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Updated: Mar 13, 2026

Neuro-rehabilitation Approach for Sudden Sensorineural Hearing Loss
Published on: January 25, 2016
Detection of Unilateral Hearing Loss by Stationary Wavelet Entropy
Yudong Zhang1, Deepak Ranjan Nayak, Ming Yang
1Hunan Provincial Key Laboratory of Network Investigational Technology, Hunan Policy Academy, Changsha, Hunan 410138, China.
Aim:
Sensorineural hearing loss is correlated to massive neurological or psychiatric disease.
Materials:
T1-weighted volumetric images were acquired from fourteen subjects with right-sided hearing loss (RHL), fifteen subjects with left-sided hearing loss (LHL), and twenty healthy controls (HC).
Method:
We treated a three-class classification problem: HC, LHL, and RHL. Stationary wavelet entropy was employed to extract global features from magnetic resonance images of each subject. Those stationary wavelet entropy features were used as input to a single-hidden layer feedforward neuralnetwork classifier.
Results:
The 10 repetition results of 10-fold cross validation show that the accuracies of HC, LHL, and RHL are 96.94%, 97.14%, and 97.35%, respectively.
Conclusion:
Our developed system is promising and effective in detecting hearing loss.
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