ECG and GSR measure and analysis using wearable systems: Application in anorexia nervosa adolescents

The objective of this study was to test the feasibility of using wearable sensors and wireless technology to measure the autonomic function and stress level in the ambulatory setting. Autonomic function was studied acquiring ECG tracings by means of a wearable sensorized chest strap. Galvanic skin response (GSR) was measured as an indicator of stress level by two electrodes positioned on the palm of the non dominant hand and a wireless acquisition module in a wrist support. Data were acquired in a group of young adolescents with anorexia nervosa (AN) as compared to controls in resting conditions. From ECG the tachogram, the mean RR intervals (meanRR), the root mean square of successive differences (RMSSD) the power of low frequency (LF) and high frequency (HF) bands and the LF/HF ratio were assessed. From GSR mean, median, variance, standard deviation, area under the curve of the sampled signal and delta between maximum and minimum conductance values were computed. All AN patients showed reduced HR and increased meanRR and RMSSD. HF increase, LF decrease and LF/HF reduction were suggestive of prevalence of parasympathetic over sympathetic activity. Additionally, AN showed a decreased GSR variance, standard deviation and delta value with respect to controls. The results of this study show that wearable sensors used in this study were feasible, unobtrusive and therefore extremely suitable for young patients providing the means for future monitoring in the home setting which may be preferable in this population burdened by high cardiovascular morbidity and mortality.

[1]  Fabio Galetta,et al.  Heart rate variability and left ventricular diastolic function in anorexia nervosa. , 2003, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[2]  P. Welch The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[3]  M. Gianelli,et al.  Spectral analysis of R-R interval variability by short-term recording in anorexia nervosa , 2002, Eating and weight disorders : EWD.

[4]  K J Rothman,et al.  No Adjustments Are Needed for Multiple Comparisons , 1990, Epidemiology.

[5]  Maria Weis,et al.  Alterations of Autonomic Cardiac Control in Anorexia Nervosa , 1998, Biological Psychiatry.

[6]  Frédéric Costes,et al.  Chronotropic incompetence to exercise separates low body weight from established anorexia nervosa , 2004, Clinical physiology and functional imaging.

[7]  A. Barreto,et al.  Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  P. Caminal,et al.  Adaptive baseline wander removal in the ECG: Comparative analysis with cubic spline technique , 1992, Proceedings Computers in Cardiology.

[9]  Luca Scalfi,et al.  Heart rate variability as a measure of autonomic nervous system function in anorexia nervosa , 1997, Clinical cardiology.

[10]  Paul Poirier,et al.  Resting and ambulatory heart rate variability in chronic anorexia nervosa. , 2004, The American journal of cardiology.

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

[12]  Yang Hao,et al.  Detecting Vital Signs with Wearable Wireless Sensors , 2010, Sensors.

[13]  M. H. Kempski,et al.  Heart rate power spectrum analysis of autonomic dysfunction in adolescents with anorexia nervosa. , 1994, The International journal of eating disorders.

[14]  T. Sakata,et al.  Reduced 24 hour ambulatory blood pressure and abnormal heart rate variability in patients with dysorexia nervosa , 2004, Heart.

[15]  Adrian Burns,et al.  SHIMMER™ – A Wireless Sensor Platform for Noninvasive Biomedical Research , 2010, IEEE Sensors Journal.

[16]  J. Cadzow Maximum Entropy Spectral Analysis , 2006 .

[17]  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 .

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

[19]  N. Lomb Least-squares frequency analysis of unequally spaced data , 1976 .

[20]  M. Kollai,et al.  Cardiac vagal hyperactivity in adolescent anorexia nervosa. , 1994, European heart journal.

[21]  J. Scargle Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data , 1982 .