Abstract:
Automatic long-term recording of esophageal pressures by means of intraluminal transducers
is used increasingly for evaluation of esophageal function. Most automatic analysis
techniques are based on detection of derived parameters from the time series by means
of arbitrary rule-based criterions. The aim of the present work has been to test the
ability of neural networks to identify abnormal contraction patterns in patients with
nonobstructive dysphagia (NOBD).
Nineteen volunteers and 22 patients with NOBD underwent simultaneous recordings of
four pressures in the esophagus for at least 23 hours. Data from 21 subjects were
selected for training. The performances of two trained networks were subsequently
verified on reference data from 20 subjects. The results show that non-parametric
classification by means of neural networks has good potentials. Back propagation shows
good performance with a sensitivity of 1.0 and a specificity of 0.8.
Keywords:
Neural Network - Prolonged Recording - Esophagus - Motility - Non-Obstructive Dysphagia
