Brain-Computer Interface (BCI) Based Musical Composition

Hamadicharef, Brahim; Xu, Mufeng; Aditya, Sheel

doi:10.1109/cw.2010.32

Cited by 13 publications

(8 citation statements)

References 26 publications

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“…Other researchers [Dan et al 2009, Hamadicharef et al 2010 are exploring this field, creating applications for music composition. Our main objective was to evaluate how to reduce, as much as possible, the training time necessary for using BCI devices.…”

Section: Explicit Approach: Conscious Production Of Single Notesmentioning

confidence: 99%

“…The relationship between emotions and entertainment is obvious, as is the influence of music in human emotional states. While BCI devices represent a challenge in gaming motion control, they have been successfully applied in music production [Dan et al 2009] and composition [Hamadicharef et al 2010]. In our previous work [Conscious and unconscious music from the brain in press] we focused on conscious production of music notes with the aim of developing a prototype for applications in entertainment.…”

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confidence: 99%

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BCI Promises in Emotional Involvement in Music and Games

Folgieri

Zampolini

2014

Comput. Entertain.

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The reliability of commercial non-invasive BCI (brain computer Interface) devices and the lower cost of these EEG-based systems, as well as the equipment's portability, determined the increasing interest in their application in different research fields. The latter feature makes BCI devices particularly suited for entertainment applications, especially given the possibility to detect the mental state of the users. The relationship between emotions and entertainment is obvious, as is the influence of music in human emotional states. While BCI devices represent a challenge in gaming motion control, they have been successfully applied in music production [Dan et al. 2009] and composition [Hamadicharef et al. 2010]. In our previous work [Conscious and unconscious music from the brain in press] we focused on conscious production of music notes with the aim of developing a prototype for applications in entertainment. In this work we trace the state-of-the art of our research and present our opinion on possible applications of the preliminary results.

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Section: Explicit Approach: Conscious Production Of Single Notesmentioning

confidence: 99%

mentioning

confidence: 99%

BCI Promises in Emotional Involvement in Music and Games

Folgieri

Zampolini

2014

Comput. Entertain.

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“…For a more accurate study on this subject, the outlier segments (the segments with Signal to Noise Ratios (SNR) less than 1) are determined and excluded from the data set. The SNR of the signal is defined as follows [ (2) where the sum of the powers of the fundamental frequency and its second harmonic is divided by the average power. The average power is calculated by summing the power of the signal in a window of width of three times of the frequency resolution of the signal around both the fundamental frequency and its second harmonic.…”

Section: Data Acquisition and Analysismentioning

confidence: 99%

“…Using the EEG signal as a communication channel was first proposed by Hans Berger in 1929 [1]. The first Brain Computer Interfacing (BCI) system was however designed in Dr. Vidal's laboratory in 1973 [2]. Various BCI systems were then developed and used with different levels of success.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Effect of the Inter-Sources Distance on the Performance of the SSVEP-Based BCI Systems

Resalat¹,

Setarehdan

2012

AJBE

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Brain Computer Interfacing (BCI) systems, which are a new communicating channel between humans and the computers are growing rapidly. One such a method is based on the Steady State Visual Evoked Potentials (SSVEP), which can be recorded during visual stimulating of the subject by a twinkling light source with a fixed frequency. An important parameter to be considered is the effect of the inter-sources distance on the accuracy of such BCI systems. In particular inter-sources (LEDs) distances of 4, 14, 24, 44 and 64 cm when the sources plane is located 60 cm away from the subject's eyes (producing inter-sources visual angles of 3.8°, 13.4°, 22.6°, 40.2° and 56° respectively) were examined. In addition, four different sweep lengths of 0.5, 1, 2 and 3 seconds are considered. In addition, due to the usage of the AR models for feature extraction from the SSVEP signals, selection of the best AR model together with the best classifier among the LDA, the SVM and the Naïve Bayes are studied. It is showed that the BCI system with D=44 cm, AR order of 13 and either the LDA or the SVM classifiers could produce the best results compared to the other cases.

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“…Composing melody also become a reality for severely disabled people by using brain computer technology, where users can compose their melodies by picking the tune notes from the screen using BCI [27]. Brain computer interface has been used for entertainment games under Android platform in a racing game [17] where it was developed for Android and controlled using BCI.…”

Section: Entertainmentmentioning

confidence: 99%