Train seat comfort evaluation method and system based on multi-source physiological signals

Abstract

The invention, which belongs to the technical field of train seat adjustment information processing, discloses a train seat comfort evaluation method and system based on multi-source physiological signals. After combination of physiological signal data of a subject and a subjective evaluation scale, a train seat comfort database for a group is established by combining a mainstream subjective evaluation method with a physiological-signal-based objective evaluation method; and a train seat comfort evaluation model is established by selecting a LightGBM gradient boosting tree which is a machine learning modeling method with multiple characteristics of rapidness, distribution and high performance. According to the invention, physiological signal data of a tester are inputted into the established train seat comfort evaluation model to obtain a comfort evaluation result. Therefore, the evaluation deviation caused by subjectivity of evaluation personnel is effectively reduced. The irrationality caused by a direct objective analysis method is avoided; and the comfort evaluation accuracy and feasibility of the train seat are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of train seat adjustment, and in particular relates to a train seat comfort evaluation method and system based on multi-source physiological signals. Background technique [0002] Currently, the closest prior art: [0003] To improve the comfort of train seats, it is first necessary to evaluate the comfort of train seats. In the prior art, methods for evaluating the comfort of train seats are mainly divided into subjective evaluation methods and objective evaluation methods. The subjective evaluation method, also known as the psychological evaluation method, is to let the subjects score or describe according to their own comfort level in the form of scales or questionnaires, and finally obtain the comfort level evaluation through mathematical statistical analysis. However, there are also some problems in the operation of this method. If the scale and questionnaire are not well thought out or incomplete, t...

AI Technical Summary

Problems solved by technology

However, the actual physiological and psychological representations of the human body are complex, and there are many features that can be extracted from EEG, ECG, and EMG. The statistical models in the prior art cannot accurately reflect the mapping relationship between human responses and subjective comfort scores.

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