I am a fourth-year PhD student in Mechanical Engineering at the University of Maryland, College Park advised by Professor Jin-Oh Hahn. Previously, I completed my BS in Energy and Environment System Engineering at Zhejiang University and my MS in Mechanical Engineering at Tennessee State University. And I have worked as Mechanical Engineer in manufacturing industry for 4 years before starting my PhD journey.
My research interests span multimodal physiological signal analysis, state-space modeling, closed-loop control, and machine learning, with hands-on experience in 3D modeling and manufacturing.
Non-Pharmacological Mitigation of Acute Mental Stress-Induced Sympathetic Arousal:
Comparison Between Median Nerve Stimulation and Auricular Vagus Nerve Stimulation
Sensors 2025, 25(5), 1371.
This paper comparatively investigated Median nerve stimulation (MNS) and auricular vagus nerve stimulation (AVNS)
in terms of efficacy and mechanism of action in the context of mitigating acute stress-induced arousal. The findings may
support future device development for addressing acute mental stress-induced arousal through MNS or AVNS,
and they pave the way toward a better understanding of how to quantify the efficacy of such interventions.
Yuanyuan Zhou,
Sina Masoumi Shahrbabak,
Rayan Bahrami,
Farhan N. Rahman,
Jesus Antonio Sanchez-Perez,
Asim H. Gazi,
Omer T. Inan,
Jin-Oh Hahn
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A Synthetic Multi-Modal Variable to Capture Cardiovascular Responses to Acute Mental Stress
and Transcutaneous Median Nerve Stimulation
IEEE Transactions on Biomedical Engineering, Volume 72, Issue 1, January 2025, Pages 346 - 357.
We developed a novel synthetic multi-modal variable capable of capturing cardiovascular responses to acute mental stress
and the stress-mitigating effect of transcutaneous median nerve stimulation (TMNS),
as an initial step toward the overarching goal of enabling closed-loop controlled mitigation of the physiological response to acute mental stress.
Yuanyuan Zhou,
Jesse D. Parreira,
Sina Masoumi Shahrbabak,
Jesus Antonio Sanchez-Perez,
Farhan N. Rahman,
Asim H. Gazi,
Omer T. Inan,
Jin-Oh Hahn
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Inference-enabled tracking of acute mental stress via multi-modal wearable
physiological sensing: A proof-of-concept study
Biocybernetics and Biomedical Engineering, Volume 44, Issue 4, October–December 2024, Pages 771-781.
Continuously track acute mental stress by integrating multimodal physiological signals
(ECG, PPG, SCG, BCG, EDA, respiration) to derive interpretable digital signatures and
compute stress probabilities via collective inference, significantly outperforming
traditional univariate approaches in accuracy and confidence.
Yuanyuan Zhou,
Azin S. Mousavi,
Yekanth R. Chalumuri,
Jesse D. Parreira,
Mihir Modak,
Jesus Antonio Sanchez-Perez,
Asim H. Gazi,
Omer T. Inan,
Jin-Oh Hahn
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Sampling Rate Requirement for Accurate Calculation of Heart Rate and its Variability based on the Electrocardiogram
Physiological Measurement, Volume 45, Issue 2, February 2024, 025007.
Develop analytical formulas which can serve as quantitative guidelines for the selection
of the sampling rate for the electrocardiogram (ECG) required to calculate heart rate (HR)
and heart rate variability (HRV) with a desired level of accuracy, for the first time.
Yuanyuan Zhou,
Bryndan Lindsey,
Samantha Snyder,
Elizabeth Bell,
Lucy Reider,
Michael Vignos,
Eyal Bar-Kochba,
Azin Mousavi,
Jesse D. Parreira,
Casey Hanley,
Jae Kun Shim,
Jin-Oh Hahn
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* denotes equal contribution.