Farnoush Baghestani

Biomedical Engineering

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Farnoush Baghestani

Ph.D. Student, Biomedical Engineering
University of Connecticut

I am a Ph.D. student in Biomedical Engineering and an M.S. student in Electrical Engineering at the University of Connecticut, where I focus on biomedical signal processing and machine learning applications in physiological monitoring. My research centers on analyzing skin sympathetic nerve activity (SKNA) using advanced signal processing techniques, with a particular emphasis on improving noise removal and evaluating autonomic nervous system responses under stress, pain, and clinical interventions.

I have several years of experience working with physiological time-series data, combining classical signal processing methods with deep learning approaches such as convolutional autoencoders and LSTM networks. My work has contributed to developing novel biomarkers for sympathetic activity, improving SKNA signal quality in noisy conditions, and comparing SKNA with electrodermal activity (EDA) in both experimental and clinical settings.

Beyond my academic research, I collaborate with clinical teams at Hartford Hospital, working on SKNA and ECG data from ICU patients undergoing Stellate Ganglion Block procedures. I have also contributed to research in EEG signal analysis, blood glucose estimation from PPG, and brain-computer interfaces.

Education

• Ph.D. Biomedical Engineering, University of Connecticut (in progress)
• M.Sc. Electrical Engineering, University of Connecticut
• B.Sc. Electrical Engineering, University of Tehran

Research Interests

• Biomedical signal processing
• Autonomic nervous system and SKNA analysis
• Machine learning and deep learning for physiological data
• Wearable and digital health technologies

Selected Publications

• Baghestani F., Kong Y., Chen I.P., D’Angelo W., Chon K.H. Detecting Sympathetic Discharges: Comparison of Electrodermal Activity and Skin Sympathetic Nerve Activity in Stimulation-to-Response Time and Recovery Time to Baseline. IEEE Transactions on Affective Computing, 2025.
• Baghestani F., Kong Y., D’Angelo W., Chon K.H. Analysis of sympathetic responses to cognitive stress and pain through skin sympathetic nerve activity and electrodermal activity. Computers in Biology and Medicine, 2024.
• Baghestani F., MPS Nejad, Kong Y., Chon K.H. Towards Continuous Skin Sympathetic Nerve Activity Monitoring: Removing Muscle Noise. 2024 IEEE 20th International Conference on Body Sensor Networks (BSN), 1–4.

See full list on Google Scholar

Awards and Honors

• First place, UConn Get Seeded (2024)
• Third place, InnovateHealth PitchFest (2024)
• Best Paper Award (Third Place), IEEE BSN Conference (2023)

Professional Profiles

• Google Scholar
• LinkedIn
• Email: farnoushbaghestani@gmail.com