Article ID Journal Published Year Pages File Type
261490 Design Studies 2015 28 Pages PDF
Abstract

•Machine learning to detect emotions using non-invasive sensors in design teams.•Effectiveness of approach illustrated with case study.•High accuracy over 90% achieved for detecting many body language poses.•Scalable solutions with potential for further research.

Design team interactions are one of the least understood aspects of the engineering design process. Given the integral role that designers play in the engineering design process, understanding the emotional states of individual design team members will help us quantify interpersonal interactions and how those interactions affect resulting design solutions. The methodology presented in this paper enables automated detection of individual team member's emotional states using non-wearable sensors. The methodology uses the link between body language and emotions to detect emotional states with accuracies above 98%. A case study involving human participants, enacting eight body language poses relevant to design teams, is used to illustrate the effectiveness of the methodology. This will enable researchers to further understand design team interactions.

Related Topics
Physical Sciences and Engineering Computer Science Computer Graphics and Computer-Aided Design
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