AUTHOR=Moreu Fernando , Maharjan Dilendra , Zhu Can , Wyckoff Elijah TITLE=Monitoring Human Induced Floor Vibrations for Quantifying Dance Moves: A Study of Human–Structure Interaction JOURNAL=Frontiers in Built Environment VOLUME=6 YEAR=2020 URL=https://www.frontiersin.org/journals/built-environment/articles/10.3389/fbuil.2020.00036 DOI=10.3389/fbuil.2020.00036 ISSN=2297-3362 ABSTRACT=

Human induced dynamic forces on structures are of interest in the area of human-environment interfaces. The research community is interested in characterizing human decisions and providing information on the consequences of human actions to control those human forces more effectively. Dynamic structures can vibrate under human motion. In the context of human–structure interactions (HSI), dance induced vibrations can be quantified with sensors. This data can provide a unique opportunity for dancers to understand the quality of their dance with objective metrics. Previous work in capturing dance moves required wearable sensors attached to the dancer’s body. Often an intrusive process, this method is not scalable if dancers are not familiar with technology and it limits their participation without access to special studios or facilities. If simple, deployable technology could be available to dancers, they could monitor their dance without engineers. This research integrates dancers’ interest in qualifying dance motion and engineering curiosity to study human induced vibrations. As a part of the framework, researchers used two indexes to differentiate between a well synchronized group dance from asynchronous moves. The two indexes are the Harmony Index and the Coordination Index, respectively, and are validated against the Visual Index, a qualitative index obtained from an expert who judged dance moves based on one video capture. The indexes were derived from measurements of the movement of the structure dynamically excited by the dancers, hence quantifying dance coordination. These two indexes are based on time history data obtained from sensors installed on a wooden bridge where dancers performed at different levels of proficiency. The results of this research show that the two indexes sort effectively the quality of the dancers, when validated with the Visual Index. As a result, this research proposes using Low-cost efficient wireless intelligent sensor (LEWIS) to objectively sort different levels of dance quality which could be expanded to study the HSI for design and assessment of the structural systems used for dancing, such as performance halls and ballrooms.