Hearing Loss via Wavelet Entropy and Particle Swarm Optimized Trained Support Vector Machine

  • BAO F
  • NAKAMURA K
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Abstract

This paper proposed a method that combines wavelet entropy with particle swarm optimized support vector machine to detect hearing loss (HL). The dataset for this task contains 75 images: 25 healthy controls, 25 left-sided hearing loss patients, and 25 right-sided hearing loss patients. The results shows that our method has higher accuracy than some traditional method. The sensitivities over healthy control, left-sided HL patients, and right-sided HL patients are 85.20± 3.79, 85.20± 4.64, and, 86.40± 5.06, respectively. The overall accuracy is 85.60± 0.84.

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BAO, F.-Z., & NAKAMURA, K. (2019). Hearing Loss via Wavelet Entropy and Particle Swarm Optimized Trained Support Vector Machine. DEStech Transactions on Engineering and Technology Research, (ecae). https://doi.org/10.12783/dtetr/ecae2018/27724

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