Wearable biomonitoring system for stress management: A preliminary study on robust ECG signal processing

There is a close correlation between stress and health risk factors such as poor immune function and cardiovascular problems. Various researches showed that long-term exposure to stress and its related diseases are responsible of dramatic increase of mortality in theWestern Countries. In this context, the European Collaborative Project INTERSTRESS is aimed at designing and developing advanced simulation and sensing technologies for the assessment and treatment of psychological stress, based on mobile biosensors. In this paper a wearable system able to implement the acquisition and the real-time elaboration of the ECG signal for stress management purposes will be described. A novel and robust algorithm for QRS complex detection has been developed. Robust QRS detection is fundamental to evaluate Heart Rate and Heart Rate Variability that are relevant parameters used as quantitative marker related to mental stress. In comparison to existing solutions the realized algorithm presents many advantages: an adaptive optimal filtering technique that avoids the use of thresholds and empirical rules for R peaks detection, low computational cost for real time elaboration and good tollerance with noisy ECG signal.

[1]  S Cerutti,et al.  Sympathovagal interaction during mental stress. A study using spectral analysis of heart rate variability in healthy control subjects and patients with a prior myocardial infarction. , 1991, Circulation.

[2]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[3]  T. Pickering,et al.  Mental stress as a causal factor in the development of hypertension and cardiovascular disease , 2001, Current hypertension reports.

[4]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[5]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[6]  A. Malliani,et al.  Cardiovascular Neural Regulation Explored in the Frequency Domain , 1991, Circulation.

[7]  Shankar Muthu Krishnan,et al.  ECG signal conditioning by morphological filtering , 2002, Comput. Biol. Medicine.

[8]  S. Segerstrom,et al.  Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. , 2004, Psychological bulletin.

[9]  Marcello Ferro,et al.  Interreality: The use of advanced technologies in the assessment and treatment of psychological stress , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[10]  B. McEwen Protective and damaging effects of stress mediators. , 1998, The New England journal of medicine.

[11]  Szi-Wen Chen,et al.  A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising , 2006, Comput. Methods Programs Biomed..

[12]  K. H. Kim,et al.  Emotion recognition system using short-term monitoring of physiological signals , 2004, Medical and Biological Engineering and Computing.

[13]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[14]  R. Cohen,et al.  Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. , 1981, Science.

[15]  S Cerutti,et al.  Individual recognition by heart rate variability of two different autonomic profiles related to posture. , 1997, Circulation.

[16]  S. Suppappola,et al.  Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis , 1994, IEEE Transactions on Biomedical Engineering.

[17]  D.S. Benitez,et al.  A new QRS detection algorithm based on the Hilbert transform , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[18]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.