WEARABLE SENSORS FOR CONTINUOUS BIOSIGNAL MONITORING: CHALLENGES, AI INTEGRATION AND CURRENT LIMITATIONS
Keywords:
wearable sensors, biosignal monitoring, continuous health monitoring, AI-driven healthcare, signal quality, power consumption, data privacy, algorithmic bias, stress detection, EDA, PPG, ECG.Abstract
Wearable sensor technologies have emerged as a transformative platform for continuous, real-time biosignal monitoring, enabling week- and month-long acquisition of physiological parameters outside clinical settings. This paper presents a systematic review of wearable biosignal monitoring systems, focusing on three critical dimensions: device capabilities and signal quality, artificial intelligence (AI) integration for automated analysis, and unresolved challenges that impede widespread clinical adoption. Drawing on three key recent studies — Stuart et al. (APL Bioengineering, 2022), Huang et al. (Biosensors, 2025), and Bolpagni et al. (Sensors, 2024) — the review identifies power consumption, user compliance, data interoperability, algorithmic bias, and real-world deployment as the principal open challenges.
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