Evaluation of an impedance-based power adaptation strategy to quantify collateral tissue damage (average thermal spread).
• Comparison of proposed methods against conventional electrosurgery techniques.

Main Results:

• Sparse-sampling method achieved power computing errors between 1.43 W and 4.89 W.
• Multi-sampling method demonstrated higher accuracy with errors ranging from 0.02 W to 3.09 W, particularly in the presence of arcing nonlinearity.
• Impedance-based power adaptation reduced average thermal spread to 0.36-0.86 mm, compared to 1.49 mm for conventional electrosurgery.

Conclusions:

• Both sparse- and multi-sampling methods effectively address sampling speed limitations and compute output power with minimal errors.
• The multi-sampling method offers superior accuracy when dealing with arcing nonlinearity.
• The impedance-based power adaptation strategy significantly reduces collateral tissue damage, sensor requirements, and overall cost, paving the way for less invasive electrosurgery.