I focus on the use of bio-data sensors on the performer’s body in a project called W1NGS developed in close collaboration with LWT3, an Italian engineering company researching and developing bio-signalling technologies. They are developing a ‘smart suit’ prototype able to track different physiological processes with the specific purpose of my dance research. The ‘smart suit’ contains 41 sensors to landmark the body for MOCAP (motion capturing), and at least 8 of them register biometric signatures. I focus on muscle tensions (EMG) from superficial muscles. Using S0M_AI as a user testcase for generative choreography means that I combined use of both tools allowing the generation of an experiential choreography that contains uninterrupted feedback signals for the dancer and the audience.
The experiments with bio-data give insights into the three ‘technosomatic’ characteristics: superficial embodied awareness(sensations vs. sensors), geometry in hybrid performance spaces (virtual vs. real), and digital and physical temporalities (embodied reaction time vs. computer processing time). Analysing these characteristics post-practice, we can investigate how dance practices become more resilient and/or adaptive to some of the issues that occur when adapting a conventional dance practice to a technological environment. Accordingly, it is needed to shift the focus from expanding dance awareness through technology to expanding technological awareness in dance practices.
Since few months, W1NGS is being continuously expanding and new features are being integrated in the guide and workshop for technosomatic dance practicing through motion data & biometric (EMG) choreography.