Skip to main content
Log in

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

  • Original Article
  • Published:
Dysphagia Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Langerman A, MacCracken E, Kasza K, Haraf DJ, Vokes EE, Stenson KM. Aspiration in CRT patients with HNC. Arch Otolaryngol Head Neck Surg. 2007;133:1289–95.

    Article  PubMed  Google Scholar 

  2. Hutcheson KA, Lewin JS, Barringer DA, Lisec A, Gunn GB, Moore MW, Holsinger FC. Late dysphagia after radiotherapy-based treatment of head and neck cancer. Cancer. 2012;118:5793–9.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Shaw SM, Martino R. The normal swallow: muscular and neurophysiological control. Otolaryngol Clin North Am. 2013;46:937–56.

    Article  PubMed  Google Scholar 

  4. Hind JA, Nicosia MA, Roecker EB, Carnes ML, Robbins J. Comparison of effortful and noneffortful swallows in healthy middle-aged and older adults. Arch Phys Med Rehabil. 2001;82:1661–5.

    Article  CAS  PubMed  Google Scholar 

  5. Lazarus C, Logemann JA, Song CW, Rademaker AW, Kahrilas PJ. Effects of voluntary maneuvers on tongue base function for swallowing. Folia Phoniatr Logop. 2002;54:171–6.

    Article  PubMed  Google Scholar 

  6. Bryant M. Biofeedback in the treatment of a selected dysphagic patient. Dysphagia. 1991;6:140–4.

    Article  CAS  PubMed  Google Scholar 

  7. Crary MA, Carnaby Mann GD, Groher ME, Helseth E. Functional benefits of dysphagia therapy using adjunctive sEMG biofeedback. Dysphagia. 2004;19:160–4.

    PubMed  Google Scholar 

  8. Wheeler-Hegland K, Rosenbek JC, Sapienza CM. Submental sEMG and hyoid movement during Mendelsohn maneuver, effortful swallow, and expiratory muscle strength training. J Speech Lang Hear Res. 2008;51:1072–87.

    Article  PubMed  Google Scholar 

  9. Azola AM, Greene LR, Taylor-Kamara I, Macrae P, Anderson C, Humbert IA. The relationship between submental surface electromyography and hyo-laryngeal kinematic measures of Mendelsohn maneuver duration. J Speech Lang Hear Res. 2015;58:1627–36.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Reaz MB, Hussain MS, Mohd-Yasin F. Techniques of EMG signal analysis: detection, processing, classification and applications. Biol Proced Online. 2006;8:11–35.

    Article  Google Scholar 

  11. Stepp CE. Tutorial: surface electromyography for speech and swallowing systems: measurement, analysis, and interpretation. J Speech Lang Hear Res. 2012;55:1232–46.

    Article  PubMed  Google Scholar 

  12. Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol. 2000;10:361–74.

    Article  CAS  PubMed  Google Scholar 

  13. Vigreux B, Cnockaert JC, Pertuzon E. Factors influencing quantified surface EMGs. Eur J Appl Physiol. 1979;41:119–29.

    Article  CAS  Google Scholar 

  14. Brown CC. Reliability of electromyography detection systems for the pelvic floor muscles. School of Rehabilitation Therapy. Kingston: Queen’s University; 2007.

  15. Islam MA, Sundaraj K, Ahmad RB, Sundaraj S, Ahamed NU, Ali MA. Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force. PLoS one. 2014;9:e96628.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Posatskiy AO.Design and evaluation of pressure-based sensors for mechanomyography: an investigation of chamber geometry and motion artefact.: Mechanical and Industrial Engineering, in collaboration with the Institute of Biomaterials and Biomedical Engineering: University of Toronto, 2011.

  17. Silva S, Chau T. A Mathematical model for source separation of MMG signals recorded with a coupled microphone-accelerometer sensor pair. IEEE Trans Biomed Eng. 2005;52:1493–501.

