3 citations · 7 across the 6 of their papers we have counts for
6 papers
Deep Learning Approaches for Sleep Apnea Classification from Polysomnographic EEG Signals
Shashank Manjunath, Mukesh Cheemakurthi, Aarti Sathyanarayana
Sleep apnea diagnosis via polysomnography remains resource intensive and relies on time consuming manual data analysis and scoring. Recent work has demonstrated that central nervou…
Beyond Motion Artifacts: Optimizing PPG Preprocessing for Accurate Pulse Rate Variability Estimation
Yuna Watanabe, Natasha Yamane, Aarti Sathyanarayana +2
Wearable physiological monitors are ubiquitous, and photoplethysmography (PPG) is the standard low-cost sensor for measuring cardiac activity. Metrics such as inter-beat interval (…
Extending Stress Detection Reproducibility to Consumer Wearable Sensors
Ohida Binte Amin, Varun Mishra, Tinashe M. Tapera +2
Wearable sensors are widely used to collect physiological data and develop stress detection models. However, most studies focus on a single dataset, rarely evaluating model reprodu…
Sleep Staging from Airflow Signals Using Fourier Approximations of Persistence Curves
Shashank Manjunath, Hau-Tieng Wu, Aarti Sathyanarayana
Sleep staging is a challenging task, typically manually performed by sleep technologists based on electroencephalogram and other biosignals of patients taken during overnight sleep…
Detection of Sleep Oxygen Desaturations from Electroencephalogram Signals
Shashank Manjunath, Aarti Sathyanarayana
In this work, we leverage machine learning techniques to identify potential biomarkers of oxygen desaturation during sleep exclusively from electroencephalogram (EEG) signals in pe…
Topological Data Analysis of Electroencephalogram Signals for Pediatric Obstructive Sleep Apnea
Shashank Manjunath, Jose A. Perea, Aarti Sathyanarayana
Topological data analysis (TDA) is an emerging technique for biological signal processing. TDA leverages the invariant topological features of signals in a metric space for robust…