Ko Keun Kim

The electrically noncontacting ECG measurement on the toilet seat using the capacitively-coupled insulated electrodes

The studies of ECG measurement on the toilet seat have been performed specifically for the ubiquitous health care. Instead of the mainly used dry electrodes having several problems such as the electrical safety or the environmental stability, we used the capacitively-coupled insulated electrodes, which were composed of the Cu plate and the PTFE film for the measurement. The biosignal sensed with the insulated electrodes was measured through the ultra-high input impedance system including OPA111 having the common mode impedance of 10/sup 14/ /spl Omega/ ft. As the result of measuring the signal, with the electrical ground on the neck or the hand, the R-peaks were detected very positively. However, without the electrical ground on the body, we could detect the heartbeat signal, a land of the motion artifacts by the variation of the blood vessel volume. It seems that this heartbeat signal can be also used as the important parameter like the R-peaks for the HRV (heart rate variability) analysis. In addition, it is thought that, without the directly electrical ground, the R-peak detection will be possible by the improvement of the SNR with the active common canceling system.

Common Mode Noise Cancellation for Electrically Non-Contact ECG Measurement System on a Chair

Electrically non-contact ECG measurement system on a chair can be applied to a number of various fields for continuous health monitoring in daily life. However, the body is floated electrically for this system due to the capacitive electrodes and the floated body is very sensitive to the external noises or motion artifacts which affect the measurement system as the common mode noise. In this paper, the driven-seat-ground circuit similar to the driven-right-leg circuit is proposed to reduce the common mode noise. The analysis of this equivalent circuit is performed and the output signal waveforms are compared between with driven-seat-ground and with capacitive ground. As the results, the driven-seat-ground circuit improves significantly the properties of the fully capacitive ECG measurement system as the negative feedback

Nonintrusive Biological Signal Monitoring in a Car to Evaluate a Driver’s Stress and Health State

Nonintrusive monitoring of a drivers physiological signals was introduced and evaluated in a car as a test of extending the concept of ubiquitous healthcare to vehicles. Electrocardiogram, photoplethysmogram, galvanic skin response, and respiration were measured in the ubiquitous healthcare car (U-car) using nonintrusively installed sensors on the steering wheel, drivers seat, and seat belt. Measured signals were transmitted to the embedded computer via Bluetooth(R) communication and processed. We collected and analyzed physiological signals during driving in order to estimate a drivers stress state while using this system. In order to compare the effect of stress on physical and mental conditions, two categories of stresses were defined. Experimental results show that a drivers physiological signals were measured with acceptable quality for analysis without interrupting driving, and they were changed meaningfully due to elicited stress. This nonintrusive monitoring can be used to evaluate a drivers state of health and stress.

The effect of missing RR-interval data on heart rate variability analysis in the frequency domain

In this study, optimal methods for re-sampling and spectral estimation in frequency-domain heart rate variability (HRV) analysis were investigated through a simulation using artificial RR-interval data. Nearest-neighbour, linear, cubic spline and piecewise cubic Hermite interpolation methods were considered for re-sampling and representative non-parametric, parametric, and uneven approaches were used for spectral estimation. Based on this result, the effects of missing RR-interval data on frequency-domain HRV analysis were observed through the simulation of missing data using real RR-interval tachograms. For this simulation, data including the simulated artefact section (0-100 s) were used; these data were selected randomly from the real RR data obtained from the MIT-BIH normal sinus rhythm RR-interval database. In all, 7182 tachograms of 5 min durations were used for this analysis. The analysis for certain missing data durations is performed by 100 Monte Carlo runs. TF, VLF, LF and HF were estimated as the frequency-domain parameters in each run, and the normalized errors between the data with and without the missing data duration for these parameters were calculated. Rules obtained from the results of these simulations were evaluated with real missing RR-interval data derived from a capacitive-coupled ECG during sleep.

The ECG measurement in the bathtub using the insulated electrodes

The ECG recording in the bathtub was studied using insulated electrode. Prior studies of the ECG recording in the bathtub used conductive electrodes having some problems such as the possibility of the electric shock and sensitivity to contamination of the electrode surfaces. The insulated electrodes were made of copper plate coated with PET film. The electrodes were attached on bathtub at both sides of the chest. High-input-impedance amplifier was designed to amplify ECG signal sensed by insulated electrodes of high impedance. The recorded signals in this study were noisier than those recorded with conventional conductive electrodes. But the R peaks in the recorded signals were large enough to be auto-detected. Further study will improve SNR by reducing of power line noise and common-mode noise.

