Journal Articles:

[1]          E. Y. Ding et al., “Accuracy and Usability of a Novel Algorithm for Detection of Irregular Pulse Using a Smartwatch Among Older Adults: Observational Study,” JMIR Cardio, vol. 3, no. 1, p. e13850, 2019. Download

[2]          H. F. Posada-Quintero, T. Dimitrov, A. Moutran, S. Park, and K. H. Chon, “Analysis of Reproducibility of Noninvasive Measures of Sympathetic Autonomic Control Based on Electrodermal Activity and Heart Rate Variability,” IEEE Access, vol. 7, pp. 22523–22531, 2019. Download

[3]          S. K. Sinha et al., “Graphene and Poly(3,4-ethylene dioxythiophene):Poly(4-styrenesulfonate) on Nonwoven Fabric as a Room Temperature Metal and Its Application as Dry Electrodes for Electrocardiography,” ACS Appl. Mater. Interfaces, Aug. 2019. Download

[4]          S. K. Bashar, E. Ding, A. J. Walkey, D. D. McManus, and K. H. Chon, “Noise Detection in Electrocardiogram Signals for Intensive Care Unit Patients,” IEEE Access, vol. 7, pp. 88357–88368, 2019. Download

[5]          E. Y. Ding et al., “Novel Method of Atrial Fibrillation Case Identification and Burden Estimation Using the MIMIC-III Electronic Health Data Set,” J Intensive Care Med, vol. 34, no. 10, pp. 851–857, Oct. 2019. Download

[6]          J. Harvey, S. M. A. Salehizadeh, Y. Mendelson, and K. H. Chon, “OxiMA: A Frequency-Domain Approach to Address Motion Artifacts in Photoplethysmograms for Improved Estimation of Arterial Oxygen Saturation and Pulse Rate,” IEEE Trans Biomed Eng, vol. 66, no. 2, pp. 311–318, 2019. Download

[7]          S. K. Bashar, Y. Noh, A. J. Walkey, D. D. McManus, and K. H. Chon, “VERB: VFCDM-Based Electrocardiogram Reconstruction and Beat Detection Algorithm,” IEEE Access, vol. 7, pp. 13856–13866, 2019. Download

[8]          S. K. Bashar et al., “Atrial Fibrillation Detection from Wrist Photoplethysmography Signals Using Smartwatches,” Sci Rep, vol. 9, no. 1, pp. 1–10, Oct. 2019. Download Dataset

[9]          Y. Kong and K. H. Chon, “Heart Rate Tracking Using a Wearable Photoplethysmographic Sensor During Treadmill Exercise,” IEEE Access, vol. 7, pp. 152421–152428, 2019. Download

[10]        M. B. Hossain, S. K. Bashar, A. J. Walkey, D. D. McManus, and K. H. Chon, “An Accurate QRS Complex and P Wave Detection in ECG Signals Using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Approach,” IEEE Access, vol. 7, pp. 128869–128880, 2019. Download

[11]        H. F. Posada-Quintero, N. Reljin, J. B. Bolkhovsky, A. D. Orjuela-Cañón, and K. H. Chon, “Brain Activity Correlates With Cognitive Performance Deterioration During Sleep Deprivation,” Front. Neurosci., vol. 13, 2019. Download

[12]        N. Bosch et al., “New-Onset Atrial Fibrillation as a Sepsis Defining Organ Failure,” in D104. CRITICAL CARE: A FINE BALANCE – SEPSIS DEFINITIONS, OUTCOMES AND EPIDEMIOLOGY, 296 vols., American Thoracic Society, 2019, pp. A7164–A7164. Download

[13]        H. F. Posada-Quintero et al., “Mild Dehydration Identification Using Machine Learning to Assess Autonomic Responses to Cognitive Stress,” Nutrients, vol. 12, no. 1, p. 42, Jan. 2020, doi: 10.3390/nu12010042. Download

[14]        H. F. Posada-Quintero and J. B. Bolkhovsky, “Machine Learning models for the Identification of Cognitive Tasks using Autonomic Reactions from Heart Rate Variability and Electrodermal Activity,” Behavioral Sciences, vol. 9, no. 4, p. 45, Apr. 2019, doi: 10.3390/bs9040045. Download

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