• Science of Emotion and Sensibility
• /
• v.2 no.2
• /
• pp.37-42
• /
• 1999

Long-term exposure to loud noise affects performance since it changes arousal level, distracts attention, and also is able to evoke subjective stress accompanied by negative emotional states. The purpose of the study was to analyze dynamics of subjective and physiological variables during a relatively long-lasting (30 min) exposure to white noise (85 dB[A]). Physiological signals were recorded on 15 college students during 30 min of intense auditory stimulation. Autonomic variables, namely skin conductance level , non-specific SCR number, inter-best intervals in ECG, heart rate variability index (HF/LF ratio of HRV), skin temperature, as well as respiration rate were analyzed on 5 min epoch basis. Psychological assessment (subjective rating of stress level) was also repeated every 5 min. Statistical analysis was employed to trace the time course of the dynamics of subjective and autonomic physiological variables and their relationships. Results showed that the intense noise evoked subjective stress as well as associated autonomic nervous system responses. However it was shown that physiological variables endured specific changes in the process of exposure to the loud white noise. Discussed were probable psychophysiological mechanisms mediating reactivity to long-term auditory stimulation of high intensity, namely short-term activation, followed by transient adaptation (with relatively stable autonomic balance) and then a subsequent wave of arousal due to tonic sympathetic dominance.

• Journal of Biomedical Engineering Research
• /
• v.19 no.3
• /
• pp.269-278
• /
• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.

• Journal of the Korean Geotechnical Society
• /
• v.21 no.5
• /
• pp.207-214
• /
• 2005

The reflected signals from the defects of a pile and the boundaries between the pile and soils are analyzed to evaluate the integrity of drilled shafts in the impact-echo test. Signals varied according to both of the stiffness ratio of the pile to defects and that of the pile to surrounding soils. Model tests using the small size pile in the laboratory and numerical analyses have limitations in finding the characteristics of the signals due to different stress wave characteristics and unreliable modelling for the interaction between the pile and soils respectively. Full scale testing piles which have artificial defects are installed by the actual construction method and they were used to investigate the characteristics of reflected signals according to defects and the stiffness ratios of the pile to soils around.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.3
• /
• pp.661-668
• /
• 2018

Biomedical signals using skin resistance have different characteristics according to stress diseases. Biological diagnostic devices for diagnosing stress diseases have been developed by using these characteristics, and devices have been developed so that the signals measured by the skin storage meter can be easily analyzed. Experts in the field will look directly at the output signal to determine the likelihood of any stress disorder. However, it is very difficult for a person to accurately determine whether a person to be measured has a stress disorder by analyzing a bio-signal measured by each person to be measured, and the result of the judgment is very likely to be wrong. In order to solve these problems, we implemented the function of determining the signal of a stress disorder by using the machine learning technique. SVM was used as a classification method in consideration of low computing ability of measurement equipment. Training data and test data were randomly generated for each disease using error range 5 based on 13 diseases. Simulation results showed more than 90% decision accuracy. In the future, if the measurement equipment is actually applied to the patients, we can retrain the classifier with the newly generated data.

• Journal of Biomedical Engineering Research
• /
• v.25 no.6
• /
• pp.581-587
• /
• 2004

Conventional power spectrum methods based on FFT, AR method are not appropriate for analyzing biomedical signals whose spectral characteristics change rapidly. On the other hand, time-frequency analysis has more desirable characteristics of a time-varying spectrum. In this study, we investigated the spectral components of heart rate variability(HRV) in time-frequency domain using time frequency analysis methods. In the various time-frequency kernels functions, we studied the suitable kernels for the analysis of HRV using synthetic HRV signals. First, we evaluated the time/frequency resolution and cross term reduction of various kernel functions. Then, from the instantaneous frequency, obtained from time-frequency distribution, the method extracting frequency components of HRV was proposed. Subjects were 17 healthy young men. A coin-stacking task was used to induce mental stress. For each subjects, the experiment time was 3 minutes. Electrocardiogram, measured during the experiment, was analyzed after converted to HRV signal. In the results, emotional stress of subjects produced an increase in sympathetic activity. Sympathetic activation was responsible for the significant increase in the LF/HF ratio. Subjects were divided into two groups with task ability. Subjects who have higher mental stress have lack of task ability.

