• Journal of KIISE:Software and Applications
• /
• v.41 no.8
• /
• pp.586-597
• /
• 2014

The next generation mobile computing technology is recently attracting attention that smartphone and wearable device imbedded with various sensors are being deployed in the world. Existing activity and posture recognition research can be divided into two different ways considering feature of one's movement. While activity recognition focuses on catching distinct pattern according to continuous movement, posture recognition focuses on sudden change of posture and body orientation. There is a lack of research constructing a system mixing two separate patterns which could be applied in real world. In this paper, we propose a method to use both smartphone and wearable device to recognize activity and posture in the same time. To use smartphone and wearable sensor data together, we designed a pre-processing method and constructed recognition model mixing signal vector magnitude and orientation pattern features of vertical and horizontal. We considered cycling, fast/slow walking and running activities, and postures such as standing, sitting, and laying down. We confirmed the performance and validity by experiment, and proved the feasibility in real world.

• Journal of Convergence for Information Technology
• /
• v.7 no.5
• /
• pp.47-51
• /
• 2017

The purpose of this study was to investigate the effect of wearable sensor wear on the muscle contraction of cervical erector spinae and upper trapezius causing the forward head posture induction in order to reduce the stress induced by the use of smartphone. This study was to investigate the muscle activity of healthy adults in the 20th to 30th generations by dividing them into the control group using the smartphone, the non-wearing group conscious the posture of the head posture, and the wearing group wearing the wearable sensor. There were no differences in muscle activity between cervical erector spinae and upper trapezius compared to the control, non - wearing, and wearing groups. In addition, the changes in muscle activity of cervical erector spinae muscles were increased in all groups, but the muscle activity of upper trapezius muscles were in the wear group compared to the non-wear group and the control group, but there was no statistical significance. That is, wear of the wearable sensor may be effective in controlling the conscious posture, but it may cause the compensation of another part.

• Proceedings of the Korea Contents Association Conference
• /
• 2015.05a
• /
• pp.13-14
• /
• 2015

In the past few decades, many catastrophic natural disasters have occurred not only in Japan and Korea, but also in other countries in the world, forcing people to live in unfamiliar houses for middle or long range evacuation periods. Residents staying in temporary houses exhibit insomnia, resulting in severe fatigue. In order to investigate sleeping state of residents, measuring vital signals has been performed at examination room of a hospital. To avoid the restriction of residents' movement, we propose to use smartphone and/or wearable devices with various high performance sensors like measuring heart beat rate. We clarify the availability and usefulness of those devices as support for analyzing daily sleeping state of residents.

• Journal of Fashion Business
• /
• v.25 no.5
• /
• pp.88-98
• /
• 2021

In this study, the characteristics of digital anthropometric methods were determined with case studies. These methods were broadly classified into two categories: non-wearable and wearable. Then, these categories were further classified into four types: 3D Scanning, mobile app, smart clothing, and smart tool Among the non-wearable types, the "3D scanning" technique was based on the use of 3D hardware equipment. With this technique, the body shape was measured and the internal body information was obtained. Therefore, it is used in fields of healthcare and fitness. Among the wearable types, "Smart clothing" involves a special clothing that measures human body and a smartphone application. Both the components are linked to a fashion platform, which is based on the measured sizes that help shoppers. The "Smart tool" has the characteristic of measuring only with smart tools and smartphone applications; it does not involve the measurement of images. The common advantage of digital anthropometric methods are as follows: they reduce the time and cost of measurement by enabling self-measurement. Moreover, simple measurements are used to determine the size of anthropometry. Thereafter, it accumulates this data to track the continuous changes in size. From an industrial point of view, digital anthropometric technology should be used to increase sales. The on-demand market can be expanded as global consumers would throng the Korean fashion market. For the consumer, an avatar should be created to fit the user's size. This would provide a fun experience to the user.

• International Journal of Computer Science & Network Security
• /
• v.21 no.2
• /
• pp.221-228
• /
• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.326-330
• /
• 2012

In 2011, There were about 25,000 people died because of heart disease. The aim of this paper is to design a heart attack situation monitoring and spreading system for patients. Wearable computer with a sensor is used to monitor heart rate. Heart rate is transffered to smartphone with bluetooth. After analyzing heart rate, smartphone spread out the emergency situation by various service including emergency call, SNS and SMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.986-987
• /
• 2013

본 연구에서는 사용자 스스로가 바른 자세를 교정 할 수 있도록 도움을 줄 수 있는 스마트폰 기반의 자이로 센서를 이용한 착용형 자세 교정 시스템을 구현하였다. 이를 위하여 2개의 자이로 센서를 Y자 서스펜더 상, 하에 각각 부착하여 신체의 기울기를 측정하였으며, 블루투스 통신을 이용하여 스마트폰으로 데이터를 전송하였다. 전송된 신체의 기울기 정보는 바른 자세에 대한 평균 기울기 정보와 비교하여 바른 자세와 잘못된 자세를 판단하고자 하였으며, 이를 위한 스마트폰 기반의 어플리케이션을 구현하였다. 구현된 어플리케이션은 자세 판별뿐만 아니라 현재의 자세 정보를 직관적으로 표현하기 위한 모니터링 부와 잘못된 자세 검출 시 진동이나 알림 음 또는 팝업 메시지를 통해 사용자에게 전달하는 알림 기능을 구성하였다. 또한 구현된 시스템으로부터 대표적인 잘못된 자세 4가지에 대한 검출 실험을 수행하였으며, 그 결과 100% 검출이 가능함을 확인하였다.

• Journal of Sensor Science and Technology
• /
• v.27 no.1
• /
• pp.6-12
• /
• 2018

In this paper, a 32-variable pulse position modulation (32-VPPM) scheme is proposed to support a red-green-blue light-emitting-diode (RGB-LED)-based optical camera communication (OCC) system. Our proposed modulation scheme is designed to enhance the OCC data transmission rate, which is targeted for the wearable biomedical data monitoring system. The OCC technology has been utilized as an alternative solution to the radio frequency (RF) wireless system for long-term self-healthcare monitoring. Different biomedical signals, such as electrocardiograms, photoplethysmograms, and respiration signals are being monitored and transmitted wirelessly from the wearable biomedical device to the smartphone receiver. A common 30 frames per second (fps) smartphone camera with a CMOS image sensor is used to record a transmitted optical signal. Moreover, the overall proposed system architecture, modulation scheme, and data demodulation are discussed in this paper. The experimental result shows that the proposed system is able to achieve > 9 kbps using only a common smartphone camera receiver.

• Journal of Digital Convergence
• /
• v.20 no.5
• /
• pp.637-642
• /
• 2022

Self-authentication technology using electrocardiogram (ECG) signals is drawing attention as a self-authentication technology that can replace existing bio-authentication. A device that recognizes a digital electronic key can be mounted on a vehicle to wirelessly exchange data with a car, and a function that can lock or unlock a car door or start a car by using a smartphone can be controlled through a smartphone. However, smart keys are vulnerable to security, so smart keys applied with bio-authentication technology were studied to solve this problem and provide driver convenience. A personal authentication algorithm using electrocardiogram was mounted on a watch-type wearable device to authenticate bio, and when personal authentication was completed, it could function as a smart key of a car. The certification rate was 95 per cent achieved. Drivers do not need to have a smart key, and they propose a smart key as an alternative that can safely protect it from loss and hacking. Smart keys using personal authentication technology using electrocardiogram can be applied to various fields through personal authentication and will study methods that can be applied to identification devices using electrocardiogram in the future.