Využití fNIRS pro hodnocení míry svalové únavy

Abstract

This thesis focuses on the analysis of functional near-infrared spectroscopy (fNIRS) for monitoring muscle oxygenation during physical exercise. The aim was to verify the impact of emitter-detector distance and subcutaneous adipose tissue thickness on the quality of measured signals and the accuracy of detecting the second ventilatory threshold (VT₂), and to extend the analysis by calculating advanced muscle oxygenation metrics. Experimental measurements were conducted on the vastus lateralis muscle during wall-sit and CPET tests using configurations with four different emitter-detector distances. VT₂ detection was performed through polynomial approximation of the deoxyhemoglobin signal, and latency between VT₂ detection and maximal muscle deoxygenation was also analyzed. The results showed that greater adipose tissue thickness and larger sensor distance significantly impaired signal quality and VT₂ detection accuracy. Analysis of advanced metrics (mVO₂ index, T₁/₂, AUC HHb, HbDiff slope, and tHb slope) further demonstrated their sensitivity to exercise type and physiological profile. An illustrative comparison between an athlete and a non-athlete revealed differences in muscle endurance and recovery capacity. The thesis confirmed technological limitations of fNIRS under conditions of increased subcutaneous fat and highlighted the importance of optimizing sensor configurations. The findings may contribute to the development of fNIRS methodologies in sports diagnostics, rehabilitation, and applied physiology.