• Journal of the Korea Institute of Building Construction
• /
• v.20 no.1
• /
• pp.93-102
• /
• 2020

The purpose of this study is to find out how to measure the stress related to accidents at the construction site promptly and conveniently to prevent safety accidents of construction workers. Accordingly, we analyzed the correlations between the questionnaire tool index that measures the stress associated with complex psychology of humans by integrating emotion, cognition, physical and behavioral responses, and basic brain waves, SEF-90, concentration, stress index from brain wave. As a result, which had the highest correlation with the stress measured through the questionnaire, was the SEF-90, and the regression analysis between two independent variables yielded a specific regression equation. This suggests the possibility of measuring the integrated stress of construction workers through the EEG signal at the construction site, and it can be used for the safety management of the construction site in the future.

• Smart Structures and Systems
• /
• v.15 no.1
• /
• pp.135-150
• /
• 2015

Large concrete structures are prone to cracks and damages over time from human usage, weathers, and other environmental attacks such as flood, earthquakes, and hurricanes. The health of the concrete structures should be monitored regularly to ensure safety. A reliable method of real time communications can facilitate more frequent structural health monitoring (SHM) updates from hard to reach positions, enabling crack detections of embedded concrete structures as they occur to avoid catastrophic failures. By implementing an unconventional mode of communication that utilizes guided stress waves traveling along the concrete structure itself, we may be able to free structural health monitoring from costly (re-)installation of communication wires. In stress-wave communications, piezoelectric transducers can act as actuators and sensors to send and receive modulated signals carrying concrete status information. The new generation of lead zirconate titanate (PZT) based smart aggregates cause multipath propagation in the homogeneous concrete channel, which presents both an opportunity and a challenge for multiple sensors communication. We propose a time reversal based pulse position modulation (TR-PPM) communication for stress wave communication within the concrete structure to combat multipath channel dispersion. Experimental results demonstrate successful transmission and recovery of TR-PPM using stress waves. Compared with PPM, we can achieve higher data rate and longer link distance via TR-PPM. Furthermore, TR-PPM remains effective under low signal-to-noise (SNR) ratio. This work also lays the foundation for implementing multiple-input multiple-output (MIMO) stress wave communication networks in concrete channels.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.285-288
• /
• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.9 no.1
• /
• pp.106-110
• /
• 1989

Bolting degradation problems in primary coolant pressure boundary applications have become a major concern in the nuclear industry. In the bolts concerned, the failure mechanism was either corrosion wastage(loss of bolt diameter) or stress-corrosion cracking.(3) Here the manual ultrasonic testing of RPV(Reactor Pressure Vessel) and RCP(Reactor Coolant Pump) stud has been performed. But it is difficult to detect indications because examiner can not exactly control the rotation angle and can not distinguish the indication from signals of bolt. In many cases, the critical sizes of damage depth are very small(1-2 mm order). At critical size, the crack tends to propagatecompletly through the bolt under stress, Resulting in total fracture.(3) Automatic stud scanner for studs(bolts) was developed because the precise measurement of bolt diameter is required in this circumstance. By use of this scanner, the rotation angle of probe was exactly controlled and the exposure time of radiations was reduced.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.62 no.1
• /
• pp.50-55
• /
• 2013

Subjects with 0.7[clo]'s amount of clothing were estimated on their thermal comfort, concentrativeness, heart rate variability, stress and fatigue degree when given variation in relative humidity to 30, 40, 50, 60, 70, and 80[RH%], in an environmental test room of temperature 25[$^{\circ}C$], illumination 1000[lux] and air velocity 0.02[m/sec], by using EEG, learning ability and HRV. At the result, it was at 50~60[RH%] of relative humidity that subject's thermal comfort and concentrativeness were at the highest while stress were at the lowest, and it was at 60[RH%] of relative humidity that heart rate variability was most stabilized. It was found that when temperature and humidity of the environmental test room are at 25[$^{\circ}C$] and 50~60[RH%], subject's productivity and psychological state are least affected.