Due to the critical function and susceptibility to loading-related issues of the knee joint, the development of novel examination methods is beneficial. Vibroarthrography (VAG) is a method for analyzing vibrations generated by the knee joint in motion. While extensive literature exists on VAG analysis in the discrete, classification context, this study analyzed VAG signals in a regressive, i.e., continuous one. Such approach allows for more nuanced analysis, providing qualitative conclusions. The relationship was investigated between VAG signals and external loads in asymptomatic male participants performing squats with varying weights. A sample of 38 male asymptomatic participants was analyzed, with each participant executing 8 sets of squat exercises with different loads (from 0 to 70 kg with 10 kg increments; random ordering across participants). Linear mixed models regression analysis was used to model the relationships between selected VAG features and external loads, providing quantitative insights into the mechanical function of the knee joint. The analysis showed that power of the signal is positively correlated with external load, and lower frequencies contain proportionally more power with increasing load. These findings suggest that VAG may serve as a sensitive tool for detecting changes in joint arthrokinematics under varying loads. The regression analysis provided quantitative insights and continuous relationships, offering potential for clinical decision support systems in evaluating joint function and personalized treatment planning.