利用新型生理数据集和机器学习,在模拟求职面试中检测自闭症成人的压力

IF 2.5 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Accessible Computing Pub Date : 2024-01-08 DOI:10.1145/3639709
Miroslava Migovich, Deeksha Adiani, Michael Breen, A. Swanson, Timothy J. Vogus, Nilanjan Sarkar
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引用次数: 0

摘要

面试过程已被确认为自闭症患者就业的主要障碍之一,这也是自闭症成年人就业不足率和失业率惊人的原因之一。事实证明,减轻面试过程中的压力可以提高面试成绩。然而,为了有效地为受访者和面试官提供有关压力的见解,有必要首先对压力进行有效测量。这项研究探索了通过可穿戴传感技术进行生理压力检测的方法,从而利用监督机器学习技术从正在接受虚拟模拟面试的年轻自闭症成年人那里获得定量压力测量值。研究人员探索了几种监督学习模型,发现弹性网回归(Elastic Net Regression)的准确率最高,单个模型的准确率为 84.8%,而支持向量回归(Support Vector Regression)模型在留一交叉验证(leave-one-out cross validation)的评估下,群体准确率为 75.4%。压力模型的预测结果被用于数据可视化技术,以便从小组和个人的角度对面试过程进行深入分析,这表明可以使用压力模型发现和评估压力趋势。这项研究还填补了生理压力检测文献中的一大空白,为 15 名正在接受模拟面试的自闭症青少年提供了一个包含生理数据和地面实况标签的新数据集。
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Stress Detection of Autistic Adults during Simulated Job Interviews using a Novel Physiological Dataset and Machine Learning
The interview process has been identified as one of the major barriers to employment of autistic individuals, which contributes to the staggering rate of under and unemployment of autistic adults. Decreasing stress during the interview has been shown to improve interview performance. However, in order to effectively provide insights on stress to both interviewees and interviewers, it is necessary to first effectively measure stress. This work explores physiological stress detection through wearable sensing as a means of obtaining quantitative stress measures from young autistic adults undergoing a virtual simulated interview using supervised machine learning techniques. Several supervised learning models were explored and it was found that Elastic Net Regression had the best accuracy with individual models with an accuracy of 84.8% while Support Vector Regression models evaluated with leave-one-out cross validation had a group accuracy of 75.4%. The predictions from the stress model were used with data visualization techniques in order to provide insights on the interview process from both a group and individual viewpoint, showing that stress trends can be found and evaluated using the stress model. This work also addresses a major gap in physiological stress detection literature by presenting a novel dataset of physiological data and ground truth labels for 15 autistic young adults undergoing a simulated interview.
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来源期刊
ACM Transactions on Accessible Computing
ACM Transactions on Accessible Computing COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
6.20
自引率
8.30%
发文量
43
期刊介绍: Computer and information technologies have re-designed the way modern society operates. Their widespread use poses both opportunities and challenges for people who experience various disabilities including age-related disabilities. That is, while there are new avenues to assist individuals with disabilities and provide tools and resources to alleviate the traditional barriers encountered by these individuals, in many cases the technology itself presents barriers to use. ACM Transactions on Accessible Computing (TACCESS) is a quarterly peer-reviewed journal that publishes refereed articles addressing issues of computing that seek to address barriers to access, either creating new solutions or providing for the more inclusive design of technology to provide access for individuals with diverse abilities. The journal provides a technical forum for disseminating innovative research that covers either applications of computing and information technologies to provide assistive systems or inclusive technologies for individuals with disabilities. Some examples are web accessibility for those with visual impairments and blindness as well as web search explorations for those with limited cognitive abilities, technologies to address stroke rehabilitation or dementia care, language support systems deaf signers or those with limited language abilities, and input systems for individuals with limited ability to control traditional mouse and keyboard systems. The journal is of particular interest to SIGACCESS members and delegates to its affiliated conference (i.e., ASSETS) as well as other international accessibility conferences. It serves as a forum for discussions and information exchange between researchers, clinicians, and educators; including rehabilitation personnel who administer assistive technologies; and policy makers concerned with equitable access to information technologies.
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