Brain computer music interface (BCMI): supporting mental disorder treatments

• Grant number: 20/14115-8
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2021
• End date: July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: João Luís Garcia Rosa
• Grantee: João Luís Garcia Rosa
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated researchers: Graziela Bortz

Abstract

Music can change our emotions, influence our mood and ultimately affect our health. Music therapy is one of the oldest methods used to treat neurological disorders. Therefore, the combination of the music therapy process with electroencephalography (EEG)-based human emotion recognition algorithms can be a useful approach. Thus, it would be possible to identify the user's emotional state and compose a song based on this biofeedback. Thus, music therapy could be adjusted according to the patient's needs, considering that the songs composed by the algorithm can induce new emotions with sound stimuli to that individual. A general algorithm of music therapy for people with mental disorders is proposed in order to use EEG for musical composition allowing to adapt the therapy to the predened time of treatment and adjust the music therapy session to the emotional state of the user. The purpose is that this technology can really improve the lives of people with mental disorders and meet their therapeutic needs. For this, we intend to use Event-Related Potentials (ERPs) and the Stationary State Visual Evoked Potential (SSVEP), which are well-known patterns in the electroencephalography (EEG) records. These types of brain signals are used for different applications in the Brain-Computer Musical Interface (BCMI). For the prototyping of the project, the Python language will be used, as it has a large arsenal for signal processing and pattern recognition. Subsequently, for performance issues, the C++ language will be used. In principle, the evaluation will take place through tests with the database that will be obtained during this project. This base will be the gold standard, since the data will be collected and tested. In the second phase of the project, the user experience will be evaluatedusing forms that are commonly used to evaluate BCMI studies. (AU)

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

DE AGUIAR NETO, FERNANDO SOARES; GARCIA ROSA, JOAO LUIS; IEEE. Impact of Sampling Rate and Eye-Condition on Resting Quantitative EEG. 2022 SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS (SPA), v. N/A, p. 6-pg., 2022-01-01. (20/14115-8)