Abstract
Parkinson’s disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1–1 %, and an annual incidence between 1.3–2.0/10,000 inhabitants. The most obvious symptoms are movement-related such as tremor, rigidity, slowness of movement and walking difficulties and frequently these are the symptoms that lead to the PD diagnoses but also they could have In this sense voice analysis is a safe, non-invasive, and reliable screening procedure for PD patients with dysphagia, which could detect patients at high risk of clinically significant aspiration. In this paper we will present a part of an ongoing project that will evaluate automatic speech analysis based on linear and non-linear features. These can be reliable predictors/indicators of swallowing and balance impairments in PD. An important advantage of voice analysis is its low intrusiveness and easy implementation in clinical practice. Thus, if a significant correlation between these simple analyses and the gold standard video-fluoroscopic analysis will imply simpler and less stressing diagnostic test for the patients as well as the use of cheaper analysis systems.
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Acknowledgments
This work has been supported by FEDER and Ministerio de ciencia e Innovación, TEC2012-38630-C04-03 and the University of the Basque Country by EHU-14/58. The described research was performed in laboratories supported by the SIX project; the registration number CZ.1.05/2.1.00/03.0072, the operational program Research and Development for Innovation.
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López-de-Ipiña, K. et al. (2016). Advances in a Multimodal Approach for Dysphagia Analysis Based on Automatic Voice Analysis. In: Bassis, S., Esposito, A., Morabito, F., Pasero, E. (eds) Advances in Neural Networks. WIRN 2015. Smart Innovation, Systems and Technologies, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-319-33747-0_20
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DOI: https://doi.org/10.1007/978-3-319-33747-0_20
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