EMVIZ (flow) is an interactive artistic visualisation system that maps movement quality data to aesthetic visual representations. The goal of EMVIZ is to communicate complex movement information to an ‘everyday’ audience and support discernment of the experience of complex movement data. EMVIZ (flow) generates dynamic visual representations of human movement qualities derived from a framework of Laban Movement Analysis (LMA), a rigorous, analytical and embodied system for analysing human movement. Movement data is obtained from a real-time wearable sensor classifier supervised learning system that applies an LMA model to extract movement qualities from a moving body in the form of Laban Basic-Effort-Actions (BEA), This movement quality recognition system outputs a stream of Basic-Effort-Action vectors and EMVIZ (flow) maps this stream of data to an autonomous flocking agents system and colour palettes for creating visual representations of movement quality. EMVIZ (flow) was used in an improvised interactive dance performance at the Human Factors in Computing System (CHI) workshop 2011 and exhibited at a Simon Fraser University (SFU) Open House 2011 event. We describe an underlying model to capture and map movement quality to a visualisation system, a data mapping strategy, a generative algorithm, and an application used for visualising movement quality.