Telematic performance enforced by the pandemic: NeuroKnitting Beethoven

ABSTRACT

The interactive performance NeuroKnitting Beethoven was conceived as a live work combining music, neurofeedback and algorithmic knitting to commemorate Ludwig van Beethoven’s 250th anniversary and to provide an alternative experience of the classical music canon. This article describes how, due to travel restrictions during the COVID pandemic, the interactive performance became also a telematic project. Apart from the practical considerations regarding the technical execution and adaptation of the work, we focus on the opportunities provided by this transition. We further reflect on how meanings and dynamics ingrained in the technical media deployed by the artists are uncovered and actualised in a new context. Taking the concept of data sensification as our starting point, we examine the capability of biometric data for establishing ‘telepathic’ connections and the latent imaginative potential of EEG technology that underscores its cultural history. In the context of social distancing during the Covid pandemic, when real-time video and sound connections were found to be an inadequate surrogate for in-person communication, we argue that sensification of brain data could be a means for creating an alternative space of remote intimacy and for providing an experience of ‘psychic’ connection between the participants.

KEYWORDS:

• EEG
• interdisciplinary performance‌
• biometric data
• telematic art
• data experience

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 https://var-mar.info/the-rhythm-of-city/

2 https://var-mar.info/neuroknitting/

3 https://var-mar.info/spampoetry/

4 https://var-mar.info/circular-knitic/

Additional information

Funding

NeuroKnitting Beethoven art project was commissioned by Goethe Institute Asia and curated by Susa Pop from Public Art Lab. MSC is supported as a CUDAN research fellow and ERA Chair for Cultural Data Analytics, funded through the European Union’s Horizon 2020 research and innovation program [grant number 810961]; HKUST(GZ) Start-Up Fund.

Notes on contributors

Varvara Guljajeva

Dr Varvara Guljajeva is an artist and researcher holding the position of Assistant Professor in Computational Media and Arts at the Hong Kong University of Science and Technology (Guangzhou).

Mar Canet Sola

Mar Canet Sola is an artist and researcher. Mar is a PhD candidate and research fellow at Cudan research group in BFM Tallinn University. Varvara and Mar form an artist duo Varvara & Mar since 2009.

Iurii Kuzmin

Iurii Kuzmin is a PhD student in Computational Media and Arts at HKUST(GZ) investigating sonic interfaces.