title: MARS, a multi-agent system for assessing rowers' coordination via motion-based stigmergy.
abstract: A crucial aspect in rowing is having a synchronized, highly-efficient stroke. This is very difficult to obtain, due to the many interacting factors that each rower of the crew must perceive. Having a system that monitors and represents the crew coordination would be of great help to the coach during training sessions. In the literature, some methods already employ wireless sensors for capturing motion patterns that affect rowing performance. A challenging problem is to support the coach's decisions at his same level of knowledge, using a limited number of sensors and avoiding the complexity of the biomechanical analysis of human movements. In this paper, we present a multi-agent information-processing system for on-water measuring of both the overall crew asynchrony and the individual rower asynchrony towards the crew. More specifically, in the system, the first level of processing is managed by marking agents, which release marks in a sensing space, according to the rowers' motion. The accumulation of marks enables a stigmergic cooperation mechanism, generating collective marks, i.e., short-term memory structures in the sensing space. At the second level of processing, information provided by marks is observed by similarity agents, which associate a similarity degree with respect to optimal marks. Finally, the third level is managed by granulation agents, which extract asynchrony indicators for different purposes. The effectiveness of the system has been experimented on real-world scenarios. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and initial experimental setting.
authors.affiliation: Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, Pisa 56122, Italy. m.cimino@iet.unipi.it.
authors.forename: Marco
authors.initials: M
authors.lastname: Avvenuti
authors.forename: Daniel
authors.initials: D
authors.lastname: Cesarini
authors.forename: Mario G C A
authors.initials: MG
authors.lastname: Cimino
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D054874:Athletic Performance / Q000502:physiology*; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods*; D009068:Movement / Q000502:physiology*; D012767:Ships; D013647:Task Performance and Analysis
references.citation: J Biomech. 2004 Jul;37(7):969-76
references.pmid: 15165867
references.citation: Sensors (Basel). 2009;9(9):7069-82
references.pmid: 22423204