• 패션비즈니스
• /
• 제18권4호
• /
• pp.1-14
• /
• 2014

Currently smart textile market is rapidly expanding and the demand is increasing integration of an electronic fiber circuit. The garments are an attractive platform for wearable device. This is one of the integration techniques, which consists of is the selective introduction of conductive yarns into the fabric through knitting, weaving or embroidering. The aim of this work is to develop a golf bend driven prototype design for an attachable Arduino that can be used to assess elbow motion. The process begins with the development of a wearable device technique that uses conductive yarn and flex sensor for measurement of elbow bending movements. Also this paper describes and discusses resistance value of zigzag embroidery of the conductive yarns on the tensile properties of the fabrics. Furthermore, by forming a circuit using an Arduino and flex sensor the prototype was created with an assistance band for golf posture training. This study provides valuable information to those interested in the future directions of the smart fashion industry.

• 대한임베디드공학회논문지
• /
• 제17권1호
• /
• pp.19-24
• /
• 2022

Through the development and dissemination of embedded devices, studies that may help patients are rapidly emerging. Recently, as wearable devices have become one of the ways to diagnose diseases in daily life, they are being studied as a way to assist severely ill patients to lead their daily lives. Among them, a method of detecting and giving signals to detect and solve symptoms using acceleration sensors to diagnose Parkinson's disease is being studied, and there is no study to measure and analyze various factors that can affect Parkinson's disease. To solve them, we designed and developed a wearable device, P-Band, with various sensors capable of diagnosing related symptoms, including acceleration sensors capable of diagnosing Parkinson's disease. In this paper, the overall structure of the P-Band and the description and operation method of the measurable sensors are presented. In addition, it was confirmed that the symptoms of Parkinson's patients could be determined complexly through the results measured in actual patients.

• 한국산학기술학회논문지
• /
• 제22권1호
• /
• pp.18-23
• /
• 2021

산업 전반에 걸쳐 자기장 센서에 대한 연구나 제품개발이 많이 진행되어져 왔다. 하지만 이런 제품의 단가를 낮추기 위해서는 초기 개발단계에서부터 자기장 필드와 자기장 센서의 특징과 최종제품의 특징들을 정확하게 이해하는 것이 중요하다. 특히, 자기장 필드는 비선형 데이터를 처리하는 계산이 복잡하여 실제로 사용하고 응용하기에는 매우 어렵기 때문에, 이렇게 측정된 자기장 센서값들을 정확하게 계산하기 위해서는 고가의 장비나 복잡한 알고리즘이 필요한 추세였다. 하지만, 본 논문에서는 기존 조이스틱의 특징을 이해한 상태에서 자기장 센서의 고유한 특성과 특징을 소개하면서, 자기장 센서를 사용하는 웨어러블 조이스틱을 개발하기에 적합하고 간단하면서도 기능을 충족하는 디자인 및 개발 방법들을 제시하였다. 특히, 기존 조이스틱의 기계적인 특징과 자기장 센서의 특성을 서로 잘 고려한 후에, 기존 조이스틱의 본질적인 문제인 기계적인 마모와 문제점들을 해결하고자 기계적 구성이나 선들이 필요없는 자기장 센서를 이용하여, 저가의 웨어러블 조이스틱 장치의 디자인 및 개발 할 수 있는 설계요소 및 방법들을 소개하였다. 본 논문의 개발결과로 실제 사용자 테스트를 수행하여, 본 논문의 장비를 처음 접하는 사용자들도 쉽게 이용하여 기존 조이스틱과 같이 정확하게 제어할 수 있음을 보였다.

• 센서학회지
• /
• 제19권1호
• /
• pp.43-51
• /
• 2010

In this study, wearable ECG measurement system was implemented for health monitoring during daily life. A wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenience in wearing. The measured ECG signal is transmitted via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. The ECG monitoring program is developed at end user which is personal computer. The measured ECG contains many noises mainly due to motion artifacts. For ECG signal processing, adaptive filtering process is proposed which can reduce motion artifacts efficiently and accurately than digital filter. The experimental results show that a reliable performance with high quality ECG signal can be achieved using this wearable ECG monitoring system.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.261-263
• /
• 2006

Nowadays, technologies such as RFID, sensor network makes our life comfortable more and more. In this paper we propose a wearable computing system for blind and deaf person who can be easily out of sight from our technology. We are making a wearable computing system that is consisted of embedded board to processing data, ultrasonic sensors to get distance data and motors that make vibration as a signal to see the screen for a deaf person. This system offers environmental informations by text and voice. For example, distance data from a obstacle to a person are calculated by data compounding module using sensed ultrasonic reflection time. This data is converted to text or voice by main processing module, and are serviced to a handicapped person. Furthermore we will extend this system using a voice recognition module and text to voice convertor module to help communication among the blind and deaf persons.

• Journal of Information Processing Systems
• /
• 제20권2호
• /
• pp.159-172
• /
• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2017년도 제56차 하계학술대회논문집 25권2호
• /
• pp.419-420
• /
• 2017

착용센서가 스포츠, 복지, 건강 등 다양한 분야에서 널리 연구되고 있다. 착용센서 시스템은 일반적으로 데이터획득, 데이터전처리, 특징값 추출 그리고 분석 단계로 구성된다. 본 연구는 착용센서 시스템 각 단계별 연구 현황과 착용센서 활용 연구현황을 살펴본다.

• 한국측량학회지
• /
• 제38권5호
• /
• pp.425-433
• /
• 2020

Three-dimensional data has been used for different applications such as robotics, building reconstruction, and so on. 3D data can be generated from an optical camera or a laser scanner. Especially, a wearable multi-sensor system including the above-mentioned sensors is an optimized structure that can overcome the drawbacks of each sensor. After finding the geometric relationships between sensors, georeferencing of the datasets acquired from the moving system, should be carried out. Especially, in an indoor environment, error propagation always causes problem in the georeferencing process. To improve the accuracy of this process, other sources of data were used to combine with LiDAR (Light Detection and Ranging) data, and various registration methods were also tested to find the most suitable way. More specifically, this paper proposed a new process of NDT (Normal Distribution Transform) to register the LiDAR point cloud, with additional information from other sensors. For real experiment, a wearable mapping system was used to acquire datasets in an indoor environment. The results showed that applying the new process of NDT and combining LiDAR data with IMU (Inertial Measurement Unit) information achieved the best result with the RMSE 0.063 m.

• 센서학회지
• /
• 제31권5호
• /
• pp.301-306
• /
• 2022

With the recent widespread implementation of Internet of Things (IoT) technology driven by Industry 4.0, self-powered sensors for wearable and implantable systems are increasingly gaining attention. Piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), which convert biomechanical energy into electrical energy, can be considered as efficient self-powered sensor platforms. These are energy harvesters that are used as low-power energy sources. However, they can also be used as sensors when an output signal is used to sense any mechanical stimuli. For sensors, collecting high-quality data is important. However, the accuracy of sensing for practical applications is equally important. This paper provides a brief review of the performance advanced by the materials and structures of the latest PENG/TENG-based wearable sensors and intelligent applications applied using artificial intelligence (AI)

• 로봇학회논문지
• /
• 제18권4호
• /
• pp.496-504
• /
• 2023

This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.