Automated audiometer for home based health care based on mobile app

Hearing deficiency is one of the most important issues that people experience these days. This hearing loss is assessed using an audiometer. An audiometer is an instrument that tests the efficacy or hearing capacity of the ear. In this proposed study, an Android app is created along with a bone conduction device that functions as an audiometer for bone conduction. The aim and objectives of the proposed study are as follows: i) to create an automatic bone conduction system for self-diagnosing a patient’s hearing ability; ii) to use pure tone audiometry to assess auditory thresholds at various frequencies and classify the normal and hearing loss patients with different machine learning classifiers. The right and left ear features of normal and hearing loss patients were given as the input to the SVM, k-NN and Naive Bayes classifier. The Naive bayes classifier produced 100% accuracy and outperformed well compared to the SVM (98%) and k-NN classifier (98%). The developed mobile app would be used to conduct the self-audiometry test at home and reduce the expense of audiometry tests.