    Article  PubMed  Google Scholar 

  18. Posatskiy AO, Chau T. Design and evaluation of a novel microphone-based mechanomyography sensor with cylindrical and conical acoustic chambers. Med Eng Phys. 2012;34:1184–90.

    Article  CAS  PubMed  Google Scholar 

  19. Mohamed Irfan MR, Sudharsan N, Santhanakrishnan S, Geethanjali B. A comparative study of EMG and MMG signals for practical applications. International conference on signal, image processing and applications with workshop of ICEEA 2011.

  20. Lee J, Chau T, Steele CM. Effects of age and stimulus on submental mechanomyography signals during swallowing. Dysphagia. 2009;24:265–73.

    Article  PubMed  Google Scholar 

  21. Roy SH, De Luca G, Cheng MS, Johansson A, Gilmore LD, De Luca CJ. Electro-mechanical stability of surface EMG sensors. Med Bio Eng Comput. 2007;45:447–57.

    Article  CAS  Google Scholar 

  22. Lee J, Steele CM, Chau T. Swallow segmentation with artificial neural networks and multi-sensor fusion. Med Eng Phys. 2009;31:1049–55.

    Article  PubMed  Google Scholar 

  23. Silva J, Chau T. Coupled microphone-accelerometer sensor pair for dynamic noise reduction in MMG signal recording. Electron Lett. 2003;39:1496.

    Article  CAS  Google Scholar 

  24. Posatskiy AO, Chau T. The effects of motion artifact on mechanomyography: a comparative study of microphones and accelerometers. J Electromyogr Kinesiol. 2012;22:320–4.

    Article  CAS  PubMed  Google Scholar 

  25. Seikaly H, Jha N, McGaw T, Coulter L, Liu R, Oldring D. Submandibular gland transfer: a new method of preventing radiation-induced xerostomia. Laryngoscope. 2001;111:347–52.

    Article  CAS  PubMed  Google Scholar 

  26. Beck TW, Housh TJ, Cramer JT, Weir JP, Johnson GO, Coburn JW, Malek MH, Mielke M. Mechanomyographic amplitude and frequency responses during dynamic muscle actions: a comprehensive review. Biomed Eng Online. 2005;4:67.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Jaskolska A, Brzenczek W, Kisiel-Sajewicz K, Kawczynski A, Marusiak J, Jaskolski A. The effect of skinfold on frequency of human muscle mechanomyogram. J Electromyogr Kinesiol. 2004;14:217–25.

    Article  PubMed  Google Scholar 

  28. Valouchova P, Lewit K. Surface electromyography of abdominal and back muscles in patients with active scars. J Bodyw Mov Ther. 2009;13:262–7.

    Article  PubMed  Google Scholar 

  29. Crary MA, Baldwin BO. Surface electromyographic characteristics of swallowing in dysphagia secondary to brainstem stroke. Dysphagia. 1997;12:180–7.

    Article  CAS  PubMed  Google Scholar 

  30. De-Ary-Pires B, Ary-Pires R, Pires-Neto MA. The human digastric muscle: patterns and variations with clinical and surgical correlations. Ann Anat. 2003;185:471–9.

    Article  CAS  PubMed  Google Scholar 

  31. Basmajian JV, De Luca CJ. Muscles alive: their functions revealed by electromyography. 2nd ed. Baltimore: Williams & Wilkins; 1985.

    Google Scholar 

  32. Petitjean M, Maton B, Cnockaert J-C. Evaluation of human dynamic contraction by phonomyography. Am Physiol Soc. 1992;73:2567–73.

    CAS  Google Scholar 

  33. Ibitoye MO, Hamzaid NA, Zuniga JM, Hasnan N, Wahab AK. Mechanomyographic parameter extraction methods: an appraisal for clinical applications. Sensors. 2014;14:22940–70.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Al-Mulla MR, Sepulveda F, Colley M. A review of non-invasive techniques to detect and predict localised muscle fatigue. Sensors. 2011;11:3545–94.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Nonaka H, Mita K, Akataki K, Watakabe M, Itoh Y. Sex differences in mechanomyographic responses to voluntary isometric contractions. Med Sci Sports Exerc. 2006;38:1311–6.

