Skip to contentMasud Rabbani
CV
Menu

Conference articles · 2023

Predicting and Classifying Heart Rates Using Instantaneous Video Data

Paramita Basak Upama, Masud Rabbani, Kazi Shafiul Alam, Lin He, Shiyu Tian, Mohammad Syam, Iysa Iqbal, Anushka Kolli, Hansika Kolli, Syeda Shefa, Bipasha Sobhani, Sheikh Iqbal Ahamed

2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC) · Pages 1076–1083

Abstract

Heart Rate (HR) and Heart Rate Variability (HRV) is an essential measurement to know the heart’s cardiovascular condition. Many works have been done for measuring HR-HRV based on the facial video non-invasively. In this paper, based on our previous work experience of measuring HR-HRV by Remote photoplethysmography signals (rPPG) analysis, we have built a prediction model from the 10-second time series data extracted from a facial video. In this work, we have used the instantaneous public dataset with several data models to predict the HR-HRV, and stress levels exclusively from the dataset. We have used here some of the popular algorithms appropriate for this task. We have also analyzed the stress level classification on the gender of a subject using the same facial videos with 16 different classifiers resulting in almost perfect accuracy for several classifiers.

Publication details

Category
Conference articles
Authors & affiliations
  1. Paramita Basak UpamaUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  2. Masud RabbaniUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  3. Kazi Shafiul AlamUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  4. Lin HeUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  5. Shiyu TianUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  6. Mohammad SyamUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  7. Iysa IqbalUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  8. Anushka KolliUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  9. Hansika KolliUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  10. Syeda ShefaUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  11. Bipasha SobhaniUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
  12. Sheikh Iqbal AhamedUbicomp Lab, Department of Computer Science, Marquette University, Milwaukee, WI, USA
Venue
2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)
Publisher
IEEE
Record
Pages 1076–1083
Published
2023
Cite this work

Paramita Basak Upama, Masud Rabbani, Kazi Shafiul Alam, Lin He, Shiyu Tian, Mohammad Syam, Iysa Iqbal, Anushka Kolli, Hansika Kolli, Syeda Shefa, Bipasha Sobhani, Sheikh Iqbal Ahamed. “Predicting and Classifying Heart Rates Using Instantaneous Video Data”. 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), 1076–1083. (2023). https://doi.org/10.1109/COMPSAC57700.2023.00163.

Download BibTeXDownload RIS

Research topics

  • Predicting heart rate
  • Time series analysis
  • Detection and Record Electronically Acceptable Medical Data (dDream)
  • Autoregressive integrated moving average (ARIMA)
  • Exponential Triple Smoothing (ETS)
  • heart-rate prediction
  • video photoplethysmography
  • remote PPG
  • cardiovascular monitoring
  • non-contact sensing
  • machine learning