Literature DB >> 27565156

Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors.

Gabriela Constantinescu1,2, William Hodgetts1,2, Dylan Scott1, Kristina Kuffel1, Ben King1,3, Chris Brodt3, Jana Rieger4,5.   

Abstract

Surface electromyography (sEMG) is used as an adjuvant to dysphagia therapy to demonstrate the activity of submental muscles during swallowing exercises. Mechanomyography (MMG) has been suggested as a potential superior alternative to sEMG; however, this advantage is not confirmed for signal acquired from submental muscles. This study compared the signal-to-noise ratio (SNR) obtained from sEMG and MMG sensors during swallowing tasks, in healthy participants and those with a history of head and neck cancer (HNC), a population with altered anatomy and a high incidence of dysphagia. Twenty-two healthy adults and 10 adults with a history of HNC participated in this study. sEMG and MMG signals were acquired during dry, thin liquid, effortful, and Mendelsohn maneuver swallows. SNR was compared between the two sensors using repeated measures ANOVAs and subsequent planned pairwise comparisons. Test-retest measures were collected on 20 % of participants. In healthy participants, MMG SNR was higher than that of sEMG for dry [t(21) = -3.02, p = 0.007] and thin liquid swallows [t(21) = -4.24, p < 0.001]. Although a significant difference for sensor was found in HNC participants F(1,9) = 5.54, p = 0.043, planned pairwise comparisons by task revealed no statistically significant difference between the two sensors. sEMG also showed much better test-retest reliability than MMG. Biofeedback provided as an adjuvant to dysphagia therapy in patients with HNC should employ sEMG technology, as this sensor type yielded better SNR and overall test-retest reliability. Poor MMG test-retest reliability was noted in both healthy and HNC participants and may have been related to differences in sensor application.

Entities:  

Keywords:  Deglutition; Deglutition disorders; Electromyography; Head and neck cancer; Mechanomyography; Visual biofeedback

Mesh:

Year:  2016        PMID: 27565156     DOI: 10.1007/s00455-016-9742-6

Source DB:  PubMed          Journal:  Dysphagia        ISSN: 0179-051X            Impact factor:   3.438


  38 in total

Review 1.  Surface electromyography for speech and swallowing systems: measurement, analysis, and interpretation.

Authors:  Cara E Stepp
Journal:  J Speech Lang Hear Res       Date:  2012-01-09       Impact factor: 2.297

2.  The effects of motion artifact on mechanomyography: A comparative study of microphones and accelerometers.

Authors:  A O Posatskiy; T Chau
Journal:  J Electromyogr Kinesiol       Date:  2011-10-22       Impact factor: 2.368

3.  The normal swallow: muscular and neurophysiological control.

Authors:  Stephanie M Shaw; Rosemary Martino
Journal:  Otolaryngol Clin North Am       Date:  2013-10-23       Impact factor: 3.346

4.  Comparison of effortful and noneffortful swallows in healthy middle-aged and older adults.

Authors:  J A Hind; M A Nicosia; E B Roecker; M L Carnes; J Robbins
Journal:  Arch Phys Med Rehabil       Date:  2001-12       Impact factor: 3.966

5.  Effects of age and stimulus on submental mechanomyography signals during swallowing.

Authors:  Joon Lee; Tom Chau; Catriona M Steele
Journal:  Dysphagia       Date:  2009-01-14       Impact factor: 3.438

Review 6.  Evidence-based systematic review: Oropharyngeal dysphagia behavioral treatments. Part IV--impact of dysphagia treatment on individuals' postcancer treatments.

Authors:  Daniel McCabe; John Ashford; Karen Wheeler-Hegland; Tobi Frymark; Robert Mullen; Nan Musson; Carol Smith Hammond; Tracy Schooling
Journal:  J Rehabil Res Dev       Date:  2009

7.  The effect of skinfold on frequency of human muscle mechanomyogram.

Authors:  Anna Jaskólska; Wioletta Brzenczek; Katarzyna Kisiel-Sajewicz; Adam Kawczyński; Jarosław Marusiak; Artur Jaskólski
Journal:  J Electromyogr Kinesiol       Date:  2004-04       Impact factor: 2.368

8.  Surface electromyography of abdominal and back muscles in patients with active scars.

Authors:  Petra Valouchová; Karel Lewit
Journal:  J Bodyw Mov Ther       Date:  2008-06-09

Review 9.  A review of non-invasive techniques to detect and predict localised muscle fatigue.

Authors:  Mohamed R Al-Mulla; Francisco Sepulveda; Martin Colley
Journal:  Sensors (Basel)       Date:  2011-03-24       Impact factor: 3.576

10.  Techniques of EMG signal analysis: detection, processing, classification and applications.

Authors:  M B I Raez; M S Hussain; F Mohd-Yasin
Journal:  Biol Proced Online       Date:  2006-03-23       Impact factor: 3.244

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  2 in total

1.  Evaluation of an Automated Swallow-Detection Algorithm Using Visual Biofeedback in Healthy Adults and Head and Neck Cancer Survivors.

Authors:  Gabriela Constantinescu; Kristina Kuffel; Daniel Aalto; William Hodgetts; Jana Rieger
Journal:  Dysphagia       Date:  2017-11-02       Impact factor: 3.438

2.  Effectiveness of Therapy on Post-Extubation Dysphagia: Clinical and Electromyographic Findings.

Authors:  Aretuza Zaupa Gasparim El Gharib; Giédre Berretin-Felix; Diogo Francisco Rossoni; Sergio Seiji Yamada
Journal:  Clin Med Insights Ear Nose Throat       Date:  2019-09-12
  2 in total

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