    Article  PubMed  Google Scholar 

  36. Lazarus C. Dysphagia Secondary to the Effects of Chemotherapy and Radiotherapy. In: Shaker R, Belafsky PC, Postma GN, Easterling C, editors. Principles of deglutition: a multidisciplinary text for swallowing and its disorders. New York: Springer; 2013. p. 431–43.

    Chapter  Google Scholar 

  37. McCabe D, Ashford J, Wheeler-Hegland K, Frymark T, Mullen R, Musson N, Hammond CS, Schooling T. Evidence-based systematic review: oropharyngeal dysphagia behavioral treatments. Part IV—Impact of dysphagia treatment on individuals’ postcancer treatments. J Rehabil Res Dev. 2009;46:205.

    Article  PubMed  Google Scholar 

  38. Russell JA, Connor NP. Effects of age and radiation treatment on function of extrinsic tongue muscles. Radiother Oncol. 2014;9:1–15.

    Article  Google Scholar 

  39. Zaheer F, Roy SH, De Luca CJ. Preferred sensor sites for surface EMG signal decomposition. Physiol Meas. 2012;33:195–206.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Holobar A, Zazula D. Correlation-based decomposition of surface electromyopgrams at low contraction forces. Med Biol Eng Comput. 2004;42:487–95.

    Article  CAS  PubMed  Google Scholar 

  41. Evetovich TK, Housh TJ, Stout JR, Johnson GO, Smith DR, Ebersole KT. Mechanomyographic responses to concentric isokinetic muscle contractions. Eur J Appl Physiol. 1997;75:166–9.

    Article  CAS  Google Scholar 

  42. Cramer JT, Housh TJ, Johnson GO, Ebersole KT, Perry SR, Bull AJ. Mechanomyographic and electromyographic responses of the superficial muscles of the quadriceps femoris during maximal, concentric isokinetic muscle actions. Isokinet Exerc Sci. 2000;8:109–17.

    Google Scholar 

  43. Smith DB, Housh TJ, Stout JR, Johnson GO, Evetovich TK, Ebersole KT. Mechanomyographic responses to maximal eccentric isokinetic muscle actions. Am Physiol Soc. 1997;82:1003–7.

    CAS  Google Scholar 

  44. Herda TJ, Ryan ED, Beck TW, Costa PB, DeFreitas JM, Stout JR, Cramer JT. Reliability of mechanomyographic amplitude and mean power frequency during isometric step and ramp muscle actions. J Neurosci Method. 2008;171:104–9.

    Article  Google Scholar 

  45. Woodward R, Shefelbine S, Vaidyanathan R. Pervasive motion tracking and muscle activity monitor. Computer-based medical systems (CBMS), 2014 IEEE 27th international symposium on, 2014, pp 421–426.

  46. Vaiman M, Eviatar E, Segal S. Evaluation of normal deglutition with the help of rectified surface electromyography records. Dysphagia. 2004;19:125–32.

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported by Alberta Cancer Foundation Transformative Program Grant (26355); Alberta Innovate – Health Solutions (AIHS) Clinician Fellowship (#201400350); Natural Sciences and Engineering Research Council (NSERC) and industrial and government partners, through the Healthcare Support through Information Technology Enhancements (hSITE) Strategic Research Network (22143).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jana Rieger.

Ethics declarations

Conflict of Interest

The authors Gabriela Constantinescu, Dylan Scott, Ben King, and Jana Rieger are inventors listed on a patent for the mobile swallowing therapy device. The patent application was made through TEC Edmonton Office, University of Alberta (file number: 2014015. No commercial interest has been shown at this stage).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Constantinescu, G., Hodgetts, W., Scott, D. et al. Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors. Dysphagia 32, 90–103 (2017). https://doi.org/10.1007/s00455-016-9742-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00455-016-9742-6

Keywords

Navigation