The installation investigates the interaction of body within confined textile structure (knitted tube 1, hanging + knitted tube 2 on floor) and document body and movement explorations changing the aesthetic expression. The ephemeral embodied explorations are documented by using machine learning model Posenet that can estimate human movement. This will reflect on the outcome of existing methods and studying how the EDI (embodied design ideation) framework can be used to develop new methods for fashion and textile design processes. The EDI (embodied design ideation) method has been actively referred to by the researchers both in the field of human-computer interaction (HCI) and embodied interaction. These methods help to view body and material within the thought context and draw relationship that is used to inform a design. Posenet is used as a sketching tool to document spatial levels and structural characteristics of body while moving. This further identifies how and where movement occurs. The results question the limitation of technology and highlight through experiment when and where Posenet stops identifying body movement.