Automatic Voice Pathology Monitoring Using Parallel Deep Models for Smart Healthcare

Recent advancements in wireless communication and machine learning technologies aid in the development of an accurate and affordable healthcare facility. In this paper, we propose a smart healthcare framework in a mobile platform using deep learning. In the framework, a smartphone records a voice signal of a client and sends it to a cloud server. The cloud server processes the signal and classifies it as normal or pathological using a parallel convolutional neural network model. The decision on the signal is then transferred to the doctor for a prescription. Two publicly available databases were used in the experiments, where voice samples were played in front of a smartphone. The experimental results show the suitability of the proposed framework in the healthcare framework.