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.

I. Introduction

The need for development of smart wearable systems has progressively increased in the scientific and industrial world. Smart wearable systems for health monitoring include several devices, both wearable and implantable, and can be classified as sensors and actuators, power supplies and wireless communication networks. Decision support systems, algorithms for data processing, smart fabrics, processing units, software, multimedia devices and user interfaces are also included in this classification.