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| Augmented Intelligence-Based Interference Pattern Analysis (AI-IPA) in Concentric Needle Electromyography |
Augmented Intelligence-Based Interference Pattern Analysis (AI-IPA) in Concentric Needle Electromyography
Sanjeev D Nandedkar, Paul E Barkhaus
Abstract
Introduction/aims: To add objectivity to the routine needle electromyography examination, we describe an "Augmented Intelligence" based interference pattern (IP) analysis method that mimics the subjective assessment by quantifying IP fullness, discreteness, amplitude, pitch, and motor unit firing rate (FR).
AVEMG adds objectivity to routine needle electromyography by using an Augmented Intelligence–based interference pattern (IP) analysis that mimics subjective assessment. The algorithm relies on simple, easily interpretable measurements, providing quantitative data to support the electromyographer’s evaluation. When implemented online, it can guide the operator without increasing procedure time or altering recording technique, and the measurements can be included in reports to support study findings. Similar in concept to autoSCORE, AVEMG streamlines testing and represents a game-changing innovation from Natus.
