Detection and analysis of symptomatic patterns in audio bio-logical signals at low power consumption and optimized area

  • Authors

    • Syed Thouheed Ahmed
    • Mariyam Fathima
    • Syeda Tasmiya Tarannum
    • Asha Kiran M. U
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.15512
  • Audio Signal Processing, Biometric, Thresholding, Classification

  • Abstract

    Audio signal processing for a biometric analysis of a signal is most challenging field in current era. In this paper, a design is proposed for the acquisition of audio signals and then process under a standard pattern values with the consideration of lower attributes such as power and system scalability for detection of symptomatic pattern. In this paper, a subsequent low power design is used with a mathematical matrix with respect to energy, Quasi-Average (QA), and other various coefficients of wavelets under threshold value analysis. In later process of Mel-frequent analysis is processed and distinguished among signals such as cough and sneeze, with most alike patterns for thresholding value of attribute extracted under matching. The proposed system is more feasible with the user inputs and the Indian environment. Typically, this system is designed and dedicated for Indian digital development

     

     

  • References

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  • How to Cite

    Thouheed Ahmed, S., Fathima, M., Tasmiya Tarannum, S., & Kiran M. U, A. (2018). Detection and analysis of symptomatic patterns in audio bio-logical signals at low power consumption and optimized area. International Journal of Engineering & Technology, 7(2.33), 839-842. https://doi.org/10.14419/ijet.v7i2.33.15512

    Received date: 2018-07-13

    Accepted date: 2018-07-13

    Published date: 2018-06-08