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Automatic Detection and Analysis of Swallowing Sounds in Healthy Subjects and in Patients with Pharyngolaryngeal Cancer

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Abstract

Assessment of swallowing function is often invasive or involves irradiation. Analysis of swallowing sounds is a noninvasive method for assessment of swallowing but is not used in daily medical practice. Dysphagia could be the first symptom that occurs in head and neck cancer. This study evaluated a method for the automatic detection and analysis of swallowing sounds in healthy subjects and in patients with pharyngolaryngeal cancer. A smartphone application, developed for automatic detection and analysis of swallowing sounds was developed and tested in 12 healthy volunteers and in 26 patients with pharyngolaryngeal cancer. Swallowing sounds were recorded with a laryngophone during a standardized meal (100 mL mashed potatoes, 100 mL water, and 100 mL yogurt). Swallowing number and duration were noted; the results were compared to a standard swallowing sound analysis using the software AUDACITY®. There were no statistically significant differences in swallowing number or duration between the two analysis methods for the three types of foods in healthy volunteers and only for water in patients. In healthy volunteers, the results of our automatic analysis were comparable with those obtained with the standard analysis. However, a better discrimination of swallowing sounds is necessary for the algorithm to obtain reliable results with thicker food in patients with head and neck cancer.

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Abbreviations

HNC:

Head and neck cancer

ms:

Millisecond

mL:

Millilitre

SSD:

Swallowing sound duration

SN:

Swallowing number

FN:

False negative

FP:

False positive

Se:

Sensitivity

PPV:

Positive predictive value

TNM:

Tumoral classification according to tumor (T), nodular (N) or metastasis (M) criteria from the 8th edition of the American Joint Commission of Cancer

DT:

Detection threshold parameter

SR:

Sound richness parameter

EA:

End of analysis parameter

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Acknowledgements

We would like to thank the “Société française de carcinologie cervico-faciale” for its financial support. We would also like to thank “textcheck” for reviewing this article. For a certificate, please see: http://www.textcheck.com/certificate/ltDLWD.

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Correspondence to P. Rayneau.

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Rayneau, P., Bouteloup, R., Rouf, C. et al. Automatic Detection and Analysis of Swallowing Sounds in Healthy Subjects and in Patients with Pharyngolaryngeal Cancer. Dysphagia 36, 984–992 (2021). https://doi.org/10.1007/s00455-020-10225-9

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  • DOI: https://doi.org/10.1007/s00455-020-10225-9

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