K. Behbehani et al., PHARYNGEAL WALL VIBRATION DETECTION USING AN ARTIFICIAL NEURAL-NETWORK, Medical & biological engineering & computing, 35(3), 1997, pp. 193-198
An artificial-neural-network-based detector of pharyngeal wall vibrati
on (PWV) is presented. PWV signals the imminent occurrence of obstruct
ive sleep apnoea (OSA) in adults who suffer from OSA syndrome, Automat
ed detection of PWV is very important in enhancing continuous positive
airway pressure (CPAP) therapy by allowing automatic adjustment of th
e applied airway pressure by a procedure called automatic positive air
way pressure (APAP) therapy. A network with 15 inputs, one output, and
two hidden layers, each with two Adaline nodes, is used as part of a
PWV detection scheme. The network is initially trained using nasal mas
k pressure data from five positively diagnosed OSA patients. The perfo
rmance of the ANN-based detector is evaluated using data from five dif
ferent OSA patients. The results show that on the average it correctly
detects the presence of PWV events at a rate of similar or equal to 9
2% and correctly distinguishes normal breaths similar or equal to 98%
of the time, Further, the ANN-based detector accuracy is not affected
by the pressure level required for therapy.