Abstract
Alterations of the swallowing process at neurological and muscular levels can cause dysphagia. Its instrumental diagnosis is carried out by videofluoroscopy, which is invasive, expensive, and sometimes unavailable. Inexpensive and non-invasive alternatives have been proposed in several studies considering different biosignals including surface electromyography and accelerometry. Automatic approaches have been focused on unimodal analysis, disregarding the high complexity of the process. In this way, we performed a multimodal analysis of the swallowing process in 30 healthy individuals and 30 dysphagic patients, using surface electromyography and accelerometry-based cervical auscultation. Features in time, frequency, and time-frequency domains were extracted and selected for classification purposes. A support vector machine was used as a classifier, and hyperparameters were optimized by a grid search. The proposed scheme achieved an accuracy of 0.92 ± 0.07 in the best case. The performed method achieved promising results in terms of classification of dysphagic and healthy individuals, which could contribute to the development of non-invasive techniques of dysphagia screening.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Clavé, P., Shaker, R.: Dysphagia: current reality and scope of the problem. Nat. Rev. Gastroenterol. Hepatol. 12, 259 (2015)
Streppel, M., Veder, L.L., Pullens, B., Joosten, K.F.: Swallowing problems in children with a tracheostomy tube. Int. J. Pediatr. Otorhinolaryngol. 124, 30–33 (2019)
Chen, D.F.: Dysphagia in the hospitalized patient. Hosp. Med. Clin. 6, 38–52 (2017)
Suárez Escudero, J.C., Rueda Vallejo, Z.V., Orozco, A.F.: Disfagia y neurología: una unión indefectible? Acta Neurol. Colomb. 34, 92–100 (2018)
Cichero, J.A.Y., Altman, K.W.: Definition, prevalence and burden of oropharyngeal dysphagia: a serious problem among older adults worldwide and the impact on prognosis and hospital resources. Nestle Nutr. Inst. Workshop Ser. 72, 1–11 (2012)
Shapira-Galitz, Y., Drendel, M., Yousovich-Ulriech, R., Shtreiffler-Moskovich, L., Wolf, M., Lahav, Y.: Translation and validation of the dysphagia handicap index in Hebrew-speaking patients. Dysphagia 34(1), 63–72 (2018). https://doi.org/10.1007/s00455-018-9914-7
Hsu, C.C., Chen, W.H., Chiu, H.C.: Using swallow sound and surface electromyography to determine the severity of dysphagia in patients with myasthenia gravis. Biomed. Signal Process. Control 8, 237–243 (2013)
Miller, C.K., Maybee, J., Prager, J., Pentiuk, S.: Feeding and swallowing disorders. In: Kendig’s Disorders of the Respiratory Tract in Children, 9th edn., pp. 1106–1113.e1. Elsevier Inc. (2018)
Armán, J.A., Lorente-Ramos, R.M., García, P.G., Lorduy, T.C.: Videofluoroscopic evaluation of normal and impaired oropharyngeal swallowing. Radiographics 39, 78–79 (2019)
Wilson, R.D., Howe, E.C.: A of cost-effectiveness analysis screening methods for dysphagia after stroke. PM and R 4, 273–282 (2012)
Cámpora, H., Falduti, A.: Evaluación y tratamiento de las alteraciones de la deglución. Rev. Am. Med. Respiratoria, 98–107 (2012)
Mohammadi, H., Samadani, A.A., Steele, C., Chau, T.: Automatic discrimination between cough and non-cough accelerometry signal artefacts. Biomed. Signal Process. Control 52, 394–402 (2019)
Mao, S., Zhang, Z., Khalifa, Y., Donohue, C., Coyle, J.L., Sejdic, E.: Neck sensor-supported hyoid bone movement tracking during swallowing. Roy Soc. Open Sci. 6 (2019)
Vaiman, M.: Standardization of surface electromyography utilized to evaluate patients with dysphagia. Head Face Med. 3, 1–7 (2007)
Ertekin, C., Aydogdu, I.: Neurophysiology of swallowing. Clin. Neurophysiol. 114, 2226–2244 (2003)
Roldan-Vasco, S., Restrepo-Agudelo, S., Valencia-Martinez, Y., Orozco-Duque, A.: Automatic detection of oral and pharyngeal phases in swallowing using classification algorithms and multichannel EMG. J. Electromyogr. Kinesiol. 43, 193–200 (2018)
Sebastian, R.V., Estefania, P.G., Andres, O.D.: Scalogram-energy based segmentation of surface electromyography signals from swallowing related muscles (2020)
Lee, J., Steele, C.M., Chau, T.: Swallow segmentation with artificial neural networks and multi-sensor fusion. Med. Eng. Phys. 31, 1049–1055 (2009)
Afkari, S., et al.: Measuring frequency of spontaneous swallowing. Australas. Phys. Eng. Sci. Med. 30, 313–317 (2007)
Crary, M.A., Sura, L., Carnaby, G.: Validation and demonstration of an isolated acoustic recording technique to estimate spontaneous swallow frequency. Dysphagia 28, 86–94 (2013)
Sejdić, E., Steele, C.M., Chau, T.: A method for removal of low frequency components associated with head movements from dual-axis swallowing accelerometry signals. PLoS ONE 7, 1–8 (2012)
Dudik, J.M., Kurosu, A., Coyle, J.L., Sejdić, E.: A comparative analysis of DBSCAN, K-means, and quadratic variation algorithms for automatic identification of swallows from swallowing accelerometry signals. Comput. Biol. Med. 59, 10–18 (2015)
Roldan-Vasco, S., Perez-Giraldo, E., Orozco-Duque, A.: Continuous wavelet transform for muscle activity detection in surface EMG signals during swallowing. In: Figueroa-García, J.C., Villegas, J.G., Orozco-Arroyave, J.R., Maya Duque, P.A. (eds.) WEA 2018. CCIS, vol. 916, pp. 245–255. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00353-1_22
Sejdic, E., Steele, C.M., Chau, T.: Classification of penetration-aspiration versus healthy swallows using dual-axis swallowing accelerometry signals in dysphagic subjects. IEEE Trans. Biomed. Eng. 60, 1859–1866 (2013)
Lazareck, L.J., Moussavi, Z.M.: Classification of normal and dysphagic swallows by acoustical means. IEEE Trans. Biomed. Eng. 51, 2103–2112 (2004)
Hackett, J.K., Shah, M.: Multi-sensor fusion: a perspective, pp. 1324–1330 (1990)
Lee, J., Steele, C.M., Chau, T.: Classification of healthy and abnormal swallows based on accelerometry and nasal airflow signals. Artif. Intell. Med. 52, 17–25 (2011)
Acknowledgements
This work has been supported by COLCIENCIAS - República de Colombia, research project No. 121077758144.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Restrepo-Uribe, J.P., Roldan-Vasco, S., Perez-Giraldo, E., Orozco-Arroyave, J.R., Orozco-Duque, A. (2020). Electrophysiological and Mechanical Approaches to the Swallowing Analysis. In: Figueroa-García, J.C., Garay-Rairán, F.S., Hernández-Pérez, G.J., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2020. Communications in Computer and Information Science, vol 1274. Springer, Cham. https://doi.org/10.1007/978-3-030-61834-6_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-61834-6_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-61833-9
Online ISBN: 978-3-030-61834-6
eBook Packages: Computer ScienceComputer Science (R0)