Ultra Short Term Analysis of Heart Rate Variability for Monitoring Mental Stress in Mobile Settings

By L. Salahuddin, Jaegeol Cho, M. Jeong, Desok Kim. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007

369 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/6a9b7c1109db9c85456f1a6b215c07869b4b1ae4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. J. Ginsberg
2. Sylvain Laborde
3. Julian F. Thayer
4. E. Mosley
5. Z. J. Lau
6. Tam Pham
7. Shen-Hsing Annabel Chen
8. Dominique Makowski

In Cardiology and Cardiovascular Medicine

1. Z. J. Lau
2. Tam Pham
3. Shen-Hsing Annabel Chen
4. Dominique Makowski
5. J. Ginsberg
6. Sylvain Laborde
7. E. Mosley
8. F. Shaffer

In Cognitive Neuroscience

1. Maja Pantic
2. Thierry Pun
3. Hatice Gunes
4. Mohammad Soleymani
5. Sylvain Laborde
6. E. Mosley
7. Z. J. Lau
8. Tam Pham

Citations in the corpus

• Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting (2017, background): “Furthermore recordings between 10 and 50 s, according to which HRV parameters are considered, have been proven to be reliable under certain conditions (Salahuddin et al., 2007).”
• Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial (2021, background): “Its statistical robustness makes it well-suited for short-term time windows [30,33,49].”
• Emotion representation, analysis and synthesis in continuous space: A survey (2011, background): “, [42]), while on the other hand obtaining a reliable prediction accuracy requires long(er)-term monitoring [76], [77].”
• Categorical and dimensional affect analysis in continuous input: Current trends and future directions (2013, positive): “prediction accuracy requires longer-term monitoring [33,34].”
• Activity-Aware Mental Stress Detection Using Physiological Sensors (2010, methodology): “First, the HRV features that we used in this study can distinguish between stressed and baseline segments using 60-second windows [23].”
• Review on Psychological Stress Detection Using Biosignals (2019, methodology): “Various studies have used this method to induce stress [44, 64, 90, 109, 116, 133, 151, 154, 186, 187, 189, 192, 205, 209, 216, 238].”
• An Overview of Heart Rate Variability Metrics and Norms (2017, background): “(30) obtained 5 min of resting ECG data from 24 healthy students and noted”
• Short-term emotion assessment in a recall paradigm (2009, background): “In (Salahuddin et al., 2007) the authors analyzed the usability of heart rate variability on different time periods and concluded that 50 s of signals are necessary to accurately monitor mental stress in real settings.”