Resources

MIMIC III Subset Annotations:

We provide some annotations of the Medical Information Mart for Intensive Care (MIMIC) III waveform database matched Subset here. Details about MIMIC III matched subset can be found on Physionet. More annotations will be added in future.

If you use the annotations, please cite the following paper:

  1. Bashar, S.K., Ding, E., Walkey, A.J., McManus, D.D. and Chon, K.H., 2019. Noise Detection in Electrocardiogram Signals for Intensive Care Unit Patients. IEEE Access7, pp.88357-88368.  (PDF)
  2. S. Bashar, M. B. Hossain, E. Ding, A. Walkey, D. McManus, and K. Chon, “Atrial Fibrillation Detection during Sepsis: Study on MIMIC III ICU Data*,” IEEE Journal of Biomedical and Health Informatics, pp. 1–1, 2020, doi: 10.1109/JBHI.2020.2995139. Download
  3. S. Bashar et al., “Novel Density Poincare Plot Based Machine Learning Method to Detect Atrial Fibrillation from Premature Atrial/Ventricular Contractions,” IEEE Transactions on Biomedical Engineering, pp. 1–1, 2020, doi: 10.1109/TBME.2020.3004310. Download

 

Smartwatch PPG datasets:

UMass Medical School Simband Dataset (Smartwatch PPG Data with Atrial Fibrillation (AF), Premature Atrial Contraction (PAC), Premature Ventricular Contraction (PVC), and Normal Sinus Rhythm (NSR)):

The Simband dataset was collected by our partner at UMass Medical Center.

(Please register a Synapse account, send your Synapse ID and your true name and organization affiliation to Dong Han (dong.han@uconn.edu) if you want to download the dataset. Thank you.)

Please cite possible papers for using our UMass Simband data:

  1. 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
  2. D. Han et al., “Premature Atrial and Ventricular Contraction Detection using Photoplethysmographic Data from a Smartwatch,” Sensors, vol. 20, no. 19, Art. no. 19, Jan. 2020, doi: 10.3390/s20195683. Download

Selected MIMIC III Dataset (Finger Tips Pulse Oximetry PPG Data with AF, PAC/PVC, and NSR):

The MIMIC III dataset that we selected and used in our paper (ID: syn25005553):

(Please register a Synapse account, send your Synapse ID and your true name and organization affiliation to Dong Han (dong.han@uconn.edu) if you want to download the dataset. Thank you.)

Please cite possible papers for using our UMass Simband data:

  1. S. Bashar, M. B. Hossain, E. Ding, A. Walkey, D. McManus, and K. Chon, “Atrial Fibrillation Detection during Sepsis: Study on MIMIC III ICU Data*,” IEEE Journal of Biomedical and Health Informatics, pp. 1–1, 2020, doi: 10.1109/JBHI.2020.2995139. Download
  2. Bashar, S.K., Ding, E., Walkey, A.J., McManus, D.D. and Chon, K.H., 2019. Noise Detection in Electrocardiogram Signals for Intensive Care Unit Patients. IEEE Access7, pp.88357-88368.  (PDF)

 

 

Implementation of comparison PPG peak detection algorithms:

If you used our implementation code in https://github.com/Cassey2016/PPG_Peak_Detection, please cite our paper:

Han, Dong, Syed K. Bashar, Jesús Lázaro, Fahimeh Mohagheghian, Andrew Peitzsch, Nishat Nishita, Eric Ding, Emily L. Dickson, Danielle DiMezza, Jessica Scott, Cody Whitcomb, Timothy P. Fitzgibbons, David D. McManus, and Ki H. Chon. 2022. "A Real-Time PPG Peak Detection Method for Accurate Determination of Heart Rate during Sinus Rhythm and Cardiac Arrhythmia" Biosensors 12, no. 2: 82. https://doi.org/10.3390/bios12020082