• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.811-817
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• 2013

In this study we present a system for pulse-rate period detection and human sensibility evaluation based on the wireless medical telemetry service (WMTS) used for transmission of data from medical telemetry devices to various medical facilities and services. We develop a medical-purpose specific WMTS communication module to transmit biometric signals. From the pulse rate variability(PRV) signal, we attempt to classify positive and negative emotional states based on analysis of the ratio of LF/HF in the frequency domain. We measure the data reception rate according to distance in order to test the performance of the WMTS module and analyze the effects on human sensibility evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.283-289
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• 2012

Web-based physiological signal monitoring system can provide appropriate healthcare services to transmit bio-signal processing, analysis of bulk in medical centers. Therefore, we constructed a design of system to analyze effect of cardiac associated auricular acupuncture reflexology based on physiological signals. System to analyze effect cardiac associated auricular acupuncture reflexology, which carried out analysis and measurement of bio-signal to apply cardiac-related biometrics input in biometric image and voice signal. In addition, we also confirmed through statistical analysis actual home healthcare system to performance evaluation of system on subjects 20.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

• 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.

• Science of Emotion and Sensibility
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• v.9 no.2
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• pp.141-150
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• 2006

Since the late 1990s, 'smart clothing' has been developed in a various way to meet the need of users and to help people more friendly interact with computers through its various designs. Recently, various applications of smart clothing concept have been presented by researchers. Among the various applications, smart clothing with a health care system is most likely to gain the highest demand rate in the market. Among them, smart clothing for check-up of health status with its sensors is expected to sell better than other types of smart clothing on the market. Under this circumstance, research and development for this field have been accelerated furthermore. This research institution has invented biometric sensors suitable for the smart clothing, and has developed a design to diagnose various diseases such as cardiac disorder and respiratory diseases. The newly developed smart clothing in this study looks similar to the previous inventions, but people can feel more comfortable in it with its fabric interaction built in it. When people wear it, the health status of the wearers is diagnosed and its signals are transmitted to the connected computer so the result can be easily monitored in real time. This smart clothing is a new kind of clothing as a supporting system for preventing various cardiac disorder and respiratory diseases using its biometric sensor built-in, and is also an archetype to show how smart clothing can work on the market.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.53-61
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• 2020

Recently, as the uncontact service is activated in earnest due to the Corona 19 virus, the necessity of system development to provide non-face-to-face contact remote medical service has increased. In this study, we propose a smart healthcare system, Rm_She(Remote Medical Smart Healthcare System). Rm_She can collect and manage various vital signs information by connecting various healthcare products that detect bio-signals based on IoT to one application. The health check app (HC_app) is used to connect vital sign measurement devices to a wireless LAN and receive vital sign values from the HC_app. Then, the vital signs are output to the user on the smartphone, and the corresponding information is transmitted to the healthcare management server. The healthcare server receives the measured values and stores them in a database, and the stored measured values are provided as a web service so that medical staff can remotely monitor them in real time.

• Physical Therapy Rehabilitation Science
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• v.9 no.1
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• pp.18-24
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• 2020

Objective: The purpose of this study was to compare the activities of the abdominal muscles according to trunk stabilization exercises using Swiss ball in normal individuals. Design: Cross-sectional study. Methods: Ten healthy university students participated in this study. The subjects were required to complete the following three exercise positions: Exercise position 1, sitting on a Swiss ball and lifting the legs; Exercise position 2, pushing to a plank position from an ending position; and Exercise position 3, push-up posture with the legs on a Swiss ball. Changes in the trunk muscle activities were estimated using Biometric electromyography (EMG). Activities of the dominant side internal oblique muscle (IOM) and external oblique muscle (EOM) were estimated in all participants. The maximal voluntary isometric contraction (MVIC %) was measured to standardize the EMG signals for the IOM and EOM during maximum resistance when sitting up with each shoulder pointing towards the contralateral pelvis with knees bent and both arms crossed on the chest for 5 seconds. Results: There was a significant difference in the activity of the internal and external oblique muscles between Exercises 1 and 2 and Exercises 1 and 3 (p<0.05). Furthermore, the IOM/EOM activity ratio was the greatest during Exercise 3 and the smallest during Exercise 1. IOM and EOM activities were the greatest during Exercise 2 with greater EOM activity. Conclusions: In future studies, it will be necessary to investigate muscle activities by supplementing the above-mentioned limitations during the stabilization exercise. The results of this study may be used as a basis for controlling the intensity and frequency of exercise while prescribing trunk stabilization exercises.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.43-52
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• 2022

We can sense somebody's feeling fatigue, which means that fatigue can be detected through sensing human biometric signals. Numerous researches for assessing fatigue are mostly focused on diagnosing the edge of disease-level fatigue. In this study, we adapt quantitative analysis approaches for estimating qualitative data, and propose video analysis models for measuring fatigue state. Proposed three deep-learning based classification models selectively include stages of video analysis: object detection, feature extraction and time-series frame analysis algorithms to evaluate each stage's effect toward dividing the state of fatigue. Using frontal face videos collected from various fatigue situations, our CNN model shows 0.67 accuracy, which means that we empirically show the video analysis models can meaningfully detect fatigue state. Also we suggest the way of model adaptation when training and validating video data for classifying fatigue.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1345-1352
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• 2023

With the development of virtual reality (VR) and blockchain technology, Metaverse is being used in various fields such as games, education, and social networking. At the same time, shipments of wearable devices such as smartwatches are growing every year, becoming more and more integrated into people's daily lives. This study presents a new possibility of reflecting the user's body signals measured through the combination of the two phenomena in the metaverse character. Various biometric information such as the user's heart rate and amount of exercise collected through the smartwatch are reflected on the character in the metaverse, allowing the user's physical condition to be reflected in the virtual world. Through this, Metaverse is expected to provide a new experience that can be called 'extended reality' beyond simple virtual reality, improve user's satisfaction with Metaverse, and suggest a direction for the development of smartwatches.

• Smart Media Journal
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• v.11 no.9
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• pp.30-38
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• 2022

It is important to grasp biometric data in real time for prompt action in the event of a safety accident at a work site where the risk of safety accidents exists. Among them, blood oxygen saturation is the most important factor in maintaining human life, so real-time oxygen saturation measurement and monitoring is necessary according to the situation as a preemptive response for worker safety management. By receiving real-time bio-signals from workers wearing health and life-risk protective clothing, and sharing and analyzing the worker's risk status in an external system, it is possible to diagnose the worker's current condition and efficiently respond to emergencies that may occur to the worker. In this paper, we propose a wearable oxygen saturation measurement platform technology that can monitor the risk of harmful gases and oxygen saturation of the wearer in real time and ensure the wearer's activity and safety in order to cope with emergency situations at the scene of an accident. If we overcome the limitations identified through the results of the proposed system later and apply improved biodata such as motion correction to the platform, we expect that it will be usable not only in hazardous gas environments, but also in hospitals and homes for emergency patients.