Analysis of normal swallowing sounds using nonlinear dynamic metric tools

Several metric tools for quantative analysis of scalar time series have been developed using the theory of nonlinear dynamics. The goal of this work was to study the characteristics of swallowing sound using these metric tools. Takens method of delays was used to reconstruct multidimensional state space representation of the swallowing sounds of 6 healthy subjects (ages 13-30 years, 3 males) being fed thin and thick liquid textures. The optimum time delay for different subjects varied from 3 to 9 samples. False nearest neighbors method was used to obtain proper embedding dimension. The correlation dimension was calculated based on Grassberger-Procaccia algorithm. The results suggest that swallowing sound is well characterized by a small number of dimensions. The largest Lyapunov exponent was also estimated to evaluate the presence of chaos. As the largest Lyapunov exponent for some cases was negative, it may be concluded that swallowing sound is not necessarily a chaotic process.