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Innermost Echoes: Integrating Real-Time Physiology into Live Music Performances

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Manage episode 443660550 series 3605621
Content provided by Kai Kunze. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kai Kunze or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this paper, we propose a method for utilizing musical artifacts and physiological data as a means for creating a new form of live music experience that is rooted in the physiology of the performers and audience members. By utilizing physiological data (namely Electrodermal Activity (EDA) and Heart Rate Variability (HRV)) and applying this data to musical artifacts including a robotic koto (a traditional 13-string Japanese instrument fitted with solenoids and linear actuators), a Eurorack synthesizer, and Max/MSP software, we aim to develop a new form of semi-improvisational and significantly indeterminate performance practice. It has since evolved into a multi-modal methodology which honors improvisational performance practices and utilizes physiological data which offers both performers and audiences an ever-changing and intimate experience.
In our first exploratory phase, we focused on the development of a means for controlling a bespoke robotic koto in conjunction with a Eurorack synthesizer system and Max/MSP software for controlling the incoming data. We integrated a reliance on physiological data to infuse a more directly human elements into this artifact system. This allows a significant portion of the decision-making to be directly controlled by the incoming physiological data in real-time, thereby affording a sense of performativity within this non-living system. Our aim is to continue the development of this method to strike a novel balance between intentionality and impromptu performative results.

https://dl.acm.org/doi/10.1145/3623509.3633356

  continue reading

41 episodes

Artwork
iconShare
 
Manage episode 443660550 series 3605621
Content provided by Kai Kunze. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kai Kunze or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this paper, we propose a method for utilizing musical artifacts and physiological data as a means for creating a new form of live music experience that is rooted in the physiology of the performers and audience members. By utilizing physiological data (namely Electrodermal Activity (EDA) and Heart Rate Variability (HRV)) and applying this data to musical artifacts including a robotic koto (a traditional 13-string Japanese instrument fitted with solenoids and linear actuators), a Eurorack synthesizer, and Max/MSP software, we aim to develop a new form of semi-improvisational and significantly indeterminate performance practice. It has since evolved into a multi-modal methodology which honors improvisational performance practices and utilizes physiological data which offers both performers and audiences an ever-changing and intimate experience.
In our first exploratory phase, we focused on the development of a means for controlling a bespoke robotic koto in conjunction with a Eurorack synthesizer system and Max/MSP software for controlling the incoming data. We integrated a reliance on physiological data to infuse a more directly human elements into this artifact system. This allows a significant portion of the decision-making to be directly controlled by the incoming physiological data in real-time, thereby affording a sense of performativity within this non-living system. Our aim is to continue the development of this method to strike a novel balance between intentionality and impromptu performative results.

https://dl.acm.org/doi/10.1145/3623509.3633356

  continue reading

41 episodes

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