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An Innovative Algorithm for Privacy Protection in a Voice Disorder Detection System

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Biologically Inspired Cognitive Architectures (BICA) for Young Scientists (BICA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 636))

Abstract

Health information is critical for the patient and its unauthorized access may have server impact. With the advancement in the healthcare systems especially through the Internet of Things give rises to patient privacy. We developed a healthcare system that protects identity of patients using innovative zero-watermarking algorithm along with vocal fold disorders detection. To avoid audio signal distortion, proposed system embeds watermark in a secret key of identity by visual cryptography rather than audio signal. The secret shares generated through visual cryptography are inserted in the secret watermark key by computing the features of audio signals. The proposed technique is evaluated using audio samples taken from voice disorder database of the Massachusetts Eye and Ear Infirmary (MEEI). Experimental results prove that the proposed technique achieves imperceptibility with reliability to extract identity, unaffected disorder detection result with high robustness. The results are provided in form of Normalized Cross-Correlation (NCR), Bit Error Rate (BER), and Energy Ratio (ENR).

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References

  1. Gong, T., Huang, H., Li, P., Zhang, K., Jiang, H.: A medical healthcare system for privacy protection based on IoT. In: Paper Presented at the 2015 Seventh International Symposium on Parallel Architectures, Algorithms and Programming (2015)

    Google Scholar 

  2. Hsu, C.-L., Lee, M.-R., Su, C.-H.: The role of privacy protection in healthcare information systems adoption. J. Med. Syst. 37(5), 9966 (2013)

    Article  Google Scholar 

  3. Chatlani, N., Soraghan, J.J.: Local binary patterns for 1-D signal processing. In: Paper Presented at the 2010 18th European Signal Processing Conference (2010)

    Google Scholar 

  4. Houam, L., Hafiane, A., Boukrouche, A., Lespessailles, E., Jennane, R.: One dimensional local binary pattern for bone texture characterization. Pattern Anal. Appl. 17(1), 179–193 (2014)

    Article  MathSciNet  Google Scholar 

  5. Massachusette Eye & Ear Infirmry Voice & Speech LAB. Disordered Voice Database Model 4337 (Ver. 1.03) (1994)

    Google Scholar 

  6. Ali, Z., Elamvazuthi, I., Alsulaiman, M., Muhammad, G.: Detection of voice pathology using fractal dimension in a multiresolution analysis of normal and disordered speech signals. J. Med. Syst. 40(1), 20 (2015)

    Article  Google Scholar 

  7. Arias-LondoÃśo, J.D., Godino-Llorente, J.I., SÃąenz-LechÃşn, N., Osma-Ruiz, V., Castellanos-DomÃnguez, G.: An improved method for voice pathology detection by means of a HMM-based feature space transformation. Pattern Recogn. 43(9), 3100–3112 (2010)

    Article  Google Scholar 

  8. Godino-Llorente, J.I., Gomez-Vilda, P., Blanco-Velasco, M.: Dimensionality reduction of a pathological voice quality assessment system based on Gaussian mixture models and short-term cepstral parameters. IEEE Trans. Biomed. Eng. 53(10), 1943–1953 (2006)

    Article  Google Scholar 

  9. Markaki, M., Stylianou, Y.: Voice pathology detection and discrimination based on modulation spectral features. IEEE Trans. Audio Speech Lang. Process. 19(7), 1938–1948 (2011)

    Article  Google Scholar 

  10. Muhammad, G., Melhem, M.: Pathological voice detection and binary classification using MPEG-7 audio features. Biomed. Signal Process. Control 11, 1–9 (2014)

    Article  Google Scholar 

  11. Villa-Canas, T., Belalcazar-Bolamos, E., Bedoya-Jaramillo, S., Garces, J.F., Orozco-Arroyave, J.R., Arias-Londono, J.D., Vargas-Bonilla, J.F.: Automatic detection of laryngeal pathologies using cepstral analysis in Mel and Bark scales. In: Paper Presented at the XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA), 12–14 September 2012

    Google Scholar 

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Author information

Authors and Affiliations

  1. Digital Speech Processing Group, Department of Computer Engineering, College of Computer and Information Science, King Saud University, Riyadh, 11543, Saudi Arabia

    Zulfiqar Ali

  2. College of Computer and Information Science, King Saud University, Riyadh, Saudi Arabia

    Muhammad Imran & Muhammad Shoaib

  3. Department of Computer Engineering, College of Computer and Information Science, King Saud University, Riyadh, 11543, Saudi Arabia

    Wadood Abdul

Authors
  1. Zulfiqar Ali
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  2. Muhammad Imran
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  3. Wadood Abdul
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  4. Muhammad Shoaib
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Corresponding author

Correspondence to Zulfiqar Ali .

Editor information

Editors and Affiliations

  1. Krasnow Institute, George Mason University, Fairfax, VA, USA

    Alexei V. Samsonovich

  2. National Research Nuclear University MEPhI, Moscow, Russia

    Valentin V. Klimov

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Ali, Z., Imran, M., Abdul, W., Shoaib, M. (2018). An Innovative Algorithm for Privacy Protection in a Voice Disorder Detection System. In: Samsonovich, A., Klimov, V. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. BICA 2017. Advances in Intelligent Systems and Computing, vol 636. Springer, Cham. https://doi.org/10.1007/978-3-319-63940-6_32

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  • DOI: https://doi.org/10.1007/978-3-319-63940-6_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63939-0

  • Online ISBN: 978-3-319-63940-6

  • eBook Packages: EngineeringEngineering (R0)

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