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Research on Measurement and a Modeling of Human Sensitivity for Qualitative Evaluation

用于定性评估的人类敏感性测量和建模研究

基本信息

批准号：
09838035
负责人：
KAGEYAMA Ichiro
金额：
$ 1.86万
依托单位：
Nihon University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 1999
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-09838035/
关键词：
Sensitivity Mental Workload Hart Rate Variability Factor Analysis Neural Network RRV method Dynamics 心拍のゆらぎ呼吸性不整脈心負担生体反応 R-R値

项目摘要

The method of the human sensitivity or Mental WorkLoad (MWL) evaluation in the human-machine-environment system is divided into classes. One is the subjective evaluation, and the other is objective. The subjective evaluation depends on the age, skill, and physical condition of the subject. Therefore, it is difficult to evaluate with the reproducibility. Also, the viewpoint of the evaluation quantitatively, it is nexessary to shift to the objective evaluation. Therefore, many researches about the MWL using the objective evaluation have been done in recent year. It is though that the human's processing in human-machine-environment system consists of the elements of the human, machine, environment. Therefore, when we estimate the MWL during the control, it is important to consider this integrated element.In this research, the Heart Rate Variability (HRV) is used to the analysis, because it became known that a strong relationship existed between the MWL and HRV. For this analysis, we try to construct the integrated model of the human-machine-environment system using the HRV.The Neural Network System (NNS) is the method of system identification that imitates the information processing of the brain nervous system. It is very suitable for nonlinear identification. Using this system, we construct two kinds of model, one is for evaluation of MWL and the other is for factor analysis to the MWL. As a result, it is found that the output of these models are described the MWL of the panel. And, also, we analysis the main factor to the MWL using the NNS model.From this result, we confirm that the method has a possibility to analyze the MWL not only qualitatively but also quantitatively.

对人-机-环境系统中人的敏感度或脑力负荷(MWL)的评价方法进行了分类。一是主观评价，二是客观评价。主观评价取决于受试者的年龄、技能和身体状况。因此，很难用重复性来评价。另外，在量化评价的观点上，有必要转向客观评价。因此，近几年来，人们对基于客观评价的最低生活质量进行了大量的研究。认为人在人-机-环境系统中的加工过程由人、机、环境三个要素构成。因此，当我们在控制期间估计MWL时，考虑这一综合因素是很重要的。在本研究中，心率变异性(HRV)被用于分析，因为众所周知MWL和HRV之间存在着很强的关系。为了进行这一分析，我们尝试使用HRV来构建人-机-环境系统的集成模型。神经网络系统(NNS)是一种模拟大脑神经系统信息处理的系统辨识方法。它非常适合于非线性辨识。利用该系统，我们构建了两种模型，一种是MWL的评价模型，另一种是MWL的因子分析模型。结果发现，这些模型的输出被描述为面板的MWL。并利用神经网络模型对影响MWL的主要因素进行了分析，结果表明，该方法不仅可以定性地分析MWL，而且可以定量地分析MWL。