A Nonlinear Analysis of Nociceptive Flexion Reflex Changes Before and After Acute Inflammation

Objectives: The nociceptive flexion reflex (NFR) is used as a pseudo-objective measure of pain that is measured using electromyography (EMG). EMG signals can be analyzed using nonlinear methods to identify complex changes in physiological systems. Physiological complexity has been shown to allow a wider range of adaptable states for the system to deal with stressors. The purpose of this study was to examine changes in complexity and entropy of EMG signals from the biceps femoris during non-noxious stimuli and noxious stimuli that evoked the NFR before and after acute inflammation. Methods and Materials: Twelve healthy participants (25.17y ± 3.43) underwent the NFR protocol. EMG signal complexity was calculated using Hurst Exponent (H), determinism (DET), and recurrence rate (RR), and Sample Entropy (SampEn). Results: RR (∼200%), DET (∼70%), and H (∼35%) were higher and SampEn was reduced (∼50%) during the noxious stimulus that evoked the NFR compared to non-noxious stimuli. No significant differences were found for any of the complexity and entropy measures before and after exercise-induced inflammation ($p<0.05$). Reduced complexity (increased H, DET, and RR) and increased regularity (SampEn) reflect reduced adaptability to stressors. Conclusions: Nonlinear methods such as complexity and entropy measures could be useful in understanding how a healthy neuromuscular system responds to disturbances. The reductions in complexity following a noxious stimulus could reflect the neuromuscular system adapting to environmental conditions to prevent damage or injury to the body.