• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.746-754
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• 2016

Smart healthcare systems, a convergent industry based on information and communications technologies (ICT), has emerged from personal health management to remote medical treatment as a distinguished industry. The smart healthcare environment provides technology to deliver vital information, such as pulse rate, body temperature, health status, and so on, from wearable devices to the hospital network where the physician is located. However, since it deals with the patient's personal medical information, there is a security issue for personal information management, and the system may be vulnerable to cyber-attacks in wireless networks. Therefore, this study focuses on a key-development and device-management system to generate keys in the smart environment to safely manage devices. The protocol is designed to provide safe communications with the generated key and to manage the devices, as well as the generated key. The security level is analyzed against attack methods that may occur in a healthcare environment, and it was compared with existing key methods and coding capabilities. In the performance evaluation, we analyze the security against attacks occurring in a smart healthcare environment, and the security and efficiency of the existing key encryption method, and we confirmed an improvement of about 15%, compared to the existing cipher systems.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.151-158
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• 2021

In this paper, we analyzed the latest research trends, challenges, and potential applications of next-generation solar cell materials in various industrial fields. In addition, future prospects and possibilities of Smart Textile Hybrid Energy Harvesting Devices that will supply electricity by combining with wearable IoT devices are presented. The hybrid textile energy harvesting device fused next-generation solar cells with tribo-piezoelectric devices will develop into new 'Convergence Integrated Smart Wear' by combining the material itself with wearable IoT devices in the era of the 4th industrial revolution. The next-generation nanotechnology and devices proposed in this paper will be applied to the field of smart textile with an energy harvesting function. And we hope it will be a paradigm shift that evolves into creative products which provide AI services such as medical & healthcare by convergence with the future smart wear industry.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.599-606
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• 2016

Many people feel uncomfortable when fitness center is crowded with people in all at the same time. So we propose exercise machines reservation system for resolving the problem that people feel uncomfortable in fitness center. In this paper, we design and implement the exercise machines reservation system that allows for users to reserve fitness equipments by using a NFC-based smart band. A user can reserve exercise machine using some reservation device. he or she will receive notifications through the smart band about when and which machine she or he will have to use. The user can do exercise with a recommended program, and can use any equipments conveniently even in a peak time because no one is waiting. Also, a manager can save cost through the efficient facility management and provide customized member management. Additionally, manager don't need to purchase other exercise machines or computers.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.165-176
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• 2021

Recently, interest in home training and changes in lifestyle are expanding the market in the healthcare field, and high value-added fashion products reflecting the dumbbell economy phenomenon are being released. This study had the following objectives: to investigate the possibility of developing a fashion item that can be applied to the dumbbell economy phenomenon; to develop the UI/UX of a smartphone application for beginners who wish to work out their upper and lower bodies regardless of time and space; and to create a wearable customized smart athleisure fashion device. First, the study identified factors related to exercise methods, breathing techniques, and range of exercises for beginners by investigating the postures of workouts of the upper and lower bodies by angles. Based on the results, the study collected empirical data through a user needs analysis from muscle strengthening exercise experts to verify the significance of the study and use as fundamental data. Second, the study developed the UI/UX of a smartphone application with three different contents: counting, suggesting exercise postures, and providing exercise calendars. Further, the study analyzed necessary user-centered concepts and characteristics in terms of design and technology and developed a wearable customized smart athleisure fashion device based on the results.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.33-39
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• 2023

As the number of people with chronic diseases increases due to an aging society, it is urgent to prevent and manage their diseases. Although biometric authentication methods and Telemedicine Systems have been introduced to solve these problems, it is difficult to solve the security problem of medical information and personal authentication. Since smart healthcare includes personal medical information of subjects, the security of personal information is the most important field. Therefore, in this paper, we tried to propose a Telemedicine System using a smart wearable device ECG in the form of a wristband and face personal authentication in a private blockchain environment. This system targets various medical personnel and patients with chronic diseases in all regions, and uses a private blockchain that can increase data integrity and transparency, ECG and face authentication that are difficult to forge and alter and have high personal identification to provide a system with high security and reliability. composed. Through this, it is intended to contribute to increasing the efficiency of chronic disease management by focusing on disease prevention and health management for patients with chronic diseases at home.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1106-1113
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• 2013

For patients who have senile mental disorder such as dementia, quantity of excercise and amount of sunlight are important clue for dose and the treatment. Therefore, monitoring health information of daily life is necessary for patients' safety and healthy life. Portable & wearable sensor device and server configuration monitoring data are needed to provide these services for patients. Watch-type device(smart watch) which patients wear and server system are developed in this paper. Smart watch developed includes GPS, accelerometer and illumination sensor, and can obtain real time health information by measuring the position of patients, quantity of exercise and amount of sunlight. Server system includes the sensor data analysis algorithm and web server that doctor and protector can monitor through sensor data acquired from smart watch. The proposed data analysis algorithm acquires quantity of exercise information and detects step count in patients' motion acquired from acceleration sensor and to verify this, the three cases with fast pace, slow pace, and walking pace show 96% of the experimental result. If developed u-Healthcare System for dementia patients is applied, more high-quality medical service can be provided to patients.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.260-269
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• 2016

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. Also, oriental medicine research is focused with modern research technology and validate it's various biochemical effect by combining with molecular biology technology. However there are few searching system for finding biochemical mechanism which is related to major compounds in oriental medicine. Therefore, in this paper, we collected papers related with medical herbs from PubMed and constructed a medical herbs database to store and manage chemical, gene/protein and biological interaction information extracted by a literature analysis on the papers. Also, to supporting a multidimensional analysis on the database, we developed a network analysis system based on a hierarchy structure of chemical, gene/protein and biological interaction information. Finally, we expect this system will be used the major tool to discover various biochemical effect by combining with molecular biology technology.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.