Food Texture Quantification Using a Magnetic Food Texture Sensor and Dynamic Time Warping

Abstract

Food texture is an important characteristic related to food preferences. Food texture instruments are used to determine the physical profiles of foods; however, they are not sufficient for detailed evaluation of food texture. In this study, a novel method for the quantitative evaluation of food texture is proposed. The proposed method records time-series data of force and vibration in fractures for different foods that have been estimated to have a similar food texture. Then, the dynamic time warping barycenter averaging algorithm is used to determine the standard data based on the recorded time-series data. Finally, the dynamic time warping algorithm is used to calculate the similarity between the measured data and the standard data, which is regarded as the quantitative food texture. The effectiveness of the method was confirmed with experimental results.