• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1303-1310
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• 2010

Recently, researches related with automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for SpO2 sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, SpO2 and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the SpO2 and ECG signals. HRV (Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.545-548
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• 2009

Recently, researches related to automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for $SpO_2$ sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, $SpO_2$ and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the $SpO_2$ and ECG signals. HRV(Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.11-18
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• 2007

The physiological and biochemical responses of healthy men and women to life stress were measured in order to temperature, blood pressure (BP), heart rate (HR) and galvanic skin response (GSR) were selected as physiological stress indices and salivary cortisol level was used as a biochemical stres biomarker. Twenty six (male 14 and female 13) colege students were participated in the experiment. Female showed the significant higher value of salivary cortisol level (p<0.01), diastolic BP (p<0.01), and HR (p<0.01) than male. The difference of skin temperature between forehead and fingertip correlated significantly with salivary cortisol level (p<0.01). The LF(low frequency)/HF(high frequency) ratio of HRV also correlated significantly with salivary cortisol level (p<0.01). However, BP, HR and GSR corelated insignificantly with salivary cortisol level. We suggest that LF/HF ratio of HRV and skin temperature may be good indices for the assessment of life stress, and may apply to measure the stress level of individual in real time.

• The Journal of Korean Medicine
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• v.35 no.4
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• pp.24-35
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• 2014

Objectives: Although the autonomic nervous system (ANS) is thought to play an important role in treatment of obesity, no study has been conducted to investigate acupuncture's effects on this aspect of the ANS. This study aimed to describe the effects of acupuncture in the ANS by means of heart rate variability (HRV) analysis. Methods: A total of 46 obese women aged from 21 to 54 with body mass index ranging from 25.1 to $39.3kg/m^2$ were recruited and randomized into both the real acupuncture group (n=23) and sham acupuncture group (n=23). A total of 3 instances of HRV analysis were conducted before, during, and after treatment. Statistically significant differences between time and groups were analyzed using repeated measure analysis of variance. Results: All parameters of time domain analysis and frequency domain analysis except for the square root of the mean squared differences of successive normal sinus intervals (RMSSD) and very low frequency (VLF) showed significant differences between times. The mean of all R-R intervals (mean RR) showed significant level of interaction between time and group. Between groups, time domain analysis of standard deviation of the normal-to-normal intervals (SDNN), RMSSD and frequency domain analysis of total power (TP) and high frequency (HF) showed significant differences. Conclusions: The real acupuncture group showed deactivation of parasympathetic function and relative increase of sympathetic activity in obese subjects. Further studies are necessary to uncover the mechanisms of acupuncture in obesity treatment.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• Journal of Sensor Science and Technology
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• v.19 no.1
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• pp.17-24
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• 2010

This paper describes a real time reliable monitoring method and analysis system using wrist type oximeter for ubiquitous healthcare service based on IEEE 802.15.4 standard. Photoplethysmograph(PPG) is simple and cost effective technique to measure blood volume change. In order to obtain and monitor physiological body signals continuously, a small size and low power consumption wrist type oximeter is designed for the measurement of oxygen saturation of a patient unobtrusively. The measured data is transferred to a central PC or server computer by using wireless sensor nodes in wireless sensor network for storage and analysis purposes. LabVIEW server program is designed to monitor stress indicator from heart rate variability(HRV) and process the measured PPG to accelerated plethysmograph(APG) by appling second order derivatives in server PC. These experimental results demonstrate that APG can precisely describe the features of an individual's PPG and be used as estimation of vascular elasticity for blood circulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1286-1293
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• 2014

Typically, studies through the simulation system have been progressed, because the evaluation of the driver's arousal state about the service of a actual train has risk of safety for the driver. When configured event same as the real in simulation system, the ability to cope with an accident situation may be the same each other. But the difference in the state of tension or arousal will occur. In this study, requested to cooperate with the railways in order to escape from these constraints, and the target of the experiment was to real engineer service. I was set about experiment when the train was stopped as safe as possible. As a result, the beta wave of EEG signals that representing complex calculations or anxiety is increased rapidly on the basis of a flag station from at the time of departure. The size of the electrodermal activity signal in response to movement of the body gave a noticeable. In terms of HRV, if the train approach a flag station gradually and the R-R interval is narrowed. So that the driver can be estimated as arousal state. In accordance with this study, if the quantitative standard of arousal state be based on the driver's biosignals will provide, it will be able to take advantage of development the system that would prevent train accidents caused by human error.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.37-46
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• 2015

The wireless electrocardiographic monitoring system(WDMS) is designed to be long term monitoring for the early detection of cardiac disorders. The current version of the WDMS can identify two types of cardiac rhythms in real-time, such as atrial fibrillation(AF) and normal sinus rhythm(NSR), which are very important to track cardiac-rhythm disorders. In this study, we proposed the analysis method to discriminate the characteristics statistically evaluated in both time and frequency domains between AF and NSR using various parameters in the heart rate variability(HRV). And we applied various ECG detection methods (e.g., difference operation method) and compared the results with those of the discrete wavelet transform(DWT) method. From the statistically results, we found that the parameters such as STD RR, STD HR, RMSSD, NN50, pNN50, RR Trian, and TNN(p<0.05) are significantly different between the AF and NSR patients in time domain. On the other hand, the frequency domain analysis results showed a significant difference in VLF power($ms^2$), LF power($ms^2$), HF power($ms^2$), VLF(%), LF(%), and HF(%). In particular, the parameters such as STD RR, RMSSD, NN50, pNN50, VLF power, LF power and HF power were considered as the most useful parameters in both AF and NSR patient groups. Our proposed method can be efficiently applied to early detection of abnormal conditions and prevent the such abnormals from becoming serious.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.136-142
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• 2014

Distinct features in heart rate signals during the driver's wake and sleep states could provide an initiative for the development of a safe driving systems such as drowsiness detecting sensor in a smart wheel. We measured ECG from health subjects ($23.5{\pm}2.5$ in age) during the wake and drowsiness states. The proposed method is able to detect R waves and R-R interval calculation in the ECG even when the signal includes in abnormal signals. Heart rate variability(HRV) was investigated for the time domain and frequency domains. The STD HR(0.029), NN50(0.044) and VLF power(0.0018) of the RR interval series of the subjects were significantly different from those of the control group (p < 0.05). In conclusion, there are changes in heart rate from wake to drowsiness that are potentially to be detected. The results in our study could be useful for the development of drowsiness detection sensors for effective real-time monitoring.

• Journal of Biosystems Engineering
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• v.38 no.2
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• pp.163-170
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• 2013

Purpose: The purpose of this study is to provide analysis of physiological, biomechanical responses occurring from the operation to lifting or twist lifting task appears frequently in agricultural work. Methods: This study investigated the changes of physiological factors such as heart rate, heart rate variability (HRV) and biomechanical factors such as physical activity and kinetic analysis in the task of twisting at the waist while lifting. Results: Heart rates changed significantly with the workload. The result indicated that the workload of 2 kg was light intensity work, and the workload of 12 kg was hard intensity work. Physical activity increased as the workload increased both on wrist and waist. Besides, stress index of the worker increased with the workload. Dynamic load to herniated discs was analyzed using inertial sensor, and the angular acceleration and torque increased with the workload. The proposed measurement system can measure the recipient's physiological and physical signals in real-time and analyzed 3-dimensionally according to the variety of work load. Conclusions: The system we propose will be a new method to measure agricultural workers' multi-dimensional signals and analyze various farming tasks.