• 제어로봇시스템학회논문지
• /
• 제22권12호
• /
• pp.1011-1020
• /
• 2016

This paper introduces a tactilely transparent soft glove composed of soft materials and flexible structures. Although it is hard to achieve a high grasping force with conventional grip-assist gloves made from soft material, the proposed glove can exert a high force by using a novel structure. This structure has a triangular shape composed of flexible structural frames, soft fabric, and belts. It can produce grip-assist moment compliantly without harmful force or misalignment with the human fingers. The whole finger part that comes into contact with objects is made of thin and soft fabric in order to facilitate sensation transference. The proposed tactilely transparent soft glove enables the user to manipulate various objects owing to both the softness and high grasping force; it helps lifting heavy weight objects as well as permitting delicate tactile feeling on the palm and fingers. The proposed concept was applied to a two-finger grip-assist device for validation. In addition, the experimental results regarding grasping objects, fingertip force, and grasping force are presented.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2016년도 제50회 동계 정기학술대회 초록집
• /
• pp.363.2-363.2
• /
• 2016

Stretchable strain sensors are becoming essential in diverse future applications, such as human motion detection, soft robotics, and various biomedical devices. One of the well-known approaches for fabricating stretchable strain sensors is to embed conductive nanomaterials such as metal nanowires/nanoparticles, graphene, conducting polymer and carbon nanotubes (CNTs) within an elastomeric substrate. Among various conducting nanomaterials, CNTs have been considered as important and promising candidate materials for stretchable strain sensors owing to their high electrical conductivity and excellent mechanical properties. In the past decades, CNT-based strain sensors with high stretchability or sensitivity have been developed. However, CNT-based strain sensors which show both high stretchability and sensitivity have not been reported. Herein, highly stretchable and sensitive strain sensors were fabricated by integrating single-walled carbon nanotubes (SWNTs) and nylon textiles via vacuum-assisted spray-layer-by-layer process. Our strain sensors had high sensitivity with 100 % tensile strain (gauge factor ~ 100). Cyclic tests confirmed that our strain sensors showed very robust and reliable characteristic. Moreover, our SWNTs-based strain sensors were easily and successfully integrated on human finger and knee to detect bending and walking motion. Our approach presented here might be route to preparing highly stretchable and sensitive strain sensors with providing new opportunity to realize practical wearable devices.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
• /
• pp.277.2-277.2
• /
• 2014

For next-generation electronic applications, human-machine interface devices have recently been demonstrated such as the wearable computer as well as the electronic skin (e-skin). For integration of those systems, it is essential to develop many kinds of components including displays, energy generators and sensors. In particular, flexible sensing devices to detect some stimuli like strain, pressure, light, temperature, gase and humidity have been investigated for last few decades. Among many condidates, a pressure sensing device based on organic field-effect transistors (OFETs) is one of interesting structure in flexible touch displays, bio-monitoring and e-skin because of their flexibility. In this study, we have investigated a flexible e-skin based on highly sensitive, pressure-responsive OFETs using microstructured ferroelectric gate dielectrics, which simulates both rapidly adapting (RA) and slowly adatping (SA) mechanoreceptors in human skin. In SA-type static pressure, furthermore, we also demonstrate that the FET array can detect thermal stimuli for thermoreception through decoupling of the input signals from simultaneously applied pressure. The microstructured highly crystalline poly(vinylidene fluoride-trifluoroethylene) possessing piezoelectric-pyroelectric properties in OFETs allowed monitoring RA- and SA-mode responses in dyanamic and static pressurizing conditions, which enables to apply the e-skin to bio-monitoring of human and robotics.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2016년도 춘계학술대회
• /
• pp.560-563
• /
• 2016

의료와 헬스케어 분야의 변화는 디지털 기술로부터 시작된다. 디지털 헬스케어라는 새로운 분야는 기존 헬스케어 및 의료 기술이 디지털 기술과 융합되어 시작된 것으로 ICBM(사물인터넷 클라우드 빅데이터 모바일), 인공지능, 로봇, 가상 증강현실, 웨어러블기기 등 ICT 기술을 활용해 건강관리 질병관리 등 헬스케어서비스 효과를 높이고 의료비용을 절감시키는 융합산업이다. 최근에는 구글 알파고와 IBM 왓슨 등 인공지능기술을 헬스케어 영역에 접목되고 있다. 따라서 본 연구에서는 디지털 헬스케어의 주요 기술, 생태계와 플랫폼, 그리고 미래의료서비스 변화 및 이슈를 분석한다.

• 센서학회지
• /
• 제28권1호
• /
• pp.30-35
• /
• 2019

Inertial measurement units (IMUs) are widely used for wearable motion-capturing systems in the fields of biomechanics and robotics. When the IMUs are combined with optical motion sensors (hereafter, OPTs) for their complementary capabilities, it is necessary to align the coordinate system orientations between the IMU and OPT. In this study, we compare the application of two coordinate transformation-based orientation alignment methods between two coordinate systems. The first method (M1) applies angular velocity coordinate transformation, while the other method (M2) applies gyroscopic angle coordinate transformation. In M1 and M2, the angular velocities and angles, respectively, are acquired during random movement for a least-square algorithm to determine the alignment matrix between the two coordinate systems. The performance of each method is evaluated under various conditions according to the type of motion during measurement, number of data points, amount of noise, and the alignment matrix. The results show that M1 is free from drift errors, while drift errors are present in most cases where M2 is applied. Thus, this study indicates that M1 has a far superior performance than M2 for the alignment of IMU and OPT coordinate systems for motion analysis.

