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