• Science of Emotion and Sensibility
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• v.18 no.2
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• pp.19-30
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• 2015

The healing effect of the aroma treated fabrics with lavender and lemon aromas was investigated by assessing the autonomic nervous responses of human body. For this cause Lemon and lavender microcapsules were coated on a cotton fabric using a water-based acrylic binder, respectively. And the study created a total of four aroma treated fabrics at a concentration of 2% and 5% respectively. Electrocardiogram(ECG), skin conductance, and Blood flow, of ten participants were measured for 30 sec at a stable condition, at a stress status (working memory task), and at a stimulation status (after rubbing aroma treated fabrics). Subjective sensibilities of the aromas were also evaluated. With regard to the responses of the autonomic nervous system, in order to understand how the values gained after the normalization process would cause different physiological signals between the stable state and the aroma-stimulated state as well as between the stress state and the aroma-stimulated state, the study conducted a non-parametric test, friedman test as well and analyzed tendencies. LF/HF turned out to be significantly different to the stress state, and according to the results of the post-hoc comparison, lemon 5% presented statistically significant differences among the lavender 2%, lavender5%, lemon2%. Lemon 5% stimuli increased stress but stimuli consisting of the lavender 2%, the lavender 5% and the lemon 2% decreased stress because of a psychological rest. And the stimuli of the lavender 2%, the lavender 5%, the lemon 2% presented a healing effect in this research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2105-2112
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• 2010

The noise component of electrocardiogram is not distributed in a certain frequency band. It is expressed in various types of signals by rater's physical and environmental conditions. Particularly, since the baseline wander is occurred by the mixture of the original signal and 0 ~ 2 [Hz] range of the frequency components according to muscle constraction of part attaching to an electrode and respiration rythm, it makes the ECG signal analysis difficult. Several methods have been proposed to eliminate the wandering effectually. However, they have some problems. In some methods, the high processing time is required due to the computational complexity, while in other cases ECG signal morphology can be distorted. This paper suggests a simple and effective algorithm that eliminates baseline wander with low computational complexity and without distorting signal morphology. First, the algorithm detects and segments a baseline wandering interval using slope analysis and curve point detection, second, approximates the wandering in the interval as a sinusoid, and then subtracts the sinusoid from signal. Finally, ecg signals without baseline wander are obtained. In order to evaluate the performance of the algorithm, several ECG signals with baseline wandering in MIT/BIH ECG database 101, 111, 113, 234 record were chosen and applied to the algorithm. It is found that the algorithm removes baseline wanders effectively without significant morphological distortion.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.

• Journal of IKEEE
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• v.13 no.1
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• pp.77-86
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• 2009

A wavelet Electrocardiogram(ECG) detector and its analog-to-digital converter(ADC) for low-power implantable cardiac pacemakers are presented in this paper. The proposed wavelet-based ECG detector consists of a wavelet decomposer with wavelet filter banks, a QRS complex detector of hypothesis testing with wavelet-demodulated ECG signals, and a noise detector with zero-crossing points. To achieve high-detection performance with low-power consumption, the multi-scaled product algorithm and soft-threshold algorithm are efficiently exploited. To further reduce the power dissipation, a low-power ADC, which is based on a Successive Approximation Register(SAR) architecture with an on/off-time controlled comparator and passive sample and hold, is also presented. Our algorithmic and architectural level approaches are implemented and fabricated in standard $0.35{\mu}m$ CMOS technology. The testchip shows a good detection accuracy of 99.32% and very low-power consumption of $19.02{\mu}W$ with 3-V supply voltage.

• Fashion & Textile Research Journal
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• v.22 no.3
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• pp.386-398
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• 2020

This study compared dip-coating and in situ polymerization methods for the development of nanofiber-based E-textile using polypyrrole. Nanofiber webs were fabricated by electrospinning an aqueous poly (vinyl alcohol) (PVA) solution. Subsequently, the PVA nanofiber web underwent thermal treatment to improve water resistance. Dip-coating and in situ polymerization methods were used to deposit polypyrrole on the surfaces of the nanofiber web. An FE-SEM analysis was also conducted to examine specimen surface characteristics along with EDS and FT-IR that analyzed the chemical bonding between polypyrrole and specimens. The line resistance and sheet resistance of the treated specimens were measured. Finally, an electrocardiogram (ECG) was measured with textile sensors made of the polypyrrole-deposited PVA nanofiber webs. The polypyrrole-deposited PVA nanofiber webs fabricated by dip-coating dissolved in the dip-coating solution and indicated damage to the nanofibers. However, in the case of in situ polymerization, polypyrrole nanoparticles were deposited on the surface and inter-web structure of the PVA nanofiber web. The resistance measurements indicated that polypyrrole-deposited PVA nanofiber webs fabricated by in situ polymerization with an average sheet resistance of 5.3 k(Ω/□). Polypyrrole-deposited PVA nanofiber webs fabricated by dip-coating showed an average sheet resistance of 57.3 k(Ω/□). Polypyrrole-deposited PVA nanofibers fabricated by in situ polymerization showed a lower line and sheet resistance; in addition, they detected the electrical activity of the heart during ECG measurements. The electrodes made from polypyrrole-deposited PVA nanofiber webs by in situ polymerization showed the best performance for sensing ECG signals among the evaluated specimens.

