Neural network-based comfort evaluation method for handheld sports products

Abstract

In order to provide a set of quantitative evaluation of the comfort of hand-held sports products, this study preliminarily constructed the comfort evaluation index system of hand-held sports products from the perspectives of performance, tactile characteristics, quality and appearance, physical stimulation, discomfort, morphological characteristics, user demographic characteristics and hand characteristics. Secondly, 165 groups of data were collected through the experiment, and factor analysis was used to reduce the dimension of the original index. Then neural network was used to establish the mapping relationship between the evaluation index and the comfort evaluation, and the evaluation model of the comfort of hand-held sports products was obtained. The results show that the relative error between the predicted value and the actual value of the network model is basically less than 5% in the practical application of the evaluation method taking the badminton racket as an example, which reflects that the comfort evaluation method can effectively reduce the correlation between the original indexes, achieve the accurate evaluation of the comfort of products, and verify the effectiveness and feasibility of the evaluation method. The combination of neural network and factor analysis can quantitatively analyze and evaluate the comfort of hand-held sports products and provide reliable suggestions for manufacturers to design and produce more comfortable products in the form of data.