Development of a System for Cognitive Workload Distinction for Intelligent Vehicle

Wongi Hong,Wonsup Lee,Kihyo Jung,Suwan Park,Yunsuk Park,Joonwoo Son,Seikwon Park,Heecheon You 대한인간공학회 2011 대한인간공학회 학술대회논문집 Vol.2011 No.5

Objective: The aim of this study is to compare and evaluate the accuracy of workload distinction of quantification measures (HR, SDNN, RMSSD, RMSE) by ROC analysis method to apply ECG biosignal to safe driving support technology of intelligent vehicle. And a system applied ROC analysis method to analyze the accuracy of workload distinction in real-time is developed. Background: Biosignals such as electrocardiography (ECG) can be used to analyze driver's cognitive workload which is one of safe driving support technologies of the intelligent vehicle. Driver's workload can be distinguished by analyzing heart rate (HR) and heart rate variability (HRV), which are calculated by ECG measured. To distinguish workload level based on ECG, individually suitable quantification measures of ECG should be selected; however, existing researches have used equal ECG quantification measures and ECG baseline. Method: System which can analyze workload in real-time and discriminate the most suitable measure for ECG quantification is developed. Results: A case study was conducted to test the system; consequently, HR was the most suitable measure for ECG quantification in the case. Conclusion: The system will be complemented at the point of effectiveness and usability continuously and it will beable to be applied and used to intelligent vehicle in the foreseeable future. Application: The system and the algorithm will be useful in the research for workload based on ECG.

A Novel Method to Estimate Heart Rate from ECG

Leu, Jenq-Shiun,Lo, Pei-Chen The Korean Society of Medical and Biological Engin 2007 의공학회지 Vol.28 No.4

Heart rate variability (HRV) in electrocardiogram (ECG) is an important index for understanding the health status of heart and the autonomic nervous system. Most HRV analysis approaches are based on the proper heart rate (HR) data. Estimation of heart rate is thus a key process in the HRV study. In this paper, we report an innovative method to estimate the heart rate. This method is mainly based on the concept of periodicity transform (PT) and instantaneous period (IP) estimate. The method presented is accordingly called the "PT-IP method." It does not require ECG R-wave detection and thus possesses robust noise-immune capability. While the noise contamination, ECG time-varying morphology, and subjects' physiological variations make the R-wave detection a difficult task, this method can help us effectively estimate HR for medical research and clinical diagnosis. The results of estimating HR from empirical ECG data verify the efficacy and reliability of the proposed method.

Smartwatch-Based Driver Vigilance Indicator With Kernel-Fuzzy-C-Means-Wavelet Method

Boon Giin Lee,Jae-Hee Park,Chuan Chin Pu,Wan-Young Chung IEEE 2016 IEEE SENSORS JOURNAL Vol.16 No.1

<P>A high-precision driver vigilance predictor could be a monetary countermeasure to reduce road accidents. Heart rate variability is a well-known measurement parameter to predict driver vigilance state, but the measurement is susceptible to motion artifact due to body movement where the electrocardiogram (ECG) sensor device had to be worn close to the heart. Thus, this paper presents a novel approach to measure the ECG from the driver palms while holding on the steering wheel. In addition, photoplethysmograms sensor attached on a driver finger can also measure the similar heart rate pattern, known as pulse rate variability. Another significant vigilance measurement parameter, respiratory rate variability, can be derived directly from the ECG with the squaring baseline method, without the usage of respiratory sensor. Furthermore, this paper is also focusing on the integration of age and gender as vigilance measurement parameter as each individual exhibits distinct signal pattern. Autonomous rules are derived from the data set that performs the kernel fuzzy c-means with if-then rules extraction, which subsequently classify the driver vigilance level into two predefined classes, that are drowsy and awake. The vigilance monitoring application is developed in smartwatch, able to perform the features extraction, and then predict the driver vigilance class based on the Kernel Fuzzy-C-Mean trained model. A vibration warning will be triggered to the driver if the driver is estimated as drowsy in five consecutive time frames. In fact, the experimental results stated that the prediction accuracy can be achieved at 97.28% on average across variant subjects.</P>

재실자 온열쾌적평가에서 인체의 생리적 반응을 고려한 심박변이도 측정 및 분석 방법 비교 연구

임재한(Lim JaeHan) 한국태양에너지학회 2021 한국태양에너지학회 논문집 Vol.41 No.3

Thermal comfort in humans has been evaluated using predicted mean vote (PMV) based on factors such as clothing and activity levels of an individual to address their satisfaction with the thermal environment. However, PMV does not consider the physiological and psychological factors associated with thermal comfort. A person may feel dissatisfied in an environment that is thermally comfortable for others; this can be calculated by applying heart rate variability (HRV) to the comfort index by measuring the ECG data of the body. Currently, various types of wearable IoT sensors are available for measuring HRV characteristics. In this study, we analyzed the HRV parameters in the human body to evaluate the thermal comfort of the occupant. A data measurement and analysis method using different HRV sensors was developed to determine the feasibility of HRV as a physiological response to the thermal comfort model of the occupant. The characteristic changes in the measured HRV values were analyzed in standard indoor and outdoor environmental conditions.