Enhancing the estimation of blood pressure using pulse arrival time and two confounding factors

A new method of blood pressure (BP) estimation using multiple regression with pulse arrival time (PAT) and two confounding factors was evaluated in clinical and unconstrained monitoring situations. For the first analysis with clinical data, electrocardiogram (ECG), photoplethysmogram (PPG) and invasive BP signals were obtained by a conventional patient monitoring device during surgery. In the second analysis, ECG, PPG and non-invasive BP were measured using systems developed to obtain data under conditions in which the subject was not constrained. To enhance the performance of BP estimation methods, heart rate (HR) and arterial stiffness were considered as confounding factors in regression analysis. The PAT and HR were easily extracted from ECG and PPG signals. For arterial stiffness, the duration from the maximum derivative point to the maximum of the dicrotic notch in the PPG signal, a parameter called TDB, was employed. In two experiments that normally cause BP variation, the correlation between measured BP and the estimated BP was investigated. Multiple-regression analysis with the two confounding factors improved correlation coefficients for diastolic blood pressure and systolic blood pressure to acceptable confidence levels, compared to existing methods that consider PAT only. In addition, reproducibility for the proposed method was determined using constructed test sets. Our results demonstrate that non-invasive, non-intrusive BP estimation can be obtained using methods that can be applied in both clinical and daily healthcare situations.

Effect of confounding factors on blood pressure estimation using pulse arrival time

Two confounding factors were selected and analyzed in blood pressure estimation using pulse arrival time (PAT) for each individual. The heart rate was used as the confounding factor for the cardiac cycle, and the duration from the maximum derivative point to the dicrotic peak (TDB) in the photoplethysmogram was used as another confounding factor representing arterial stiffness. By considering these factors with PAT in multiple regression analysis, the performance of blood pressure estimation is enhanced significantly in the diastolic phase as well as in the systolic phase. The reproducibility of this method was also validated with formerly obtained regression equations from the training set. The correlation between estimated and measured blood pressure decreased a little, but the validity was still maintained (r congruent with 0.8). This shows the value of the method in non-intrusive blood pressure estimation for individual patients and may be useful for various applications.

Effect of missing RR-interval data on heart rate variability analysis in the time domain

In this study, the effects of missing RR-interval data on time-domain analysis were investigated using simulated missing data in real RR-interval tachograms and actual missing RR data in an ECG obtained by an unconstrained measurement. For the simulation, randomly selected data (0-100 s) were removed from real RR data obtained from the MIT-BIH normal sinus rhythm database. In all, 2615 tachograms of 5 min durations were used for this analysis. For certain durations of missing data, the analysis was performed by 1000 Monte Carlo runs. MeanNN, SDNN, SDSD, RMSSD and pNN50 were calculated as the time-domain parameters in each run, and the relative errors between the original and the incomplete tachograms for these parameters were computed. The results of the simulation revealed that MeanNN is the parameter most robust to missing data; this feature can be explained by the theory of finite population correction (FPC). pNN50 is the parameter most sensitive to missing data. MeanNN was also found to be the most robust to real missing RR data derived from a capacitive-coupled ECG recorded during sleep; furthermore, the parameter patterns for the missing data were considerably similar to those for the original RR data, although the relative errors may exceed those of the simulation results.

Photoplethysmogram Measurement Without Direct Skin-to-Sensor Contact Using an Adaptive Light Source Intensity Control

We developed a chair-attached, nonintrusive photoplethysmogram (PPG) measuring system for everyday life, unconstrained monitoring using nonskin-contacting sensor-amplifier circuits capable of emitting suitable light intensity adaptable to clothing characteristics. Comparison between proposed and conventional systems showed reasonable correlation and root-mean-squared error levels, indicating its feasibility for unconstrained PPG monitoring.

Ubiquitous House and Unconstrained Monitoring Devices for Home Healthcare System

This paper suggests a healthcare monitoring system using unconstrained measurement devices with ubiquitous techniques. These measurement devices are developed into built-in type and sensor type. The first devices are built-in the households (bed, sofa and toilet seat) and measure the patients heart and respiration activity and estimate a blood pressure. The second devices are placed in a kitchen, front door and every room and detect the patients movements and activities. All digitized raw signals are transmitted to a main PC using Bluetooth wireless network from all ubiquitous devices and sent to hospital laboratory after an analyzing process. This paper suggest ubiquitous healthcare house (u-House) for a practical models of home healthcare system. And it can monitor the patients daily health condition and activity in an unconstrained manner.