Comparison of conductive fabric sensor and Ag-AgCl sensor under motion artifacts

A wearable electrocardiogram(ECG) device using conductive fabric sensor was compared with traditional Ag-AgCl electrode ECG device. The ECG signals were measured under existence of motion artifacts on variable running speed using treadmill to verify that wearable device can substitute traditional ECG device. A signal to noise ratio (SNR) and RR interval were compared between the two devices. The SNR of wearable device was similar or higher than that of clinical device and difference of RR interval was 2ms. The results show that the wearable ECG device using conductive fabric sensor can make similar performance with ECG device using Ag-AgCl electrode even under motion artifacts.

[1]  Seunghwan Kim,et al.  Development and Verification of the System for Heart Rate Detection During Exercise , 2007 .

[2]  Andreas Lymberis,et al.  Current and future R&D activities of the EC-IST programme in eHealth. , 2004, Studies in health technology and informatics.

[3]  S Cerutti,et al.  Heart rate variability as an index of sympathovagal interaction after acute myocardial infarction. , 1987, The American journal of cardiology.

[4]  Fabrice Axisa,et al.  Flexible technologies and smart clothing for citizen medicine, home healthcare, and disease prevention , 2005, IEEE Transactions on Information Technology in Biomedicine.

[5]  Danilo De Rossi,et al.  Electroactive polymer-based devices for e-textiles in biomedicine , 2005, IEEE Transactions on Information Technology in Biomedicine.

[6]  Kinga Howorka,et al.  Functional assessment of heart rate variability: physiological basis and practical applications. , 2002, International journal of cardiology.

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

[8]  A. Folsom,et al.  Low Heart Rate Variability in a 2-Minute Rhythm Strip Predicts Risk of Coronary Heart Disease and Mortality From Several Causes: The ARIC Study , 2000, Circulation.

[9]  Enzo Pasquale Scilingo,et al.  Performance evaluation of sensing fabrics for monitoring physiological and biomechanical variables , 2005, IEEE Transactions on Information Technology in Biomedicine.

[10]  R. Maestri,et al.  Short-Term Heart Rate Variability Strongly Predicts Sudden Cardiac Death in Chronic Heart Failure Patients , 2003, Circulation.

[11]  Mehmet Eren,et al.  Effect of diurnal variability of heart rate on development of arrhythmia in patients with chronic obstructive pulmonary disease. , 2003, International journal of cardiology.

[12]  Rita Paradiso,et al.  A wearable health care system based on knitted integrated sensors , 2005, IEEE Transactions on Information Technology in Biomedicine.

[13]  Mario Mariani,et al.  Alteration of Cardiac Function in Patients with Temporal Lobe Epilepsy: Different Roles of EEG‐ECG Monitoring and Spectral Analysis of RR Variability , 1997, Epilepsia.

[14]  Gregory T. A. Kovacs,et al.  A multiparameter wearable physiologic monitoring system for space and terrestrial applications , 2005, IEEE Transactions on Information Technology in Biomedicine.