Bodily expressed emotion understanding through integrating Laban movement analysis

Body movements carry important information about a person's emotions or mental state and are essential in daily communication. Enhancing the ability of machines to understand emotions expressed through body language can improve the communication of assistive robots with children and elderly users, provide psychiatric professionals with quantitative diagnostic and prognostic assistance, and aid law enforcement in identifying deception. This study develops a high-quality human motor element dataset based on the Laban Movement Analysis movement coding system and utilizes that to jointly learn about motor elements and emotions. Our long-term ambition is to integrate knowledge from computing, psychology, and performing arts to enable automated understanding and analysis of emotion and mental state through body language. This work serves as a launchpad for further research into recognizing emotions through analysis of human movement

Smart Health Monitoring System: A Human-Centered Design

Dolzodmaa Davaasuren, Jordy Timothy, Askar Zhapbassov, Tahmeed Rafee, Prim Boonwisut, and Raymond Tanudjaja are fourth-year students in industrial engineering at Purdue University. They all share a common interest in the health care industry. In this article they describe how they developed a health monitoring device prototype within the course titled Work Analysis and Design II (IE 486)