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Updated: Jan 9, 2026

Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
Published on: December 5, 2025
Real-Time, Single-Ear, Wearable ECG Reconstruction, R-Peak Detection, and HR/HRV Monitoring
This study presents a novel ear-worn system for real-time heart rate (HR) and heart rate variability (HRV) monitoring using Electrocardiogram (ECG) signals. The energy-efficient device enables continuous cardiovascular tracking with earbuds.
Area of Science:
- Biomedical Engineering
- Wearable Technology
- Biosignal Processing
Background:
- Continuous biosignal monitoring, particularly heart rate (HR) and heart rate variability (HRV), is crucial for tracking physiological and cognitive states.
- Head-worn devices like earbuds offer potential for improved usability in HR/HRV monitoring, but face challenges with wet electrodes, weak ear signals, and algorithm compatibility.
- Current methods often require invasive or cumbersome setups, limiting widespread adoption for continuous, non-invasive cardiovascular health assessment.
Purpose of the Study:
- To introduce a single-ear wearable system for real-time Electrocardiogram (ECG) parameter estimation on an energy-efficient, embedded device.
- To demonstrate robust extraction of HR and HRV parameters directly on a wearable device using advanced electrode technology and an optimized algorithm.
- To enable continuous, unobtrusive cardiovascular monitoring through everyday head-worn devices.
Main Methods:
- Development of a single-ear wearable system integrating state-of-the-art in-ear electrode technology.
- Implementation of an optimized DeepMF algorithm for Electrocardiogram (ECG) signal processing on the energy-efficient BioGAP device.
- Subject-independent approach for real-time HR and HRV parameter extraction directly on the wearable device.
Main Results:
- The system achieves low energy consumption with only 36.7 uJ/inference for HR/HRV parameter estimation.
- Comparable performance to state-of-the-art architectures with mean errors of 0.49 bpm for HR and 25.82 ms for HRV.
- Estimated battery life of 36 hours with a total system power consumption of 7.6 mW.
Conclusions:
- The developed system enables robust, real-time ECG parameter estimation directly on an ear-worn device, paving the way for continuous cardiovascular monitoring.
- Integration of HR and HRV measurements into everyday devices like earbuds offers significant potential for unobtrusive, at-home cardiovascular health tracking.
- This technology can aid in the early detection of cardiovascular irregularities through continuous, non-invasive monitoring.
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