Original Portfolio of Compositions

Student thesis: Phd


This portfolio of compositions uses novel biometrics from gestural interfaces called Myo armbands to compose five pieces of electroacoustic music within a continuum of spatial environments, ranging from the real to the virtual. The portfolio achieves this by processing biometric data from the Myo armbands within developed software (using Max 8), applying machine learning to such data (via Wekinator) and mapping predictive outputs to audiovisual materials across the spatial continuum. The results of this approach show how unique compositional affordances can be created when using biometrics within different spatial environments and how implementing machine learning methods can help to create such opportunities. The outcomes are presented via five composed portfolio works, three published papers within the scientific community, and numerous music performances navigating the overlapping areas of music composition and computer science. By using novel biometrics to compose music within a continuum of space, this interdisciplinary research topic contributes original knowledge to both the fields of music composition and computer science (human-computer interaction).
Date of Award31 Dec 2022
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorRicardo Climent (Supervisor) & Richard Allmendinger (Supervisor)


  • AR
  • Mixed Reality
  • MR
  • Extended Reality
  • XR
  • Oculus Quest
  • Electromyographic
  • Performance
  • Guitar
  • Violin
  • Myo
  • Piano
  • Augmented Reality
  • Oculus Quest 2
  • VR
  • Music
  • Interactive Composition
  • Composition
  • Unreal Engine
  • Unity
  • EMG
  • Biometrics
  • Game engines
  • ML
  • Machine Learning
  • Interactive Music
  • Virtual Reality
  • AI
  • Artificial Intelligence

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