• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.637-644
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• 2008

Human emotion has been tried to be recognized by physiological measurements in developing emotion machine enabling to understand and react to user's emotion. This study is to find the time-dependent physiological measurements and their variation characteristics for discriminating emotions according to dimensional emotion model. Ten university students were asked to watch sixteen prepared images to evoke different emotions. Their subjective emotions and autonomic nervous responses such as ECG (electrocardiogram), PPG (photoplethysmogram), GSR (Galvanic skin response), RSP (respiration), and SKT(skin temperature) were measured during experiment. And these responses were analyzed into HR(Heart Rate), Respiration Rate, GSR amplitude average, SKT amplitude average, PPG amplitude, and PTT(Pulse Transition Time). TDPs(Time dependent parameters) defined as the delay, the activation, the half recovery and the full recovery of respective physiological signal in this study have been determined and statistically compared between variations from different emotions. The significant tendencies in TDP were shown between emotions. Therefore, TDP may provide useful measurements with emotion recognition.

• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.11-18
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• 2020

This study aims to suggest the most stable color temperature that can relieve the anxiety of passengers in case of an elevator trapped accident. The experiment was conducted on 10 adult men in their 20s. The color temperature of the interior lighting of the elevator was adjusted to four stages (3,000 K; 6,000 K; 9,000 K; and 12,000 K). Electrocardiogram (ECG) was measured and analyzed to observe the reaction of the user's autonomic nervous system decline in 3,000 K; 6,000 K; 9,000 K compared with 12,000 K, where a statistically significant difference was recognized (p < 0.01). Among them, the activity of the sympathetic nervous system was the lowest under the condition of 3,000 K. Through this study, it was found that the color temperature of 3,000 K induced a sense of stability among passengers in the event of an elevator jam. If the results of this study are used, it seems that the stability of passengers will be secured in the event of an elevator jam.

• The Journal of Internal Korean Medicine
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• v.39 no.4
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• pp.839-845
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• 2018

This is a case report of a 57-year-old patient diagnosed with bradycardia and atrioventricular (AV) block. The chief complaint of the patient was palpitation and dizziness. An electrocardiogram (ECG) showed a second degree AV block with 2:1 AV conduction. The patient was treated with Korean medicine, including herbal medicine, for 35 days. After 2 weeks of treatment, the heart rate increased from 33 to 56 and the follow-up electrocardiogram showed normal findings. The symptoms of palpitation and dizziness were also improved. The effect on heart rate, ECG, and symptoms lasted until the end of the treatment. This case report demonstrated that Korean medicine could be effective for treatment of symptomatic bradycardia with AV block.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.127-134
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• 2017

Color is a significant factor for evoking human emotion. Therefore, the effects of color have been analyzed to predict and evaluate human emotion. The purpose of this study was to measure the cardiovascular responses depending on color stimuli in order to observe differences in color-emotions. Images consisting of six colors (red, green, blue, cyan, magenta, yellow) were used as visual stimuli. 26 college or graduate students (13 males) watched the color stimuli on the monitor and scored their subjective emotion while electrocardiogram (ECG) was meausred. The effects of the color on emotion were tested using Kruskal-Wallis test and Mann-Whitney U test. The coherence ratio showed significant differences between green and magenta (p = .004), green and red (p = .006), and green and yellow (p = .004). The significant differences of cardiovascular and emotions were relevant to emotional valence. This study shows significance as an empirical study by indicating that green induces pleasant and red induces unpleasant.

• Journal of The Korean Society of Clinical Toxicology
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• v.19 no.2
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• pp.133-138
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• 2021

Glufosinate-containing herbicides is a non-selective herbicide commonly used worldwide. As the use of them increased gradually since paraquat was banned in 2012, the number of suicides by their ingestion is also increasing continuously. Complications of glufosinate-containing herbicide poisoning include various central nervous system (CNS) toxicities such as convulsions, loss of consciousness, memory impairment, and respiratory depression, which may be accompanied by hemodynamic changes such as bradycardia and hypotension. However, it is very rare that arrhythmias other than bradycardia occurred and Takotsubo cardiomyopathy was combined due to cardiotoxicity. A 71-year-old female patient was transferred to our hospital after ingesting 500 mL of glufosinate-containing herbicide and receiving 5 L of gastric lavage at a local hospital. A few hours later, she presented stuporous mentality, respiratory depression, and convulsions, and was accompanied by hypotension and bradycardia. On the second day of admission, electrocardiogram (ECG) showed bradycardia and QTc prolongation with hemodynamic Instability. Accordingly, we conducted the early treatment with continuous renal replacement therapy (CRRT) and the application of temporary cardiac pacemaker. An echocardiogram demonstrated decreased ejection fraction (EF) and Takotsubo cardiomyopathy on the third day of admission. Then, she was discharged safely with conservative treatment. At the follow-up after 1 year, Takotsubo cardiomyopathy, EF and QTc prolongation were recovered on echocardiogram and ECG. Because cardiac toxicity after glufosinate-containing herbicide poisoning may cause life-threatening consequences, caution is required while treating the patient. Therefore, if electrocardiogram changes are seen in the elderly with a large amount of glufosinate herbicide ingestion, additional cardiac function test through echocardiography should be concerned, and early treatment through CRRT or artificial cardiac pacing should be considered.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.181-188
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• 2006

