• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.33-42
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• 2010

In this study, we have proposed a simple cardiorespiratory monitoring method based on displacements of human body which occurs due to periodic heartbeat and breathing. The proposed system consists of an aircushion, pressure sensing hardware and heartbeat and respiration signals extraction algorithm. The aircushion was used for unconstrained measurement of the respiration and heartbeats without a sensor attached on the subject's skin surface. The displacements of subject sitting on the aircushion cause small pressure variations. These variations are amplified and filtered with the pressure sensing hardware. Finally, heart rate and respiration rate are extracted by signal processing algorithm based on frequency domain filter. To evaluate the performance, extracted respiration and heart rate from proposed system were compared with conventional methods. The average sensitivity of respiration and heart rate are 98.67% and 99.24%, respectively. These results show the proposed method has advantages of installing and processing simplicity so as to be used easily in unconstrained respiration and heart rate monitoring in daily life.

• Journal of Korea Game Society
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• v.12 no.1
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• pp.67-77
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• 2012

With the development of tangible interface in recent years, the interest in interactive exercise games to improve health-related physical fitness has been increased. We believe that this kind of serious game should provide not only motion sensing of the action required to play sports but also a specific effectiveness of exercise. This paper will show how a serious exercise game affects theirs heart rate and preference. For the experiments, we used an exercise game named GalaxyBike for aerobics exercise which is developed by the Interaction Media Research Center of Hoseo University. In the experiments, players' heart rate was measured during the warming-up, exercise and cooling-down periods by a wireless heart-rate measuring instrument. After they played the exercise game, a survey was conducted to see how they like this serious exercise game. The findings of the study suggest that the serious exercise game providing both video game and exercise would make a contribution to the improvement of health-related physical fitness since it serves to increase the heart rate and motivation.

• Proceedings of the KSRS Conference
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• v.2
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• pp.868-871
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• 2006

Mortality of domestic people from cardiovascular disease ranked second, which followed that of from cancer last year. Therefore, it is very important and urgent to enhance the reliability of medical examination and treatment for cardiovascular disease. Heart Rate Variability (HRV) is the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate and conditions of a human heart. In this paper, our aim is to extract a quantitative measure for HRV to enhance the reliability of medical examination for cardiovascular disease, and then develop a prediction method for extracting multi-parametric features by analyzing HRV from ECG. In this study, we propose a hybrid Bayesian classifier called FP-based Bayesian. The proposed classifier use frequent patterns for building Bayesian model. Since the volume of patterns produced can be large, we offer a rule cohesion measure that allows a strong push of pruning patterns in the pattern-generating process. We conduct an experiment for the FP-based Bayesian classifier, which utilizes multiple rules and pruning, and biased confidence (or cohesion measure) and dataset consisting of 670 participants distributed into two groups, namely normal and patients with coronary artery disease.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.355-363
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• 2007

One of major factors for learning achievement is the student's learning preference according to his character type. In course of learning, if a student studies e-learning contents opposed to his preference, then he would be under stress and his blood pressure and heart beat be changed. For measuring unwillingness, we used spectral components in frequency domain known as stress measure. For 13 children attending kindergarten we examined S(sensing)/ N(intuition) of MBTI and presented same learning contents during 10 minutes. During learning we gathered ECG signals, changed into HRV(heart rate variability), transformed time-varying HRV signal into spectral density in frequency domain. And then, we divided it into three areas of low(LF), middle(MF), and high-frequency(HF) and calculated stress measures by rates of those frequency area. We compared estimated stress measures of S group with them of N group whether students in different group preferred different contents or not. Experimental shows that students according to MBTI type prefer different contents.

• Journal of Biomedical Engineering Research
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• v.27 no.4
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• pp.154-163
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• 2006

A 64-channel magnetocardiogram (MCG) system using low-noise superconducting quantum interference device (SQUID) planar gradiometers was developed for the measurements of cardiac magnetic fields generated by the heart electric activity. Owing to high flux-to-voltage transfers of double relaxation oscillation SQUID (DROS) sensors, the flux-locked loop electronics for SQUID operation could be made simpler than that of conventional DC SQUIDs, and the SQUID control was done automatically through a fiber-optic cable. The pickup coils are first-order planar gradiometers with a baseline of 4 em. The insert has 64 planar gradiometers as the sensing channels and were arranged to measure MCG field components tangential to the chest surface. When the 64-channel insert was in operation everyday, the average boil-off rate of the dewar was 3.6 Lid. The noise spectrum of the SQUID planar gradiometer system was about 5 fT$_{rms}$/$\checkmark$Hz at 100 Hz, operated inside a moderately shielded room. The MCG measurements were done at a sampling rate of 500 Hz or 1 kHz, and realtime display of MCG traces and heart rate were displayed. After the acquisition, magnetic field mapping and current mapping could be done. From the magnetic and current information, parameters for the diagnosis of myocardial ischemia were evaluated to be compared with other diagnostic methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2987-3002
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• 2023

