Abstract
In this paper, an alternative representation of EEG is investigated, in particular, translation of EEG into sound; patterns in the EEG then correspond to sequences of notes. The aim is to provide an alternative tool for analysing and exploring brain signals, e.g., for diagnosis of neurological diseases. Specifically, a system is proposed that transforms EEG signals, recorded by a wireless headset, into sounds in real-time. In order to assess the resulting representation of EEG as sounds, the proposed sonification system is applied to EEG signals of Alzheimer’s (AD) patients and healthy age-matched control subjects (recorded by a high-quality wired EEG system). Fifteen volunteers were asked to classify the sounds generated from the EEG of 5 AD patients and five healthy subjects; the volunteers labeled most sounds correctly, in particular, an overall sensitivity and specificity of 93.3% and 97.3% respectively was obtained, suggesting that the sound sequences generated by the sonification system contain relevant information about EEG signals and underlying brain activity.
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Acknowledgments
Mohamed Elgendi and Justin Dauwels would like to thank the Institute for Media Innovation (IMI) at Nanyang Technological University (NTU) for partially supporting this project (Grant M58B40020).
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Elgendi, M., Rebsamen, B., Cichocki, A., Vialatte, F., Dauwels, J. (2013). Real-Time Wireless Sonification of Brain Signals. In: Yamaguchi, Y. (eds) Advances in Cognitive Neurodynamics (III). Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4792-0_24
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DOI: https://doi.org/10.1007/978-94-007-4792-0_24
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