The purpose of this study is to predict the defibrillation success of a ventricular Fibrillation ECG signal using time-frequency analysis. During CPR, coronary perfusion pressure and electrocardiogram were measured. Parameters extracted from time-frequency domain were served as predictor of resuscitation success. Time frequency distribution(TFD) of ECG signals was estimated from the smoothed pseudo Wigner-Ville distribution(SPWVD). Median frequency, peak frequency, 1/f slope, frequency band ratios$(2{\sim}4Hz,\;4{\sim}6Hz,\;6{\sim}8Hz,\;8{\sim}10Hz,\;10{\sim}12Hz,\;12{\sim}15Hz)$ were extracted from each TFD as function of time. Paired t-test was used to determine the differences in ROSC and non-ROSC groups. In the statistical results, we selected four significant parameters - median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. We made an attempt to predict defibrillation success by combining features extracted from time frequency distribution. Independent t-test was used to determine the differences ROSC and non-ROSC groups. Consequently, we selected four significant parameters-median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. The relationship between coronary perfusion pressure and ECG parameters was analyzed with linear regression analysis. R-square value was 55%. 1/f slope and $8{\sim}10Hz$ band ratio had the significant relationship with coronary perfusion pressure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.220-226
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• 2011

Device of the ECG and pulse signal was made to measure PTT signal using non-invasive method and possible to wearable. PTT alterations were observed according to position change using implemented system.It was needed to ECG and pulse to detect the PTT, used the photoplethymorgraphy appeared to change the blood volume. And also wireless sensor node which was able to Zigbee compatibility was used to transfer the detected ECG and pulse signal to PC. Noise was removed from transit data and algorithm was applied to calculate the PTT. After the evaluation of both the conventional measuring systems and the proposed photoplethymography measuring system, a highly effective and efficient formation and distribution sequences were found within the proposed photoplethymography measuring system.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1031-1040
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• 2004

Electrocardiogram being the recording of the heart's electrical activity provides valuable clinical information about heart's status. Many re-searches have been pursued for heart disease diagnosis using ECG so far. However, electrocardio-graph uses foreign diagnosis algorithm due to inaccuracy of diagnosis results for a heart disease. This paper suggests ECG data collection, data preprocessing and heart disease pattern classification using data mining. This classification technique is the FB(Frequent pattern Bayesian) classifier and is a combination of two data mining problems, naive bayesian and frequent pattern mining. FB uses Product Approximation construction that uses the discovered frequent patterns. Therefore, this method overcomes weakness of naive bayesian which makes the assumption of class conditional independence.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.261-268
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• 2014

This paper presents a electrocardiogram(ECG), electromyogram(EMG), and Photoplethysmography(PPG) signal wireless monitoring system based on Bluetooth Low Energy (BLE). ECG and EMG sensor interface analog front-end circuits are designed by using off-the-shelf parts. Texas Instruments(TI)'s CC2540DK is used for BLE-based communication. Two CC2540DK modules are used as Peripheral and Central nodes. In peripheral device, vital signals are acquired by the analog front-ends and fed to ADC for analog-to-digital conversion. The peripheral transmitts the data through the air to the central device. The central device receive the data and sends them to PC using UART. GUI is designed using Labview for displaying the acquired vital signals. The developed system can be used for future ubiquitous wireless healthcare system based on bluetooth 4.0.

• Journal of Biomedical Engineering Research
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• v.37 no.2
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• pp.61-67
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• 2016

This paper presented a method for random forest based the arrhythmia classification using both heart rate (HR) and heart rate variability (HRV) features. We analyzed the MIT-BIH arrhythmia database which contains half-hour ECG recorded from 48 subjects. This study included not only the linear features but also non-linear features for the improvement of classification performance. We classified abnormal ECG using mean_NN (mean of heart rate), SD1/SD2 (geometrical feature of poincare HRV plot), SE (spectral entropy), pNN100 (percentage of a heart rate longer than 100 ms) affecting accurate classification among combined of linear and nonlinear features. We compared our proposed method with Neural Networks to evaluate the accuracy of the algorithm. When we used the features extracted from the HRV as an input variable for classifier, random forest used only the most contributed variable for classification unlike the neural networks. The characteristics of random forest enable the dimensionality reduction of the input variables, increase a efficiency of classifier and can be obtained faster, 11.1% higher accuracy than the neural networks.