Medical Engineering & Physics
Volume 31, Issue 9 , Pages 1049-1055 , November 2009

Swallow segmentation with artificial neural networks and multi-sensor fusion

  • Joon Lee

      Affiliations

    • Bloorview Research Institute, Toronto, Canada
    • Toronto Rehabilitation Institute, Toronto, Canada
    • Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
    • ,
  • Catriona M. Steele

      Affiliations

    • Toronto Rehabilitation Institute, Toronto, Canada
    • Bloorview Research Institute, Toronto, Canada
    • Department of Speech-Language Pathology, University of Toronto, Toronto, Canada
    • ,
  • Tom Chau

      Affiliations

    • Bloorview Research Institute, Toronto, Canada
    • Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada
    • Corresponding Author InformationCorresponding author.

Received 25 September 2008 ,Revised 2 May 2009 ,Accepted 1 July 2009.

References 

  1. Sherman B, Nisenboum J, Jesberger B, Morrow C, Jesberger J. Assessment of dysphagia with the use of pulse oximetry. Dysphagia. 1999;14:152–156
  2. Lee J, Blain S, Casas M, Kenny D, Berall G, Chau T. A radial basis classifier for the automatic detection of aspiration in children with dysphagia. Journal of NeuroEngineering and Rehabilitation. 2006;3:14
  3. Reddy N, Katakam A, Gupta V, Unnikrishnan R, Narayanan J, Canilang E. Measurements of acceleration during videofluorographic evaluation of dysphagic patients. Medical Engineering & Physics. 2000;22(6):405–412
  4. Leslie P, Drinnan M, Finn P, Ford G, Wilson J. Reliability and validity of cervical auscultation: a controlled comparison using videofluoroscopy. Dysphagia. 2004;19(4):231–240
  5. Crary M, Baldwin B. Surface electromyographic characteristics of swallowing in dysphagia secondary to brainstem stroke. Dysphagia. 1997;12:180–187
  6. Selley W, Flack F, Ellis R, Brooks W. Respiratory patterns associated with swallowing. Part 2. Neurologically impaired dysphagic patients. Age and Ageing. 1989;18:173–176
  7. Vitulano S., DiRuberto C., Nappi M., Different methods to segment biomedical images (1997) 1861–1902.
  8. Deklerck R, Cornelis J, Bister M. Segmentation of medical images. Image and Vision Computing. 1993;11(8):486–503
  9. Andreao R, Dorizzi B, Boudy J. ECG signal analysis through hidden markov models. IEEE Transactions on Biomedical Engineering. 2006;53(8):1541–1549
  10. Lehner R, Rangayyan R. A three-channel microcomputer system for segmentation and characterization of the phonocardiogram. IEEE Transactions on Biomedical Engineering. 1987;34(6):485–489
  11. Andre-Obrecht R. A new statistical approach for the automatic segmentation of continuous speech signals. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1988;36(1):29–40
  12. Hamlet S, Nelson R, Patterson R. Interpreting the sounds of swallowing: fluid flow through the cricopharyngeus. Annals of Otology, Rhinology, and Laryngology. 1990;99:749–752
  13. Lee J, Steele C, Chau T. Time and time-frequency characterization of dual-axis swallowing accelerometry signals. Physiological Measurement. 2008;29:1105–1120
  14. Das A, Reddy N, Narayanan J. Hybrid fuzzy logic committee neural networks for recognition of swallow acceleration signals. Computer Methods and Programs in Biomedicine. 2001;64(2):87–99
  15. Chau T, Chau D, Casas M, Berall G, Kenny D. Investigating the stationarity of paediatric aspiration signals. IEEE Transactions on Neural and Rehabilitation Engineering. 2005;13(1):99–105
  16. Logemann J. Evaluation and treatment of swallowing disorders. Austin, TX: Pro-Ed; 1998;
  17. Miller A. Deglutition. Physiological Reviews. 1982;62:129–184
  18. Jean A. Brain stem control of swallowing: neuronal network and cellular mechanisms. Physiological Reviews. 2001;81(2):929–969
  19. Orizio C. Muscle sound: bases for the introduction of a mechanomyographic signal in muscle studies. Critical Reviews in Biomedical Engineering. 1993;21:201–243
  20. Silva J, Heim W, Chau T. A self-contained, mechanomyography-driven externally powered prosthesis. Archives of Physical Medicine and Rehabilitation. 2005;86:2066–2070
