The re is a growing number of researchers worldwide working in the field of Brain-Computer Interfacing (BCI). Our work is unique, however, in that we are focused on the development of BCI systems for musical applications and we pay special attention to the development of generative music techniques tailored for such systems. We might call such systems Brain-Computer Music Interfaces (BCMIs). We should clarify that the BCI research community understands a BCI as a system that allows for the control of a machine by thinking about the task in question; e.g. controlling a robotic arm by thinking explicitly about moving an arm. This is an extremely difficult problem. The BCMI-Piano and the InterHarmonium presented in this paper do not employ this type of explicit control. We are not primarily interested in a system that plays a melody by thinking the melody itself; rather, we are furnishing our systems with artificial intelligence so that they can perform their own interpretations of the meanings of EEG patterns. Such machine interpretations may not always be accurate or realistic, but this is the type of human-computer interaction that we wish to address in our work.To date, most efforts in BCI research have been aimed at developing assistive technology to help disabled people communicate or control mechanical devices (such as wheelchairs or prosthetic limbs). Comparatively little has been done to implement BCI technology for musical applications.

This study proposes to use the analysis of physiological signals (electroencephalogram (EEG), electromyogram (EMG), heart beats etc) to control sound synthesis algorithms in order to build biologically driven musical instruments. A real time music synthesis environment and algorithms are developed to map these signals into sound. Finally, a "bio-orchestra", with two new digital musical instruments controlled by the EEGs and EMGs of two bio-musicians demonstrated this concept with a live concert on stage.