게임 중독군의 게임 중 스트레스 반응민감도에 따른 HRV 파라미터 추출

김정룡(Jung Yong Kim),김혜솔(Heasol Kim),김동준(Dong Joon Kim) 대한인간공학회 2020 大韓人間工學會誌 Vol.39 No.5

Objective: The purpose of this study is to extract quantitative parameters that indicate significant differences in ECG (electrocardiogram) between game-addicted group and non-addicted group. Background: Although the concept and side-effects of game addiction are recognized around the world, there is no objective means to define game addiction among health authorities, academic societies, and institutions. Also, studies suggesting objective references have been lacking so far. Considering the limitations of the current diagnosis subjective scale, it is necessary to make a quantitative assessment for the prevention and treatment of game addiction. Method: With the existing diagnostic questionnaire, authors classified subjects into game-addicted groups and non-addicted group, and used ECG parameters representing heart rate variability. The parameters were analyzed by applying various window-sizes based on specific game situations. A t-test was used to compare the two groups. Finally, correlation analysis and factor analysis were performed to extract the best parameters to differentiate the two groups. Results: The large window size over 20 minutes of gameplay time, showed no significant difference between the two groups. When the event data were analyzed, there was no significant difference during a player character killed an opponent player. However, when the player character was killed, there were significant differences in parameters. In particular, these differences were most prominent in a window size of 1min 30 sec after the player character was killed. After that, RMSSD and LF were found to be the most sensitive parameters through correlation analysis and factor analysis. Conclusion: In this study, we measured and analyzed the stress response difference by using ECG parameters between game addicted group and the non-addicted group. As a result, it was observed that the game addiction group was sensitive to stress stimuli in a particular situation. The outcome of to extract this study is the optimal window-size and parameters for developing a quantitative model discriminating the sign of addiction among game users in the future. Application: The parameters extracted in this study can be further tested to develop an algorithm to diagnose the addicted players, and the measuring technique used in this study is textile and non-invasive to be used at device development in the future.

재실자 온열쾌적평가를 위한 인체의 심박변이도 분석 방법에 대한 연구

임재한(JaeHan Lim) 한국태양에너지학회 2021 한국태양에너지학회 학술대회논문집 Vol.2021 No.5

Development of an Evaluation Method for a Driver's Cognitive Workload Using ECG Signal

Wongi Hong,Wonsup Lee,Kihyo Jung,Baekhee Lee,Suwan Park,Yunsuk Park,Joonwoo Son,Seikwon Park,Heecheon You 대한인간공학회 2011 대한인간공학회 학술대회논문집 Vol.2011 No.10

Objective: The present study is to develop an effective evaluation method for a driver's cognitive workload using electrocardiography (ECG) signal. Background: ECG measures such as heart rate (HR) and heart rate variability (HRV) have been used for cognitive workload evaluation. Since ECG changes by cognitive workload vary largely depending on personal characteristics, an optimal analysis protocol of ECG needs to be tailored to each individual accordingly; however, existing studies have not considered personal characteristics in ECG analysis for cognitive workload evaluation. Method: The proposed evaluation method uses the area under the receiver operating characteristic (ROC) curve (AUC). A preliminary analysis was conducted with ECG data collected in a driving simulator while an n-back task was conducted. AUC analysis was performed for four ECG metrics (mean IBI, SDNN, RMSSD, and RMSE), three window spans (20, 30, and 40 seconds), and three update rates (1, 2, and 3 seconds). Results: It was identified that the optimal ECG analysis parameters of metric, window span, and update rate maximizing the discriminability of cognitive workload evaluation varied between individual drivers. Conclusion: The finding of the present study supports the use of an individually customized ECG analysis protocol for better evaluation accuracy of a drivers' cognitive workload. Application: The proposed ECG analysis method for cognitive workload evaluation can be applied to development of a safe driving support system.

