Brain Music Projects

Musical Biofeedback

Music Biofeedback

The Brain Music Lab at Georgia Tech has unique facilities allowing for online recording of EEG (brainwave), ECG (heart beat), EDA (skin response), temperature, breathing, and other measures of physiological response. We develop algorithms to convert these signals into music and sound, and engineer use-cases to apply biofeedback systems to creative, medical, and research problems. Past and current projects include brain-body music performance, epileptic seizure detection, collaborative sensing, and empathy building.


  • Grace Leslie, Vijay Thadani, Barbara Jobst. (2018). "A Novel Sonification Method Reveals Spectral and Spatial Features of Epileptiform EEG Activity," in Proceedings of Conf. American Epilepsy Society.
  • Grace Leslie, Rosalind Picard, Simon Lui. (2015). "Towards a System for Affective, Musical Neurofeedback Using EEG and Expressive Gesture," in Proceeding of 1st International Workshop on Brain Computer Music Interfacing, Plymouth, UK.
  • Tim Mullen, Alexander Khalil, Tomas Ward, John Iversen, Grace Leslie, Richard Warp, Matt Whitman, Victor Minces, Aaron McCoy, Alejandro Ojeda, Nima Bigdely-Shamlo, Mike Chi and David Rosenboom. (2015). "TMindMusic: Playful and Social Installations at the Interface Between Music and the Brain," in More Playful User Interfaces, ed. Anton Nijholt, Springer-Verlag.

Emotion Classification

Analysis of Affective Response to Music

Can we train a system to identify and understand—perhaps even empathize—with the feeling a piece of music invites in a dedicated listener? We record brain and physiological data as listeners engage in musical activities, and develop ways to analyze and predict their affective response.


  • Grace Leslie, Alejandro Ojeda, Scott Makeig. (2014). "Measuring and Classifying Musical Engagement using EEG and Motion Capture," in Society for Human Brain Mapping (HBM).
  • Grace Leslie, Alejandro Ojeda, and Scott Makeig. (2013). "Towards an Affective Brain-Computer Interface Monitoring Musical Engagement," Affective Computing and Intelligent Interaction (ACII)
  • Grace Leslie, Alejandro Ojeda, and Scott Makeig. (2013). "Measuring Musical Engagement via Expressive Movement and EEG Brain Dynamics," Presented at Society for Music Perception and Cognition (SMPC)
  • Scott Makeig, Grace Leslie, Tim Mullen, Devapratim Sarma, Nima Bigdely-Shamlo, Christian Kothe. (2011). "First Demonstration of a Musical Emotion BCI," Affective Computing and Intelligent Interaction. Springer Lecture Notes in Computer Science 6975:487-496.

Musical Brain Stimulation

Musical Brain Stimulation

In collaboration with the Jobst Lab at Dartmouth-Hitchcock Medical Center and the Singer Lab at Georgia Tech’s Department of Biomedical Engineering, we are engineering new musical stimuli designed to produce beneficial brain rhythms to mitigate diseases such as Epilepsy and Alzheimer’s.

Brain/Body Music Performance

Computer musicology tools and systems

We are developing new music performance paradigms with the help of the technologies described on this page. One example is Vessels, an ongoing performance project by Grace Leslie. It represents several years of engineering, some of it collaborative, and an equal number of years of involvement with music-based meditation practices using brain waves as a means of biofeedback training. This recording reveals brain waves as converted into a sound by means of an algorithm that imprints their spectrum onto a bank of recorded samples of flute and singing voice sounds. The result is a slowly transforming architecture of sound driven by body physiology.