Prediction of Larynx Function Using Multichannel Surface EMG Classification

Johnny McNulty*, Kylie De Jager, Henry T. Lancashire, James Graveston, Martin Birchall, Anne Vanhoestenberghe

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4% (swallows), 93.8 ± 2.8% (coughs) and 70.5 ± 5.4% (speech) for controls, and 67.7 ± 4.4% (swallows), 71.0 ± 9.1% (coughs) and 78.0 ± 3.8% (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9% of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1% in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device.

Original languageEnglish
Pages (from-to)1032-1039
Number of pages8
JournalIEEE Transactions on Medical Robotics and Bionics
Volume3
Issue number4
DOIs
Publication statusPublished - 1 Nov 2021

Keywords

  • Artificial larynx
  • coughing
  • pattern recognition
  • speech
  • surface electromyography (sEMG)
  • swallowing
  • total laryngectomy

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