Research on the Sensory Feeling of Product Design for Electric Toothbrush Based on Kansei Engineering and Back Propagation Neural Network

Abstract

Over the years, China’s electric toothbrush market has been expanding. Consumers pay more attention to the sensory feeling of product shape, under the premise of product function satisfaction. Therefore, this research collected 215,827 product reviews made by consumers online and 200 samples of varying electric toothbrush samples using a web crawler. Then, 3 groups of representative perceptual words were obtained from the extraction of numerous reviews via Word2vec, factor analysis and hierarchical cluster analysis. Meanwhile, with the help of morphological analysis, design elements of sample shape were de-structured on the 32 representative samples that were extracted from the collected sample using multi-dimensional scaling and hierarchical cluster analysis. On this basis, consumers’ perceptual images were measured using semantic differential scale with 415 valid samples acquired in total. Finally, two relationship models between product design elements and consumers’ perceptual images were established by quantitative theory type I (QTTI) and back propagation neural network. By comparison, the QTTI model has more accurate prediction. This study provides defined design indexes and references for designers’ black box design patterns through establishing an effective model via combining web crawler technology and systematic analysis.