Artificial neural networks for analyzing inter-limb coordination: the golf chip shot

Motor control research relies on theories, such as coordination dynamics, adapted from physical sciences to explain the emergence of coordinated movement in biological systems. Historically, many studies of coordination have involved inter-limb coordination of relatively few degrees of freedom. This study looked at the high-dimensional inter-limb coordination used to perform the golf chip shot toward six different target distances. This study also introduces a visualization of high-dimensional coordination relevant within the coordination dynamics theoretical framework. A specific type of Artificial Neural Network (ANN), the Self-Organizing Map (SOM), was used for the analysis. In this study, the trajectory of consecutive best-matching nodes on the output map was used as a collective variable and subsequently fed into a second SOM which was used to create visualization of coordination stability. The SOM trajectories showed changes in coordination between movement patterns used for short chip shots and movement patterns used for long chip shots. The attractor diagrams showed non-linear phase transitions for three out of four players. The methods used in this study may offer a solution for researchers from a coordination dynamics perspective who intend to use data obtained from discrete high-dimensional movements.     

Attention support in digital environments. Nine questions to be addressed

Research in attention aware systems, i.e. systems that support users in their attentional choices, promises to address many of the problems related to information overload, cyber collaboration, and mobility, by providing features helping users in coping with attentional limitations. However, the design of attention aware systems necessitates a deep understanding of human attentional processes, of the knowledge a system needs to support those processes, and of the manner in which such knowledge may be acquired. Because the conceptualization of such systems requires understanding users' cognitive states in terms of their past interactions with the environment, the interactivist framework may provide a strong basis for analyzing attention aware systems.This paper briefly introduces the services that attention aware systems may provide, suggests how attention may be modeled within the interactivist framework, and proposes nine questions that may be answered within such framework to gain the knowledge necessary for the creation of attention aware systems.