In 2015, the number of senior citizens aged 65 and over in Korea was 6,662,400, accounting for 13.1% of the total population. Along with these social phenomena, risk information related to the elderly is increasing every year. In particular, a fall accident caused by a fall can cause serious injury to an elderly person, so special attention is required. Therefore, in this paper, we implemented a system that monitors fall accidents and informs them in real time to minimize damage caused by falls. To this end, beacon-based indoor location positioning was performed and biometric information based on an integrated module was collected using various sensors. In other words, a multi-functional sensor integration module was designed based on Arduino to collect and monitor user's temperature, heart rate, and motion data in real time. Finally, through the analysis and prediction of measurement signals from the integrated module, damage from fall accidents can be reduced and rapid emergency treatment is possible. Through this, it is possible to reduce the damage caused by a fall accident, and rapid emergency treatment will be possible. In addition, it is expected to lead a new paradigm of safety systems through expansion and application to socially vulnerable groups.

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.755-765
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• 2016

Recently, interest in monitoring health and sports is growing because of the emphasis on wellness, which is accelerating the development and commercialization of smart clothing for biosignal monitoring. In addition to exerciseeffect monitoring clothing that tracks heart rate and respiration, recently developed clothing makes it possible to monitor muscle balance using electromyogram (EMG). The electrode for EMG have to attached to an accurate location in order to obtain high-quality signals in surface EMG measurement. Therefore, this study develops monitoring clothing suitable for different types of human bodies and aims to extract suitable range of EMG according to movements in order to develop self-fitness monitoring clothing based on EMG measurement. This study identified and attached electrodes on six upper muscles and two lower muscles of ten males in their 20s. After selecting six main motions that create a load on muscles, the 8-ch wireless EMG system was used to measure amplitude value, noise, SNR and SNR (dB) in each part and statistical analysis was conducted using SPSS 20.0. As a result, the suitable range for EMG measurement to apply to clothing was identified as four parts in musculus pectoralis major; three parts in muscle rectus abdominis, two parts each in shoulder muscles, backbone erector, biceps brachii, triceps brachii, and musculus biceps femoris; and four part in quadriceps muscle of thigh. This was depicted diagrammatically on clothing, and the EMG-monitoring sensing locations were presented for development of self-fitness monitoring.

• Smart Structures and Systems
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• v.8 no.1
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• pp.53-67
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• 2011

Human state in human-machine systems highly affects the overall system performance, and should be detected and monitored. Physiological cues are essential indicators of human state and useful for the purpose of monitoring. The study presented in this paper was focused on developing a bio-inspired sensing system, i.e., Nano-Skin, to non-intrusively measure physiological cues on human-machine contact surfaces to detect human state. The paper is presented in three parts. The first part is to analyze the relationship between human state and physiological cues, and to introduce the conceptual design of Nano-Skin. Generally, heart rate, skin conductance, skin temperature, operating force, blood alcohol concentration, sweat rate, and electromyography are closely related with human state. They can be measured through human-machine contact surfaces using Nano-Skin. The second part is to discuss the technologies for skin temperature measurement. The third part is to introduce the design and manufacture of the Nano-Skin for skin temperature measurement. Experiments were performed to verify the performance of the Nano-Skin in temperature measurement. Overall, the study concludes that Nano-Skin is a promising product for measuring physiological cues on human-machine contact surfaces to detect human state.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.97-108
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• 2017

The purpose of this study was to propose a product planning and design direction for smart fitness wear that will improve the impact of personal training based on researching the requirements of smart fitness wear and its acceptance level, as well as the functional demand. The study conducted in-depth interviews with professional fitness trainers and derived five categories and thirteen keywords by analyzing the categorical data analysis using the interview data. In addition, we surveyed general consumers to measure the acceptance level of smart fitness wear and the functional demand for product development. The results revealed that the difference in the acceptance level of smart fitness wear generally depended on the characteristics related to exercise involvement and exercise-related culture rather than on the demographic characteristics. With regard to the difference in the functional demand of smart fitness wear, the results showed that professional trainers focused on the scientific improvement of the effect of exercise while general consumers focused on the function that considers the sustainability of exercise. Based on the results, we proposed product planning and design directions such as 'mounting of heart rate sensing, muscle activity sensing, motion angle or posture sensing, and motion sensing', 'development of concepts and contents for expert line, ordinary line', 'compression wear design', and 'differentiation of product development according to exercise areas'.