• Science of Emotion and Sensibility
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• v.6 no.2
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• pp.21-28
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• 2003

Tn the present study, 9 photographs from the International Affective Picture System (IAPS) judged to express best 2-dimensional sensibility were selected and used to stimulate the subjects. The goal of the study lay in verifying whether or not the consequent affective changes in the subjects can be discriminated psychologically and physiologically in terms of arousal and relaxation. In order to determine affective changes, the physiological signals of the subjects' autonomic nervous system were measured through electrocardiogram (ECG) , galvanic skin response (GSR), skin temperature, and respiration. After stimulation and measurement, subjective evaluation was conducted. Subjective evaluation revealed that affective arousal level could be classified into 4 consecutive stages: arousal 〉 unpleasant arousal, pleasant arousal 〉 comfort 〉 relaxation. Analysis revealed that the responses of the autonomic nervous system, too, could be classified into 3 consecutive stages: arousal, unpleasant arousal, pleasant arousal 〉 comfort 〉 relaxation. By selecting and using 9 photographs from the IAPS deemed best to express Koreans'2-dimensional sensibility, the present study confirmed that it is possible to discriminate changes in the subjects' affective arousal level in terms of arousal and relaxation through psychological and physiological evaluation.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.10
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• pp.1665-1672
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• 2009

This study examines the comfort of outdoorwear by electrocardiogram (ECG) and electroencephalogram (EEG) analyses. An experiment that consisted of rest (30 min), exercise (30 min), and recovery (20 min) periods was administered in a climate chamber with 10 healthy male participants. Two kinds of outdoorwear made of 100% cotton fabrics ('Control') and specially engineered fabrics having the feature of quick sweat absorbency and high speed drying fabric ('Functional') are evaluated in the experiment. ECG and EEG signals were obtained during the rest and recovery periods for the two outdoorwear conditions. The ECG analysis identified a smaller decrement of high frequency (HF) power for the 'Functional' when compared with the 'Control' during the recovery period. Next, the EEG analysis showed that the relative band powers of slow $\alpha$ and mid $\alpha$ increased for the 'Functional' while they decreased for the 'Control' and that the ratio of $\alpha$ power to high $\beta$ power was higher for the 'Functional'. The evaluation results indicate that the participants could remain relaxed more with less stress while wearing the functional outdoorwear that demonstrated the positive effects on autonomic nervous system (ANS) activities. The present study is significant in regard that use of ECG and EEG for the assessment of wear comfort is the first in the field of clothing and textile.

• Journal of Sensor Science and Technology
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• v.17 no.2
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• pp.87-94
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• 2008

Blood pressure (BP), one of the most important vital signs, is used to identify an emergency state and reflects the blood flow characteristics of the cardiovascular system. The conventional noninvasive method of measuring BP is inconvenient because patients must wear a cuff on their arm and the measurement process takes time. This paper proposes an algorithm for estimating the BP using the pulse transit time (PTT) of the photoplethysmography (PPG) and pressure pulse from finger at the same time as a more convenient way to measure the BP. After recording the electrocardiogram (ECG), measuring the pressure pulse, and performing PPG, we calculated the PTT from the acquired signals. Then, we used a multiple regression analysis to measure the systolic and diastolic BP indirectly. Comparing the BP measured indirectly using the proposed algorithm and the real BP measured with a sphygmomanometer, the systolic pressure had a mean error of ${\pm}3.240$ mmHg and a standard deviation of 2.530 mmHg, while the diastolic pressure had a satisfactory result, i.e., a mean error of ${\pm}1.807$ mmHg and a standard deviation of 1.396 mmHg. These results are more superior than existing method estimating blood pressure using the one PTT and satisfy the ANSI/AAMI regulations for certifying a sphygmomanometer i.e., the measurement error should be within a mean error of ${\pm}5$ mmHg and a standard deviation of 8 mmHg. These results suggest the possibility of applying our method to a portable, long-term BP monitoring system.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.419-426
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• 2008

In order to develop "textile electrode - sensing clothing" which is a sort of smart clothing to measure electric activities of heart, we propose possible ways to develop textile electrode and design of sensing clothing, ultimately aiming to develop "ECG sensing clothing for lifestyle monitoring". Conventional sensors for measuring typical electric activities of heart keep certain distance between measuring electrodes to measure signals for electric activities of heart, but these sensors often cause inappropriate factors (e.g. motional artifacts, inconvenience of use, etc) for monitoring natural cardiac activities in our daily life. In addition, most of textile electrodes have made it difficult to collect data due to high impedance and unstable contact between skin and electrodes. To overcome these questions, we minimized distance between electrodes and skin to maximize convenience of use. And in order to complement contact between skin electrodes, we modified textile electrode's form and developed ways to design clothing. As a result, we could find out clinical significance by investigating possible associations of clinical electrocardiogram (ECG) with variation of distance between electrodes, and could also demonstrate clinically significant associations between textile electrode developed herein and clothing.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.200-207
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• 2014

Arrhythmia electrocardiogram signal contains a specific unusual heartbeat with abnormal morphology. Because unusual heartbeat is useful for diagnosis and classification of various diseases, such as arrhythmia, detection of unusual heartbeat from the arrhythmic ECG signal is very important. Amplitude and kurtosis at R-peak point and RR interval are characteristics of ECG signal on R-wave. In this paper, we provide a method for detecting unusual heartbeat based on these. Through the value of the attribute deviates more from the average value if unusual heartbeat is more certainly, the proposed method detects unusual heartbeat in order using the mean and standard deviation. From 15 ECG signals of MIT-BIH arrhythmia database which has R-wave distortion, we compare the result of conventional method which uses the fixed threshold value and the result of proposed method. Throughout the experiment, the sensitivity is significantly increased to 97% from 50% using the proposed method.