Wearable ECG recorder with acceleration sensors for measuring daily stress

A small and light-weight wearable electrocardiograph (ECG) equipment with three accelerometers (x, y and zaxis) was developed for prolonged monitoring of autonomic nervous system in daily life. It consists of an amplifier, a bandpass filter, a microcomputer with an AD converter, a triaxial accelerometer, and a memory card. Four parameters can be sampled at 1 kHz (10 bits) for more than 24 hours, maximum 27 hours, with a default battery and a memory card (1 GB). The availability of the system was tested for three subjects for three days by replacing the battery and the memory card every 24 hours under each environment. Both short-term and circadian rhythms of the autonomic nervous system were clearly observed. The change of the autonomic nervous system from body movement (i.e. walking or turning over) was observed by check acceleration data. The feasibility of the application in clinical practice is also discussed.

[1]  R. Roine,et al.  Arrhythmias and heart rate variability during and after therapeutic hypothermia for cardiac arrest* , 2009, Critical care medicine.

[2]  J E Schwartz,et al.  Environmental influences on blood pressure and the role of job strain. , 1996, Journal of hypertension. Supplement : official journal of the International Society of Hypertension.

[3]  W.J. Tompkins,et al.  Neural-network-based adaptive matched filtering for QRS detection , 1992, IEEE Transactions on Biomedical Engineering.

[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]  Y. Tsuda,et al.  Shift work modifies the circadian patterns of heart rate variability in nurses. , 2001, International journal of cardiology.

[6]  H Kobayashi,et al.  Heart rate variability; an index for monitoring and analyzing human autonomic activities. , 1999, Applied human science : journal of physiological anthropology.

[7]  Piotr Augustyniak Wearable wireless heart rate monitor for continuous long-term variability studies. , 2011, Journal of electrocardiology.

[8]  Giuseppe Baselli,et al.  The influence of exercise intensity on the power spectrum of heart rate variability , 2004, European Journal of Applied Physiology and Occupational Physiology.

[9]  V. Vuksanović,et al.  Heart rate variability in mental stress aloud. , 2007, Medical engineering & physics.

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

[11]  T Moritani,et al.  Tone-entropy analysis on cardiac recovery after dynamic exercise. , 1997, Journal of applied physiology.

[12]  M. Kumari,et al.  Psychophysiological biomarkers of workplace stressors , 2010, Neuroscience & Biobehavioral Reviews.

[13]  Weidong Wang,et al.  Design and Implementation of Sensing Shirt for Ambulatory Cardiopulmonary Monitoring , 2011 .

[14]  Marimuthu Palaniswami,et al.  Association of cardiac autonomic neuropathy with alteration of sympatho-vagal balance through heart rate variability analysis. , 2010, Medical engineering & physics.

[15]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[16]  Seunghwan Kim,et al.  Performance study of the wearable one-lead wireless electrocardiographic monitoring system. , 2009, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[17]  L. G. Sison,et al.  Adaptive noise cancelling of motion artifact in stress ECG signals using accelerometer , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.

[18]  David M Almeida,et al.  Frontiers in the use of biomarkers of health in research on stress and aging. , 2010, The journals of gerontology. Series B, Psychological sciences and social sciences.

[19]  R. Fensli,et al.  A wireless ECG system for continuous event recording and communication to a clinical alarm station , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[20]  S. Malpas Neural influences on cardiovascular variability: possibilities and pitfalls. , 2002, American journal of physiology. Heart and circulatory physiology.

[21]  Wan-Young Chung,et al.  Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring , 2009 .

[22]  Jan H. Houtveen,et al.  Circadian variation in base rate measures of cardiac autonomic activity , 2004, European Journal of Applied Physiology.

[23]  B. Kudielka,et al.  Salivary cortisol as a biomarker in stress research , 2009, Psychoneuroendocrinology.

[24]  A. Porta,et al.  Heart rate variability explored in the frequency domain: A tool to investigate the link between heart and behavior , 2009, Neuroscience & Biobehavioral Reviews.

[25]  Kang-Ming Chang,et al.  Wireless portable electrocardiogram and a tri-axis accelerometer implementation and application on sleep activity monitoring. , 2011, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[26]  Akinori Nakata,et al.  Job stress, social support, and prevalence of insomnia in a population of Japanese daytime workers. , 2004, Social science & medicine.

[27]  A. Schwerdtfeger,et al.  Social interaction moderates the relationship between depressive mood and heart rate variability: evidence from an ambulatory monitoring study. , 2009, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[28]  Toshio Moritani,et al.  A comparative scale of autonomic function with age through the tone-entropy analysis on heart period variation , 2006, European Journal of Applied Physiology.

[29]  Gianfranco Parati,et al.  Variables influencing heart rate. , 2009, Progress in cardiovascular diseases.

[30]  Tokio Yamaguchi,et al.  Psychological stress increases bilirubin metabolites in human urine. , 2002, Biochemical and biophysical research communications.