• 마이크로전자및패키징학회지
• /
• 제25권4호
• /
• pp.25-34
• /
• 2018

In this paper, we review the latest technical progress and commercialization of stretchable interconnectors, stretchable strain sensors, and stretchable substrates for stretchable electronics. The development of stretchable electronics can pave a way for new applications such as wearable devices, bio-integrated devices, healthcare and monitoring, and soft robotics. The essential components of stretchable electronic devices are stretchable interconnector and stretchable substrate. Stretchable interconnector should have high stretchability and high electrical conductivity as well as stability under severe mechanical deformation. Therefore several nanocomposite-based materials using CNT, graphene, nanowire, and metal flake have been developed. Geometric engineering such as wavy, serpentine, buckled and mesh structure has been well developed. Stretchable substrate should also pose high stretchability and compatibility with stretchable sensing or interconnecting material. We summarize the recent research results of new materials for stretchable interconnector and substrate as well as strain sensors. The Important challenges in development of the stretchable interconnector and substrate are also briefly discussed.

• 센서학회지
• /
• 제31권2호
• /
• pp.96-101
• /
• 2022

As the elderly population gradually increases, the risk of fatal fall accidents among the elderly is increasing. One way to cope with a fall accident is to determine the fall direction before impact using a wearable inertial measurement unit (IMU). In this context, a previous study proposed a method of classifying fall directions using a support vector machine with sensor velocity, acceleration, and tilt angle as input parameters. However, in this method, the IMU signals are processed through several processes, including a Kalman filter and the integration of acceleration, which involves a large amount of computation and error factors. Therefore, this paper proposes a machine learning-based method that classifies the fall direction before impact using IMU raw signals rather than processed data. In this study, we investigated the effects of the following two factors on the classification performance: (1) the usage of processed/raw signals and (2) the selection of machine learning techniques. First, as a result of comparing the processed/raw signals, the difference in sensitivities between the two methods was within 5%, indicating an equivalent level of classification performance. Second, as a result of comparing six machine learning techniques, K-nearest neighbor and naive Bayes exhibited excellent performance with a sensitivity of 86.0% and 84.1%, respectively.

• 센서학회지
• /
• 제33권1호
• /
• pp.7-11
• /
• 2024

Soft-pressure sensors have numerous applications in soft robotics, biomedical devices, and wearable smart devices. Herein, we present a highly sensitive electronic skin device with an isotropic wrinkled pressure sensor. A conductive ink for soft pressure sensors is produced by a solution process using polydimethylsiloxane (PDMS), poly 3-hexylthiophene (P3HT), carbon black, and chloroform as the solvents. P3HT provides high reproducibility and conductivity by improving the ink dispersibility. The conductivity of the ink is optimized by adjusting the composition of the carbon black and PDMS. Soft lithography is used to fabricate a conductive elastic structure with an isotropic wrinkled structure. Two conductive elastic structures with an isotropic wrinkle structure is stacked to develop a pressure sensor, and it is confirmed that the isotropic wrinkle structure is more sensitive to pressure than when two elastic structures with an anisotropic wrinkle structure are overlapped. Specifically, the pressure sensor fabricated with an isotropic wrinkled structure can detect extremely low pressures (1.25 Pa). Additionally, the sensor has a high sensitivity of 15.547 kpa^-1 from 1.25 to 2500 Pa and a linear sensitivity of 5.15 kPa^-1 from 2500 Pa to 25 kPa.

• 감성과학
• /
• 제10권4호
• /
• pp.583-601
• /
• 2007

웨어러블 컴퓨팅 환경은 대개 이동 중일 가능성이 많고 이때 눈과 손이 자유롭지 못하고 많은 주의가 필요한데 기존의 데스크탑 인터페이스 방식(WIMP)은 적합하지 않다. 또한 웨어러블 환경에서 모바일 기기의 소형화로 인하여 작은 화면에서 정보를 확인하고 처리해야 하기 때문에 기능 수행에 따른 인지부하가 늘어남과 동시에 수행 속도가 느려지고 많은 오류가 발생하는 등 어려움이 따른다. 이와 같이 변화된 환경에 적합한 입력 방식의 적정 수준을 찾는 연구가 필요하다. 본 연구는 이동 상황에서 모바일 기기를 사용할 때 동시에 여러 가지 일을 수행함으로써 걸릴 수 있는 인지부하를 줄여주기 위한 방법을 기기의 입력 방식과 사용되는 메뉴구조의 복잡성을 중심으로 분석하였다. 입력 방식을 포인팅입력 방식, 버튼입력 방식, 동작입력 방식으로 나누고, 이 방식들을 통한 메뉴탐색 과제와 화면에 제시되는 도형기억 과제를 동시에 수행했을 때 수행의 정확도와 과제수행 속도를 측정하였다. 또한 제시되는 메뉴탐색 과제의 메뉴계층의 수를 변화시켜서 입력 방식의 복잡성에 따른 과제 수행을 살펴보았다. 실험은 정지 상황과 이동 상황에서 모두 이루어졌다. 정지 상황과 이동 상황 모두에서 포인팅입력 방식이 과제 수행의 정확도가 가장 높은 반면 수행 속도에서 가장 느린 것으로 나타났다. 동작입력 방식에서는 수행의 정확도는 떨어졌으나 수행 속도는 빠르게 나타났다. 이는 이동 중에 수행되는 과제에서 정확도보다도 속도가 중요한 상황에서는 동작입력 방식이 적합하다는 것을 시사한다.

• 센서학회지
• /
• 제31권6호
• /
• pp.433-440
• /
• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.