Design and Implementation of Sensing Shirt for Ambulatory Cardiopulmonary Monitoring

Ambulatory monitoring of cardiopulmonary parameters during wake, sleep, and activity states can expand our understanding of health and diseases. In this paper, we present a wearable cardiopulmonary monitoring system called the 'Sensing Shirt'. The Sensing Shirt Consists of a T-shirt with sensors integrated for physiological monitoring, a data acquisition unit (DAQU), and a set of PC-based software. A number of vital signs such as electrocardiogram (ECG), rib cage (RC) and abdominal (AB) respiration. photoplethysmogram (PPG). SpO2, and posture/activities can be acquired by the shirt. The physiological data are stored in a microSD memory card, and then analyzed offline to extract parameters such as heart rate (HR), breathing rate, SpO2, tidal volume (TV), pulse wave transit time (PWTT), and respiratory sinus arrhythmia (RSA). In the Sensing Shirt system, the ECG is acquired by means of active electrodes. PPG and ECG are sampled by one high-speed 16-bit, analog-to-digital converter at 500 Hz for precise PWTT calculation. Technique of pulse amplitude modulation is used for signal conditioning both in respiratory inductive plethysmography and PPG circuits to reduce the power consumption. Powered by 2 AA batteries with 1600 mAh capacity, the whole system can work more than 48 h continuously without interruption. Basic performance tests demonstrate that prototypes of this system can capture ECU RC and AB respiration, and PPG signals effectively, and extract parameters such as HR. breathing rate. SpO2, and TV accurately. This advanced ambulatory monitoring system maybe used in both home healthcare and scientific research.

[1]  I Dotsinsky,et al.  Power-line interference cancellation in ECG signals. , 2005, Biomedical instrumentation & technology.

[2]  Y. Mendelson.  Pulse oximetry: theory and applications for noninvasive monitoring. , 1992, Clinical chemistry.

[3]  Paul Lukowicz,et al.  AMON: a wearable multiparameter medical monitoring and alert system , 2004, IEEE Transactions on Information Technology in Biomedicine.

[4]  M. Goldman,et al.  Comparison of thoracoabdominal calibration methods in normal human subjects. , 1993, Journal of applied physiology.

[5]  A. Nevill,et al.  Validity and reliability of cardiorespiratory measurements recorded by the LifeShirt during exercise tests , 2009, Respiratory Physiology & Neurobiology.

[6]  Frank H Wilhelm,et al.  The LifeShirt , 2003, Behavior modification.

[7]  D. Altman,et al.  STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.

[8]  J. Mead,et al.  Measurement of the separate volume changes of rib cage and abdomen during breathing. , 1967, Journal of applied physiology.

[9]  J R Thompson,et al.  Qualitative diagnostic calibration technique. , 1999, Journal of applied physiology.

[10]  Maria Lindén,et al.  Electrical characteristics of conductive yarns and textile electrodes for medical applications , 2007, Medical & Biological Engineering & Computing.

[11]  Stephen W. Porges,et al.  Methodological issues in the quantification of respiratory sinus arrhythmia , 2007, Biological Psychology.

[12]  F. Martinez,et al.  ATS/ACCP Statement on cardiopulmonary exercise testing. , 2003, American journal of respiratory and critical care medicine.

[13]  Yan Chen,et al.  Continuous and Noninvasive Blood Pressure Measurement: A Novel Modeling Methodology of the Relationship Between Blood Pressure and Pulse Wave Velocity , 2009, Annals of Biomedical Engineering.

[14]  P. Grossman.  The LifeShirt: a multi-function ambulatory system monitoring health, disease, and medical intervention in the real world. , 2004, Studies in health technology and informatics.

[15]  A. Sheel,et al.  Measurement of exercise ventilation by a portable respiratory inductive plethysmograph , 2006, Respiratory Physiology & Neurobiology.

[16]  V. C. Padaki,et al.  Smart Vest: wearable multi-parameter remote physiological monitoring system. , 2008, Medical engineering & physics.

[17]  Patrick Levy,et al.  Pulse transit time improves detection of sleep respiratory events and microarousals in children. , 2005, Chest.

[18]  Wu Jia-lon.  Design of a Wearable Respiratory Inductive Plethysmograph and Its Applications , 2006 .

[19]  Ming-Yie Jan,et al.  EFFECT OF PULSE NUMBER ON THE PULSE-BASED SYNCHRONIZED-AVERAGING ANALYSIS IN LASER DOPPLER SIGNAL , 2007 .

[20]  Dirk Cysarz,et al.  Day-to-night time differences in the relationship between cardiorespiratory coordination and heart rate variability , 2008, Physiological measurement.

[21]  N. Halín,et al.  The LifeShirt system for wireless patient monitoring in the operating room , 2005, Journal of telemedicine and telecare.

[22]  Sundaresan Jayaraman,et al.  e-Health and quality of life: the role of the Wearable Motherboard. , 2004, Studies in health technology and informatics.

[23]  Margaret L Fruin,et al.  Validity of a multi-sensor armband in estimating rest and exercise energy expenditure. , 2004, Medicine and science in sports and exercise.

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

[25]  Frank H Wilhelm,et al.  Adaptive and wavelet filtering methods for improving accuracy of respiratory measurement. , 2005, Biomedical sciences instrumentation.

[26]  P. Bonato.  Clinical applications of wearable technology , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[27]  A. Lymberis,et al.  Smart fabrics and interactive textile enabling wearable personal applications: R&D state of the art and future challenges , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  M. Sackner,et al.  Validation of respiratory inductive plethysmography using different calibration procedures. , 2015, The American review of respiratory disease.

[29]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[30]  A. Murray,et al.  Relation between heart rate and pulse transit time during paced respiration , 2001, Physiological measurement.

[31]  Alexandros Pantelopoulos,et al.  A survey on wearable biosensor systems for health monitoring , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.