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This study introduces an AI system using vital signs for biometric authentication in mobile patient monitoring. This enhances security and prevents device-patient mix-ups, improving clinical workflows.

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence
  • Healthcare Security

Background:

  • Mobile patient monitoring systems lack robust identity verification.
  • Device-patient mix-ups pose significant safety risks in healthcare.
  • Current 'intelligent medical devices' for patient identification are unavailable.

Purpose of the Study:

  • To develop an AI-based biometric authentication system using physiological signals.
  • To enable patient identification based on unique biometric patterns.
  • To enhance security and safety in mobile patient monitoring.

Main Methods:

  • Utilizing vital signs (physiological signals) for biometric authentication.
  • Developing an AI algorithm for pattern recognition and identification.
  • Integrating the authentication component into a patient monitoring platform.

Main Results:

  • Successful realization of an AI-based identification system.
  • Demonstrated feasibility of biometric authentication using vital signs.
  • Established a method for pre-use patient identity verification.

Conclusions:

  • The developed system offers a reliable method for verifying patient identity before device use.
  • Integration into monitoring platforms supports safer and more efficient clinical workflows.
  • This AI-driven biometric authentication addresses a critical gap in intelligent medical devices.