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Implementation of Point of Care System Using Bio-medical Signal Steganography

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • S. Thenmozhi

    (Dayananda Sagar College of Engineering)

  • Ramgopal Segu

    (Dayananda Sagar College of Engineering)

  • Shahla Sohail

    (Dayananda Sagar College of Engineering)

  • P. Sureka

    (Dayananda Sagar College of Engineering)

Abstract

Due to the gargantuan development of technology in medicine, transmission of medical data securely through multimedia has become possible. The foremost objective of transmission of secret medical data over the internet is, it should be difficult to access the secret data information for the attackers. In this research patient’s secret medical data is concealed in the bio-medical signal like EEG/ECG/PPG. The information that is transmitted generally contains biomedical-signals and patient data. Major apprehensions comprises of authenticity and privacy of the data being transmitted. A secret key is used which is flanked by the receiver and sender involved in the system and unknown to others. A novel steganography technique is introduced in this paper that guarantees (1) security of private information applying a key and (2) uniqueness of the bio-medical-signals. To exploit embedding, Fast-Walsh-Hadamard Transform is applied for conversion of the signals into a set of coefficients. The recommended procedure uses sensors such as pulse sensor, BP sensor, DHT-11 sensor to monitor the patient in POC system. To accomplish least distortion, least significant coefficients bit is considered. The impact of the algorithm on the bio-medical signal is less and recovery of the signal at the transmitting side can be done with a smaller amount of distortion. Proposed technique is implemented in POC.

Suggested Citation

  • S. Thenmozhi & Ramgopal Segu & Shahla Sohail & P. Sureka, 2020. "Implementation of Point of Care System Using Bio-medical Signal Steganography," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 89-103, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-41862-5_9
    DOI: 10.1007/978-3-030-41862-5_9
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