PRINCIPLES OF COLLECTING PHYSIOLOGICAL BIOMETRIC DATA FROM WEARABLE DEVICES FOR AUTHENTICATION SYSTEMS

Abstract

The principles and protocols for collecting physiological biometric data from wearable devices, in particular the
Apple Watch, are investigated for building continuous user authentication systems in information systems. A comparative
analysis of existing approaches to collecting biometric signals – heart rate (HR), heart rate variability (HRV), blood
oxygen saturation (SpO₂), and skin temperature – is conducted, with a focus on the Apple Watch platform and the
HealthKit framework. The limitations and open issues specific to data collection from commercial smartwatches are
systematized, including irregular sampling rates, motion artifacts, lack of direct access to raw PPG signals, and limitations
of background data collection. An improved protocol for collecting multimodal biometric data is proposed, based on
synchronized parallel recording of four physiological signals with a contextual labeling mechanism for the user’s
physiological state. A schematic diagram of the data collection process has been developed, which includes the stages of
signal quality control, motion artifact filtering based on the accelerometer, and the formation of a biometric user matrix
with periodic updating. The scientific novelty lies in the integrated approach to collecting four physiological parameters
simultaneously, taking into account the context of activity, which ensures the formation of a more stable biometric profile
compared to single-channel approaches.
Keywords: physiological biometric signals, mobile devices, authentication, blockchain, continuous
authentication, information security, information protection, user identification.

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