基于Logistic-Fisher的老龄陪伴机器人外观形态评价方法

Appearance Evaluation Method of the Elderly Companion Robot Based on Logistic-Fisher

目的提出一种基于眼动追踪的老龄陪伴机器人的外观形态评价方法。方法首先借助眼动实验,获得老年人观看陪伴机器人时的眼动特征,提取眼动指标、心率指标与被试变量,利用SPSS23.0软件平台对变量信息进行描述统计和二元Logistic回归分析;其次根据老年人的生理和心理的特殊性将老龄陪伴机器人的外观形态评价定义为二分类问题,以影响显著性最强的几个因子作为判别因子建立Fisher判别函数模型,并进行实验验证。结果性别、年龄、文化程度、心率指标均对陪伴机器人外观关注度无显著影响;总注视时间对其产生显著负向影响,平均注视时间、注视次数产生显著正向影响,判别模型预测样本与实际样本相比准确度为91.0%。结论 Logistic-Fisher方法准确度较高,为构建老龄陪伴机器人的外观形态设计评价体系提供了一种可行的技术途径。

The purpose of this paper is to propose a method for evaluating the appearance of an elderly companion robot based on eye tracking. Obtain the eye movement characteristics of the elderly when watching the companion robot through eye movement experiments, extract eye movement indicators, heart rate indicators and test variables, and use SPSS23.0 software platform to perform descriptive statistics and binary Logistic regression analysis on the variable information. Secondly, the appearance evaluation of the companion robot is defined as a two-category problem based on the physiological and psychological particularity of the elderly. Several factors with the strongest influence in the regression are used as the discriminant factors to establish a Fisher discriminant function model and perform experimental verification. Gender, age, education level, and heart rate indicators have no significant effect on the appearance attention of the companion robot;the total fixation duration has a significant negative effect, and the average fixation duration and the number of fixations have a significant positive effect. The accuracy of the discriminant model prediction sample compared with the actual sample is 91.0%. The Logistic-Fisher method is generally highly accurate, and it provides a feasible technical way to realize the appearance design evaluation of the elderly companion robot.