Kimberley B P, Kimberley B M, Roth L
Hearing Research Laboratory, Calgary, Alberta, Canada.
Ear Nose Throat J. 1994 Nov;73(11):812-3, 817-23.
Distortion Product Emission (DPE) growth functions, demographic data, and pure tone thresholds were recorded in 229 normal-hearing and hearing-impaired ears. Half of the data set (115 ears) was used to train a set of neural networks to map DPE and demographic features to pure tone thresholds at six frequencies in the audiometric range. The six networks developed from this training process were then used to predict pure tone thresholds in the remaining 114-ear data set. When normal pure tone threshold was defined as a threshold less than 20 dB HL, frequency-specific prediction accuracy varied from 57% (correct classification of hearing impairment at 1025 Hz) to 100% (correct classification of hearing impairment at 2050 Hz). Overall prediction accuracy was 90% for impaired pure tone thresholds and 80% for normal pure tone thresholds. This neural network approach was found to be more accurate than discriminant analysis in the prediction of pure tone thresholds. It is concluded that a general strategy exists whereby DPE measures can accurately categorize pure tone thresholds as normal or impaired in large populations of ears with purely cochlear hearing dysfunction.
在229只听力正常和听力受损的耳朵中记录了畸变产物发射（DPE）增长函数、人口统计学数据和纯音阈值。数据集的一半（115只耳朵）用于训练一组神经网络，以将DPE和人口统计学特征映射到听力计范围内六个频率的纯音阈值。然后，从该训练过程中开发的六个网络用于预测其余114只耳朵数据集中的纯音阈值。当将正常纯音阈值定义为小于20 dB HL的阈值时，特定频率的预测准确率从57%（在1025 Hz处正确分类听力障碍）到100%（在2050 Hz处正确分类听力障碍）不等。对于受损纯音阈值，总体预测准确率为90%，对于正常纯音阈值，总体预测准确率为80%。发现这种神经网络方法在预测纯音阈值方面比判别分析更准确。得出的结论是，存在一种通用策略，通过该策略，DPE测量可以在大量纯耳蜗听力功能障碍的耳朵中准确地将纯音阈值分类为正常或受损。
