Neural networks for recognition of acceleration patterns during swallowing and coughing

Author

Prabhu, Deepa N Fernandes ; Reddy, Narender P. ; Canilang, Enrique P.

Author_Institution

Dept. of Biomed. Eng., Akron Univ., OH, USA

fYear

1994

fDate

1994

Firstpage

1105

Abstract

The acceleration signal during swallowing was filtered and segmented. The parameters extracted from the signal were used to develop and train two sets of neural network models. The first neural network model was developed to differentiate between the acceleration signals of normal, dysphagic and coughing. The second neural network model was developed to differentiate between acceleration during swallowing in normal, mild dysphagic, moderate dysphagic and severe dysphagic subjects

Keywords

biomechanics; acceleration pattern recognition; acceleration signal; coughing; dysphagic signals; filtering; mild dysphagic subjects; moderate dysphagic subjects; neural networks; normal signals; parameter extraction; segmentation; severe dysphagic subjects; swallowing; Acceleration; Accelerometers; Biomedical engineering; Biomedical measurements; Distortion measurement; Head; Neural networks; Pattern recognition; Phase measurement; Pressure measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE

Conference_Location

Baltimore, MD

Print_ISBN

0-7803-2050-6

Type

conf

DOI

10.1109/IEMBS.1994.415345

Filename

415345