한 자동차공장의 1주연속 12시간주야맞교대근무 노동자들의 심박동수변이

성주헌,염명걸,공정옥,이혜은,김인아,김정연,손미아,Sung, Ju-Hon,Yum, Myung-Gul,Kong, Jung-Ok,Lee, Hye-Un,Kim, In-A,Kim, Jung-Yeon,Son, Mi-A 대한예방의학회 2004 예방의학회지 Vol.37 No.2

Objectives : The objective of this study is to compare the circadian patterns of heart rate variability assessed by 24-hour ambulatory electrocardiographic (ECG) recordings during day shift and night shift among the workers in the 5 days-concecutive-12-hour shift in an automobile factory in Korea. Methods : The study population consisted 300 workers, who were randomly selected among the 8700 total workers in one car factory. To analyse circadian variation, the 24-hour ECG recordings (Marquette) were measured during day shift (08:00-20:00 h) and night shift (20:00-08:00 h). Analysis was performed for all time and frequency domain measures of HRV. 233 workers completed taking 24-hour ECG recordings. Results : This study shows that the 24 hourcircadian variation mainly follows work/sleep cycle rather than day/night cycle among shift workers. This study also shows that among the night shift, the circadian variation between work and sleep cycle decreased compared to the work/sleep cycle among day shift workers. All time and frequency domain parameters (except LF/HF ratio) show significantly different between work and sleep in the day shift and night shift. Conclusion : These changes in heart rate variability circadian rhythms reflect significant reductions in cardiac parasympathetic activity with the most marked reduction in normal vagal activity among the shift workers. Especially, it suggests the circadian rhytm has blunted among the night workers. The quantification of the circadian variation in HRV can be a surrogates of workers' potential health risk, as well as suggests possible mechanisms through which the shift works compromise workers' health.

Preceding Research for Estimating the Maximal Fat Oxidation Point through Heart Rate and Heart Rate Variability

Myeong-Heon Sim(심명헌),Min-Yong Kim(김민용),Sol-Chan Yoon(윤찬솔),Joo-Hong Chung(정주홍),Yeon-Sik Noh(노연식),Sung-Bin Park(박성빈),Hyung-Ro Yoon(윤형로) 대한전기학회 2012 전기학회논문지 Vol.61 No.9

Increasing the oxidation of fat through exercise is the recommendable method for weight control. Preceding researches have proposed increase in the usage of fat during exercise in stabilized state and under maximum exertion through aerobic training. However, such researches require additional equipment for gas analysis in order to measure the caloric value or gas exchange of subjects during exercise. Such equipments become highly restrictive for those exercise and cause substantially higher cost. According to this, we have presented the method of estimating the maximal fat oxidation point through changes in LF & HF which reflects changes in heart rate and the autonomic nervous system in order to induce exercise for a less restrictive and efficient fat oxidation than existing methods. We have conducted exercise stress test on subject with similar exercise abilities, and have detected the changes in heart rate and changes in LF & HF by measuring changes in fat oxidation and measuring ECG signals at the same time through a gas analyzer. Changes in heart rate and HRV of the subjects during exercising was detected through only the electrocardiographic signals from exercising and detected the point of maximum fat oxidation that differs from person to person. The experiment was carried out 16 healthy males, and used Modified Bruce Protocol, which is one of the methods of exercise stress test methods that use treadmill. The fat oxidation amount during exercise of all the subjects showed fat oxidation of more than 4Fkcal/min in the exercise intensity from about 5 minutes to 10 minutes. The correlation between the maximal fat oxidation point obtained through gas analysis and the point when 60% starts to be relevant in the range from -0.01 to 0.01 seconds for values of R-R interval from changes in heart rate had correlation coefficients of 0.855 in Kendall’s method and in Spearman’s rho, it showed significant results of it being p<0.01 with 0.950, respectively. Furthermore, in the changes in LF & HF, we have determined the point where the normalized area value starts to become the same as the maximal fat oxidation point, and the correlation here showed 0.620 in Kendall and 0.780 in Spearma of which both showed significant results as p<0.01.

침처치의 24시간 심박변이도 영향에 대한 비선형 분석

오달석(Oh Dalseok),이전(Lee Jeon),김종열(Kim Jongyeol),최선미(Choi Sunmi) 한국한의학연구원 2008 한국한의학연구원논문집 Vol.14 No.1

This study is to investigate cardiotonic effect of acupuncture on heart rate variability(HRV) analyzed by a nonlinear way(DFA, Detrended Fluctuation Analysis). It was designed as a randomized, single-blind, waiting list-controlled, cross-over study. We assessed heart rate and R-R intervals in Circadian electrocardiography with a Holter monitoring device for twelve hospitalized participants. The compatible analytical program, Zymed, was used for generating the signals of R-R intervals from 24 hour-ECG. In DFA analysis, we produced DFA alpha 1, alpha 2 parameters according to the process of Cygwin module of Linux server. We tested if there was any difference between HRV parameters using SPSS, a statistical package. There was no difference between acupuncture and no treatment group in DFA alpha 2 parameter {95% Confidence Interval (-)0.058 - 0.037, P = .565}. Two group all showed large intra-individual variations. Consequently, acupuncture treatment did not modulate the complexity of HRV in a DFA analysis. This study can be a rationale for acupuncture's properties on cardiovascular and autonomic systems.