Abstract
It is a well-known fact that Parkinson’s Disease (PD) patients present important alterations in speech and phonation. Recent studies have shown that neuroestimulation using binaural beats have an effect on the neuromotor and cognitive conditions of patients suffering from PD, at least temporarily after stimulation. The present study aims to test if this phenomenon has any observable effect on phonation as a manifestation of the patient’s neuromotor conditions. With this aim in mind, an experimental framework has been set up, consisting in the stimulation of PD patients with two types of signals, the first consists in a supposedly active signal (binaural beats and pink noise) and the second an inert signal (consisting only of pink noise), recording specific sustained vowels and reading text before and after each stimulation process. The sustained vowels were analyzed in further depth to estimate phonation features associated with instability (jitter, shimmer, biomechanical unbalances, and tremor in different bands). A specific study case is presented, for which the analysis shows statistically significant changes in phonation before and after active neurostimulation, whereas these changes were not detected when inert neurostimulation was used. This effect could open the possibility for the development of neuroacoustic rehabilitative therapies, based on low-cost portable acoustical stimulation devices.
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Acknowledgments
This work is being funded by TEC2016-77791-C4-4-R (MINECO, Spain) and CENIE_TECA-PARK_55_02 INTERREG V-A Spain-Portugal (POCTEP). The authors would like to thank “Asociación de Parkinson de Madrid”, and Dr. J. C. Martínez-Castrillo from Hospital Universitario Ramón y Cajal of Madrid for their help and advice, and especially to the Foundation for the Promotion of Industrial Innovation (F2I2) as the funding body in part of this research.
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Gálvez-García, G., Gómez-Rodellar, A., Palacios-Alonso, D., de Arcas-Castro, G., Gómez-Vilda, P. (2019). Neuroacoustical Stimulation of Parkinson’s Disease Patients: A Case Study. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science(), vol 11487. Springer, Cham. https://doi.org/10.1007/978-3-030-19651-6_32
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