Multimedia Systems

, Volume 25, Issue 5, pp 565–575 | Cite as

Smart healthcare monitoring: a voice pathology detection paradigm for smart cities

  • M. Shamim HossainEmail author
  • Ghulam Muhammad
  • Atif Alamri
Special Issue Paper


With the increasing demand for automated, remote, intelligent, and real-time healthcare services in smart cities, smart healthcare monitoring is necessary to provide improved and complete care to residents. In this monitoring, health-related media or signals collected from smart-devices/objects are transmitted and processed to cater to the need for quality care. However, it is challenging to create a framework or method to handle media-related healthcare data analytics or signals (e.g., voice/audio, video, or electroglottographic (EGG) signals) to meet the complex on-demand healthcare needs for successful smart city management. To this end, this paper proposes a cloud-oriented smart healthcare monitoring framework that interacts with surrounding smart devices, environments, and smart city stakeholders for affordable and accessible healthcare. As a smart city healthcare monitoring case study, a voice pathology detection (VPD) method is proposed. In the proposed method, two types of input, a voice signal and an EGG signal, are used. The input devices are connected to the Internet and the captured signals are transmitted to the cloud. The signals are then processed and classified as either normal or pathologic with a confidence score. These results are passed to registered doctors that make the final decision and take appropriate action. To process the signals, local features are extracted from the first-order derivative of the voice signal, and shape and cepstral features are extracted from the EGG signal. For classification, a Gaussian mixture model-based approach is used. Experimental results show that the proposed method can achieve VPD that is more than 93% accurate.


Smart healthcare Smart city Voice pathology detection Healthcare media-cloud 



This work is financially supported by the King Saud University, Deanship of Scientific Research, Research Chair of Pervasive and Mobile Computing.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • M. Shamim Hossain
    • 1
    • 3
    Email author
  • Ghulam Muhammad
    • 2
  • Atif Alamri
    • 1
    • 3
  1. 1.Department of Software Engineering, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhSaudi Arabia
  2. 2.Department of Computer Engineering, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhSaudi Arabia
  3. 3.Research Chair of Pervasive and Mobile ComputingKing Saud UniversityRiyadhSaudi Arabia

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