Motion-Aware Low-Power Wearable Photoplethysmography System with Metamaterial-Enhanced Wireless Telemetry.

Authors

Luvsanbat Khurelbaatar, Jungang Zhang, Jiaoran Wang, Ali Mokhtarzade, Bhavani Yalagala, Pouya Khosravi, Chi-Wa U, Morteza Amjadi, Hadi Heidari

Published in

IEEE transactions on biomedical circuits and systems. Volume PP. Aug 03, 2026. Epub Aug 03, 2026.

Abstract

In wireless photoplethysmography (PPG) systems, motion artifacts (MAs) and high-power consumption of PPG data acquisition are the critical bottlenecks. MAs induced by body movement during long-term wear significantly degrade PPG signal fidelity, thereby increasing post-processing power consumption. Although previous studies have investigated MA mitigation, power optimization, and wireless connectivity independently, their co-design and system-level integration remains largely unexplored. This paper presents a motion-controlled wearable (MCW) wireless PPG sensing system that features an autonomous motion-gated sampling technique, adaptive power management, and robust data transfer via a metamaterial-enhanced telemetry link. The MCW system autonomously employs motion-gated sampling to acquire heart rate (HR) and blood oxygen saturation (SpO₂) data under different physical activities. The motion-gated sampling algorithm reduces system power consumption by 55% from its active mode while ensuring robust physiological measurements accuracy. Experimental results demonstrate Mean Absolute Errors (MAEs) ranging from 1.5-6.2 BPM (HR) and 0.5-1.0 % (SpO₂) across sitting, standing, walking, and running motions, while maintaining PPG signal-to-noise ratio 10 dB under all evaluated activities. Additionally, integrating an electromagnetic bandgap (EBG) structured metamaterial enhances the on-body antenna's performance and decreases the specific absorption rate (SAR) from 4.36 W/kg to 1.677 W/kg. The proposed MCW system, encapsulated in silicone, provides a compact, energy-efficient platform for reliable long-term wearable cardiovascular monitoring.

PMID:
42546006
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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