A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms
The incorporation of the cloud technology with the Internet of Things (IoT) is significant in order to obtain better performance for a seamless, continuous, and ubiquitous framework. IoT has many applications in the healthcare sector, one of these applications is voice pathology monitoring. Unfortun...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2020
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| Online Access: | http://eprints.utm.my/93921/1/FahadTahaAlDhief2020_ASurveyofVoicePathologySurveillanceSystems.pdf |
| _version_ | 1796865719600676864 |
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| author | Al-Dhief, F. T. Abdul Latiff, N. M. Nik Abd. Malik, N. N. Salim, N. S. Mat Baki, M. Albadr, M. A. A. Mohammed, M. A. |
| author_facet | Al-Dhief, F. T. Abdul Latiff, N. M. Nik Abd. Malik, N. N. Salim, N. S. Mat Baki, M. Albadr, M. A. A. Mohammed, M. A. |
| author_sort | Al-Dhief, F. T. |
| collection | ePrints |
| description | The incorporation of the cloud technology with the Internet of Things (IoT) is significant in order to obtain better performance for a seamless, continuous, and ubiquitous framework. IoT has many applications in the healthcare sector, one of these applications is voice pathology monitoring. Unfortunately, voice pathology has not gained much attention, where there is an urgent need in this area due to the shortage of research and diagnosis of lethal diseases. Most of the researchers are focusing on the voice pathology and their finding is only to differentiating either the voice is normal (healthy) or pathological voice, where there is a lack of the current studies for detecting a certain disease such as laryngeal cancer. In this paper, we present an extensive review of the state-of-the-art techniques and studies of IoT frameworks and machine learning algorithms used in the healthcare in general and in the voice pathology surveillance systems in particular. Furthermore, this paper also presents applications, challenges and key issues of both IoT and machine learning algorithms in the healthcare. Finally, this paper highlights some open issues of IoT in healthcare that warrant further research and investigation in order to present an easy, comfortable and effective diagnosis and treatment of disease for both patients and doctors. |
| first_indexed | 2024-03-05T21:01:21Z |
| format | Article |
| id | utm.eprints-93921 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T21:01:21Z |
| publishDate | 2020 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | utm.eprints-939212022-02-28T13:16:17Z http://eprints.utm.my/93921/ A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms Al-Dhief, F. T. Abdul Latiff, N. M. Nik Abd. Malik, N. N. Salim, N. S. Mat Baki, M. Albadr, M. A. A. Mohammed, M. A. TK Electrical engineering. Electronics Nuclear engineering The incorporation of the cloud technology with the Internet of Things (IoT) is significant in order to obtain better performance for a seamless, continuous, and ubiquitous framework. IoT has many applications in the healthcare sector, one of these applications is voice pathology monitoring. Unfortunately, voice pathology has not gained much attention, where there is an urgent need in this area due to the shortage of research and diagnosis of lethal diseases. Most of the researchers are focusing on the voice pathology and their finding is only to differentiating either the voice is normal (healthy) or pathological voice, where there is a lack of the current studies for detecting a certain disease such as laryngeal cancer. In this paper, we present an extensive review of the state-of-the-art techniques and studies of IoT frameworks and machine learning algorithms used in the healthcare in general and in the voice pathology surveillance systems in particular. Furthermore, this paper also presents applications, challenges and key issues of both IoT and machine learning algorithms in the healthcare. Finally, this paper highlights some open issues of IoT in healthcare that warrant further research and investigation in order to present an easy, comfortable and effective diagnosis and treatment of disease for both patients and doctors. Institute of Electrical and Electronics Engineers Inc. 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/93921/1/FahadTahaAlDhief2020_ASurveyofVoicePathologySurveillanceSystems.pdf Al-Dhief, F. T. and Abdul Latiff, N. M. and Nik Abd. Malik, N. N. and Salim, N. S. and Mat Baki, M. and Albadr, M. A. A. and Mohammed, M. A. (2020) A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms. IEEE Access, 8 . pp. 64514-64533. ISSN 2169-3536 https://doi.org/10.1109/ACCESS.2020.2984925 DOI: 10.1109/ACCESS.2020.2984925 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Al-Dhief, F. T. Abdul Latiff, N. M. Nik Abd. Malik, N. N. Salim, N. S. Mat Baki, M. Albadr, M. A. A. Mohammed, M. A. A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title | A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title_full | A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title_fullStr | A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title_full_unstemmed | A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title_short | A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| title_sort | survey of voice pathology surveillance systems based on internet of things and machine learning algorithms |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/93921/1/FahadTahaAlDhief2020_ASurveyofVoicePathologySurveillanceSystems.pdf |
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