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Automated Acoustic Analysis in Detection of Spontaneous Swallows in Parkinson’s Disease

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Abstract

Acoustic monitoring of swallow frequency has become important as the frequency of spontaneous swallowing can be an index for dysphagia and related complications. In addition, it can be employed as an objective quantification of ingestive behavior. Commonly, swallowing complications are manually detected using videofluoroscopy recordings, which require expensive equipment and exposure to radiation. In this study, a noninvasive automated technique is proposed that uses breath and swallowing recordings obtained via a microphone located over the laryngopharynx. Nonlinear diffusion filters were used in which a scale-space decomposition of recorded sound at different levels extract swallows from breath sounds and artifacts. This technique was compared to manual detection of swallows using acoustic signals on a sample of 34 subjects with Parkinson’s disease. A speech language pathologist identified five subjects who showed aspiration during the videofluoroscopic swallowing study. The proposed automated method identified swallows with a sensitivity of 86.67 %, a specificity of 77.50 %, and an accuracy of 82.35 %. These results indicate the validity of automated acoustic recognition of swallowing as a fast and efficient approach to objectively estimate spontaneous swallow frequency.

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Conflict of interest

The authors have no conflicts of interest to disclose.

Author information

Authors and Affiliations

  1. Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Hezarjarib Street, 81745-319, Isfahan, Iran

    Marzieh Golabbakhsh

  2. Isfahan Neurology Research Center, Isfahan University of Medical Sciences, Hezarjarib Street, 81745-319, Isfahan, Iran

    Ali Rajaei

  3. Department of Electrical and Computer Engineering, Isfahan University of Technology, 84156-83111, Isfahan, Iran

    Mahmoud Derakhshan & Saeed Sadri

  4. Isfahan Health Management of Social Security Organization, Salman Farsi Street, Ghadir Building, Isfahan, Iran

    Masoud Taheri

  5. Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Hezarjarib Street, 81745-319, Isfahan, Iran

    Peyman Adibi

Authors
  1. Marzieh Golabbakhsh
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  2. Ali Rajaei
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  3. Mahmoud Derakhshan
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  4. Saeed Sadri
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  5. Masoud Taheri
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  6. Peyman Adibi
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Correspondence to Marzieh Golabbakhsh.

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Golabbakhsh, M., Rajaei, A., Derakhshan, M. et al. Automated Acoustic Analysis in Detection of Spontaneous Swallows in Parkinson’s Disease. Dysphagia 29, 572–577 (2014). https://doi.org/10.1007/s00455-014-9547-4

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  • DOI: https://doi.org/10.1007/s00455-014-9547-4

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