Mobile Networks and Applications

, Volume 20, Issue 3, pp 391–399 | Cite as

Cloud-Assisted Speech and Face Recognition Framework for Health Monitoring

  • M. Shamim Hossain
  • Ghulam Muhammad


The increasing demand for the remote monitoring of patients combined with the promising potential of cloud computing has enabled the design and development of a number of cloud-based systems and services for healthcare. The cloud computing, in combination with the popularity of smart handheld devices, has inspired healthcare professionals to remotely monitor patients’ health while the patient is at home. To this end, this paper proposes a cloud-assisted speech and face recognition framework for elderly health monitoring, where handheld devices or video cameras collect speech along with face images and deliver to the cloud server for possible analysis and classification. In the framework, a patient’s state such as pain, tensed, and so forth is recognized from his or her speech and face images. The patient state recognition system extracts local features from speech, and texture descriptors from face images. Then it classifies using support vector machines. The recognized state is later sent to the remote care center, healthcare professionals and providers for necessary services in order to provide seamless health monitoring. Experiments have been performed to validate the approach and to evaluate the suitability of this framework in terms of accuracy and time requirements. The results demonstrate the effectiveness of the proposed approach with regards to face and speech processing.


Elderly health monitoring Face recognition Speech recognition Cloud based healthcare 



The authors extend their appreciation to the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia for funding this work through the research group Project No. RGP VPP-228.


  1. 1.
    Pandey S, Voorsluys W, Niu S, Khandoker A, Buyya R (2012) An autonomic cloud environment for hosting ECG data analysis services. Futur Gener Comput Syst 28(1):147–151CrossRefGoogle Scholar
  2. 2.
    Kaur PD, Chan I (2014) Cloud based intelligent system for delivering healthcare as a service. Comput Methods Prog Biomed 113(1):346–359CrossRefGoogle Scholar
  3. 3.
    Xia H, Asif I, Zhaoa X (2013) Cloud-ECG for real time ECG monitoring and analysis. Comput methods program med 110(2013):253–259CrossRefGoogle Scholar
  4. 4.
    Kuo AM (2011) Opportunities, Challenges of cloud computing to improve healthcare services. J Med Internet Res 13(3):e67CrossRefGoogle Scholar
  5. 5.
    Ou Y-Y, Shih P-Y, Chin Y-H, Kuan T-W, Wang J-F, Shih S-H (2013) Framework of ubiquitous healthcare system based on cloud computing for elderly living. In: IEEE APSIPA’ 2013. Kaohsiung, TaiwanGoogle Scholar
  6. 6.
    Rowlands DD, McNab T, Laakso L, James DA (2012) Cloud based activity monitoring system for health and sport. IEEE IJCNN’ 2012. Brisbane, QLD, AustraliaGoogle Scholar
  7. 7.
    Ho C-S, Chiang KC (2010) Towards the ubiquitous healthcare by integrating active monitoring and intelligent cloud. ICCIT’2010. Seoul, South KoreaGoogle Scholar
  8. 8.
    Parente R, Kock N, Sonsini J (2004) An Analysis of the Implementation and Impact of Speech-Recognition Technology in the Healthcare Sector. Perspect Health Inf Mang 1:5Google Scholar
  9. 9.
    Takahashi S, Morimoto T, Maeda S, Tsuruta N (2003) Dialogue Experiment for Elderly People in Home healthcare System, Text, Speech, and Dialogue. Lect Notes Comput Sci 2807: 418–423Google Scholar
  10. 10.
    Dorman MF, Gifford RH (2010) Combining acoustic and electric stimulation in the service of speech recognition. Int J Audiol 49(12):912–919CrossRefGoogle Scholar
  11. 11.
    Hossain MS, Muhammad G (2014) Cloud-based Collaborative Media Service Framework for Health-Care. International Journal of Distributed Sensor Networks. 2014: Article ID 858712Google Scholar
  12. 12.
    Diraco G, Leone A, Siciliano P (2010) An active vision system for fall detection and posture recognition in elderly healthcare. In Proc DATE 2010:1536–1541Google Scholar
  13. 13.
    Cardoner N, Harrison BJ, Pujol J, Soriano-Mas C, Hernandez-Ribas R, López-Solá M, Real E , Deus J, Ortiz H, Alonso P, Menchón JM (2011) Enhanced brain responsiveness during active emotional face processing in obsessive compulsive disorder. World J Biol Psychiatry 12(5):349–363CrossRefGoogle Scholar
  14. 14.
    Dickey CC, Panych LP, Voglmaier MM, Niznikiewicz MA, Terry DP, Murphy C, Zacks R, Shenton ME, McCarley RW (2011) Facial emotion recognition and facial affect display in schizotypal personality disorder. Schizophrenia Res 131(1–3):242–249CrossRefGoogle Scholar
  15. 15.
    Nitta T (1998) A novel feature-extraction for speech recognition based on multiple acoustic-feature planes. In: Proceedings of IEEE ICASSP’98, I: 29-32Google Scholar
  16. 16.
    Vapnik V (1998) Statistical Learning Theory. Wiley, New YorkMATHGoogle Scholar
  17. 17.
    Martinez JM (2002) MPEG-7 Overview of MPEG-7 Description Tools, Part 2. IEEE Multimedia July-September: 83–93Google Scholar
  18. 18.
    Foster I, Kesselman C, Nick JM, Tuecke S (2002) Grid services for distributed system integration. IEEE Comput 35(6):37–46CrossRefGoogle Scholar
  19. 19.
    Rabiner L, Juang BH (1993) Fundamentals of speech recognition. Prentice-Hall, Englewood CliffsGoogle Scholar
  20. 20.
    Muhammad G (2015) Date fruits classification using texture descriptors and shape-size features. Eng Appl Artif Intell 37:361–367CrossRefGoogle Scholar
  21. 21.
    Chen M (2014) NDNC-BAN: Supporting Rich Media Healthcare Services via Named Data Networking in Cloud-assisted Wireless Body Area Networks. Info Sci 284(10):142–156CrossRefGoogle Scholar
  22. 22.
    Chen M, Gonzalez S, Zhang Q, Li M, Leung V (2010) A 2G-RFID based E-healthcare System. IEEE Wirel Commun Mag 17(1):37–43CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Software Engineering Department, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhKingdom of Saudi Arabia
  2. 2.Computer Engineering Department, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhKingdom of Saudi Arabia

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