Abstract
Nowadays, the use of mobile application is most important thing in the healthcare sector is increasing rapidly. Mobile technologies not only for communication for multimedia content (e.g. clinical audio-visual notes and medical records) but also promising solutions for people who desire the identification, monitoring, and treatment of their health conditions anywhere and at any time. Mobile E-healthcare systems can contribute to make patient care faster, better, and cheaper. Several pathological conditions can benefit from the use of mobile technologies. In this paper we focus on dysphonia, an alteration of the voice quality that affects about one person in three at least once in his/her lifetime. Voice disorders are rapidly spreading, although they are often underestimated. Mobile health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is necessary to realize a valid and precise mobile health system. . This technique is evaluated by based on experimental results deep neural networks with machine learning approach to provide an accuracy of 99.89% in detecting voice. In this field to detect any abnormal structure and analysis without human intervention in health care sector to enhance the utility of well beginning system.
Highlights
The introduction of mobile devices for data transmission or disease control and monitoring has been a main attraction of research and business communities
Probably due to the diffusion of the Internet of Things (IoT) and cloud technologies, there has been a development of monitoring systems in an unobtrusive, portable and easy way using wearable sensors and wireless communications, such as the solutions described in [2]–[7]
We have evaluated the performance of Support Vector Machine (SVM), the principal adopted technique in literature in relation to the Kernel function, and of some other machine learning algorithms used to identify the presence of voice disorders
Summary
The introduction of mobile devices for data transmission or disease control and monitoring has been a main attraction of research and business communities They offer, numerous opportunities to realise efficient mobile health (mhealth) systems. Probably due to the diffusion of the Internet of Things (IoT) and cloud technologies, there has been a development of monitoring systems in an unobtrusive, portable and easy way using wearable sensors and wireless communications, such as the solutions described in [2]–[7] These systems are able to achieve health data monitoring and analysis, helpful for patients suffering from cardiovascular diseases or Vengateshwaran M et al / International Research Journal of Multidisciplinary Technovation /2019, 1(5), 1-7 for their physical therapy. M-health systems could be an efficient support for the diagnosis and screening of voice disorders
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