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Detection of swallows with silent aspiration using swallowing and breath sound analysis

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Abstract

In this study, the feasibility of acoustical analysis for detection of swallowing silent aspiration is investigated. As a pilot study, we analyzed the breath sounds of 21 dysphagic individuals, 11 of which demonstrated aspiration during the fiberoptic endoscopic evaluation of swallowing (FEES) or videofluoroscopic swallowing study (VFSS). We found that the low frequency components of the power spectrum of the breath sounds after a swallow show higher magnitude when there is aspiration. Thus, we divided the frequency range below 300 Hz into three sub-bands and calculated the average power of the breath sound signal in each sub-band as the characteristic features for the stage 1 classification into two groups of aspirated and non-aspirated patients. Then, for the aspirated group, the unsupervised fuzzy k-means clustering algorithm was deployed to label the breath sounds immediately after a swallow as aspiration or non-aspiration. The results were compared with the FEES/VFSS assessments provided by the speech language pathologists. The results are encouraging: more than 86 % accuracy in detection of silent aspiration. While the proposed method should be verified on a larger dataset, the results are promising for the use of acoustical analysis as a clinical tool to detect silent aspiration.

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Acknowledgments

This study was supported financially in part by the Natural Sciences and Engineering Research Council (NSERC) of Canada and Riverview Health Centre (Winnipeg). The authors would like to acknowledge A. Meakin and all the speech language pathologists in DeerLodge Health Center and Riverview Health Centre for their help in recruiting patients and collecting data.

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Authors and Affiliations

  1. Canada Research Chair in Biomedical Engineering, Department of Electrical and Computer Engineering, University of Manitoba, Room E3-513 Eng. Bldg., 75A Chancellor’s Circle, Winnipeg, MB, R3T 5V6, Canada

    Zahra Moussavi

  2. Riverview Health Center, Room 458, Admin bldg, 1 Morley Ave, Winnipeg, MB, R3L 2P4, Canada

    Zahra Moussavi

  3. Department of Electrical and Computer Engineering, University of Manitoba, Room E3-518 Eng. Bldg., 75A Chancellor’s Circle, Winnipeg, MB, R3T 5V6, Canada

    Samaneh Sarraf Shirazi

  4. Department of Speech Language Therapy, Riverview Health Center, 1 Morley Ave, Winnipeg, MB, R3L 2P4, Canada

    Caitlin Buchel, Reesa Daun & Laura Lenton

Authors
  1. Samaneh Sarraf Shirazi
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  2. Caitlin Buchel
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  3. Reesa Daun
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  4. Laura Lenton
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  5. Zahra Moussavi
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Correspondence to Zahra Moussavi.

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Sarraf Shirazi, S., Buchel, C., Daun, R. et al. Detection of swallows with silent aspiration using swallowing and breath sound analysis. Med Biol Eng Comput 50, 1261–1268 (2012). https://doi.org/10.1007/s11517-012-0958-9

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  • DOI: https://doi.org/10.1007/s11517-012-0958-9

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