A Study of Significant data Classification between EDR extracted and frequency analysis of Heart Rate Variability from ECG using Conductive textile

Abstract

The aim of this study is classification of correlative data through comparison between ECG-Derived Respiration (EDR) and High Frequency (HF) component obtained frequency analysis of heart rate variability (HRV) from ECG using two of conductive textiles. Generally, individual frequency range of the HF component has been determined only by means of distinctive parameters of respiration such as respiratory rate, range and median value of respiratory rate, etc. However, in many cases Low Frequency (LF) components and High Frequency (HF) components may be superimposed on each other totally or particularly and can not be diagnostically estimated because respiratory rhythms are individually much remarkably differentiated. This study, in consequence, analyze frequency component of EDR derived from ECG and then compare with high frequency components of HRV and finally find out valuable data for further analysis. Hardware constitution is used to bed type ECG measurement equipment based on U-Healthcare, can identify user using Radio Frequency (RF) module as well as manage data each of user. We used Frequency Modulation (FM) method based on Respiration Sinus Arrhythmia (RSA) in order to extract EDR from ECG signal. ECG data and EDR data were processed with Lab-VIEW, then classified through each of frequency analysis.