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Memory-Efficient EDA Denoising via Knowledge Distillation for Wearable IoT Under Severe Motion Artifacts and Underwater Conditions
Yongbin Lee, Andrew Peitzsch, Youngsun Kong +4
Electrodermal activity (EDA) is widely used in wearable Internet of Medical Things (IoMT) systems for continuous health monitoring, including autonomic assessment. However, EDA sig…
Feasibility of Extracting Skin Nerve Activity from Electrocardiogram Recorded at A Low Sampling Frequency
Youngsun Kong, Farnoush Baghestani, I-Ping Chen +1
Skin nerve activity (SKNA) derived from electrocardiogram (ECG) signals has been a promising non-invasive surrogate for accurate and effective assessment of the sympathetic nervous…
A New Approach to Characterize Dynamics of ECG-Derived Skin Nerve Activity via Time-Varying Spectral Analysis
Youngsun Kong, Farnoush Baghestani, William D'Angelo +2
Assessment of the sympathetic nervous system (SNS) is one of the major approaches for studying affective states. Skin nerve activity (SKNA) derived from high-frequency components o…
A Preliminary Study on Automatic Motion Artifacts Detection in Electrodermal Activity Data Using Machine Learning
Md Billal Hossain, Hugo Fernando Posada-Quintero, Youngsun Kong +2
The electrodermal activity (EDA) signal is a sensitive and non-invasive surrogate measure of sympathetic function. Use of EDA has increased in popularity in recent years for such a…