  21. Perlman A, Ettema S, Barkmeier J. Respiratory and acoustic signals associated with bolus passage during swallowing. Dysphagia. 2000;15:89–94
  22. Martin B, Logemann J, Shaker R, Dodds W. Coordination between respiration and swallowing: respiratory phase relationships and temporal integration. Journal of Applied Physiology. 1994;76(2):714–723
  23. Hiss S, Treole K, Stuart A. Effects of age, gender, bolus volume, and trial on swallowing apnea duration and swallow/respiratory phase relationships of normal adults. Dysphagia. 2001;16:128–135
  24. Luo R, Kay M. Multisensor integration and fusion in intelligent systems. IEEE Transactions on Systems, Man, and Cybernetics. 1989;19(5):901–931
  25. Luo R, Yih C, Su K. Multisensor fusion and integration: approaches, applications, and future research directions. IEEE Sensors Journal. 2002;2(2):107–119
  26. Duda R, Nitzan D, Barrett P. Use of range and reflectance data to find planar surface regions. IEEE PAMI. 1979;1:259–271
  27. Gil B, Mitiche A, Aggarwal J. Experiments in combining intensity and range edge maps. CGIP. 1983;21:395–411
  28. Hackett J, Shah M. Multi-sensor fusion: a perspective. In: Proceedings of IEEE International Conference on Robotics and Automation. 1990;p. 1324–1330
  29. Ozkan M, Dawant B, Maciunas R. Neural-network-based segmentation of multi-modal medical images: a comparative and prospective study. IEEE Transactions on Medical Imaging. 1993;12:534–544
  30. Amartur S, Piraino D, Takefuji Y. Optimization neural networks for the segmentation of magnetic resonance images. IEEE Transactions on Medical Imaging. 1992;11(2):215–220
  31. Duda R, Hart P, Stork D. Pattern classification. 2nd ed.. New York: John Wiley and Sons; 2000;
  32. Haag A, Goronzy S, Schaich P, Williams J. Emotion recognition using bio-sensors: first steps towards an automatic system. Lecture Notes in Computer Science. 2004;36–48
  33. Silva J., Chau T., Coupled microphone-accelerometer sensor pair for dynamic noise reduction in MMG signal recording, Electronics Letters 39.
  34. Tarata M., Mechanomyography versus electromyography, in monitoring the muscular fatigue, BioMedical Engineering OnLine 2.
  35. Martin-Harris B, Brodsky M, Michel Y, Ford C, Walters B, Heffner J. Breathing and swallowing dynamics across the adult lifespan. Archives Otolaryngology Head & Neck Surgery. 2005;131:762–770
  36. Miller A. The neuroscientific principles of swallowing and dysphagia. San Diego: Singular Publishing Group; 1999;
  37. McConnel F, Cerenko D, Jackson R, Guffin T. Timing of major events of pharyngeal swallowing. Archives Otolaryngology Head & Neck Surgery. 1988;114:1413–1418
  38. Perlman A, He X, Barkmeier J, Leer EV. Bolus location associated with videofluoroscopic and respirodeglutometric events. Journal of Speech, Language, and Hearing Research. 2005;48:21–33
  39. Chen J, Tsai C, Young J, Kodell R. Classification ensembles for unbalanced class sizes in predictive toxicology. SAR and QSAR in Environmental Research. 2005;16(6):517–529
  40. Lu Y, Guo H, Feldkamp L. Robust neural learning from unbalanced data samples. In: IEEE World Congress on Computational Intelligence, vol. 3. 1998;p. 1816–1821
  41. Tzanis G, Berberidis C, Alexandridou A, Vlahavas I. Improving the accuracy of classifiers for the prediction of translation initiation sites in genomic sequences. In: Advances in Informatics, of Lecture Notes in Computer Science, vol. 3746. Springer-Verlag; 2005;p. 426–436
  42. Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters. 2006;27:861–874
  43. Daniels S, Foundas A. Swallowing physiology of sequential straw drinking. Dysphagia. 2001;16:176–182
  44. Tabaee A, Johnson P, Gartner C, Kalwerisky K, Desloge R, Stewart M. Patient-controlled comparison of flexible endoscopic evaluation of swallowing with sensory testing (feesst). The Laryngoscope. 2006;116:821–825

PII: S1350-4533(09)00144-1

doi: 10.1016/j.medengphy.2009.07.001

Medical Engineering & Physics
Volume 31, Issue 9 , Pages 1049-1055 , November 2009

Article Tools

* Image Usage & Resolution