Title :
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
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;
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
DOI :
10.1109/IEMBS.1994.415345
