Journal paper 게재(Scientific Reports) : Transparent and Flexible Mayan-Pyramid-based Pressure Sensor using Facile-Transferred Indium tin Oxide for Bimodal Sensor Applications

10월 7th, 2019 댓글이 없습니다.

Transparent and Flexible Mayan-Pyramid-based Pressure Sensor using Facile-Transferred Indium tin Oxide for Bimodal Sensor Applications

Minhyun Jung, Sujaya Kumar Vishwanath, Jihoon Kim, Dae-Kwan Ko, Myung-Jin Park, Soo-Chul Lim* & Sanghun Jeon*

Abstract

Transparent and conducting flexible electrodes have been successfully developed over the last few decades due to their potential applications in optoelectronics. However, recent developments in smart electronics, such as a direct human-machine interface, health-monitoring devices, motion-tracking sensors, and artificially electronic skin also require materials with multifunctional properties such as transparency, flexibility and good portability. In such devices, there remains room to develop transparent and flexible devices such as pressure sensors or temperature sensors. Herein, we demonstrate a fully transparent and flexible bimodal sensor using indium tin oxide (ITO), which is embedded in a plastic substrate. For the proposed pressure sensor, the embedded ITO is detached from its Mayan-pyramid-structured silicon mold by an environmentally friendly method which utilizes water-soluble sacrificial layers. The Mayan-pyramid-based pressure sensor is capable of six different pressure sensations with excellent sensitivity in the range of 100 Pa-10 kPa, high endurance of 105 cycles, and good pulse detection and tactile sensing data processing capabilities through machine learning (ML) algorithms for different surface textures. A 5 × 5-pixel pressure-temperature-based bimodal sensor array with a zigzag-shaped ITO temperature sensor on top of it is also demonstrated without a noticeable interface effect. This work demonstrates the potential to develop transparent bimodal sensors that can be employed for electronic skin (E-skin) applications.

DOI

https://doi.org/10.1038/s41598-019-50247-4

Journal paper 게재(Proceedings of the IEEE) : Flexible Multimodal Sensors for Electronic Skin: Principle, Materials, Device, Array Architecture, and Data Acquisition Method

9월 11th, 2019 댓글이 없습니다.

Flexible Multimodal Sensors for Electronic Skin: Principle, Materials, Device, Array Architecture, and Data Acquisition Method

Sanghun Jeon, Soo-Chul Lim, Tran Quang Trung, Minhyun Jung, and Nae-Eung Lee

Abstract:

Electronic skin (e-skin) is designed to mimic the comprehensive nature of human skin. Various advances in e-skin continue to drive the development of the multimodal tactile sensor technology on flexible and stretchable platforms. e-skin incorporates pressure, temperature, texture, photographic imaging, and other sensors as well as data acquisition and signal processing units formed on a soft substrate for humanoid robots, wearable devices, and health monitoring electronics that are the most critical applications of soft electronics. This artificial skin has developed very rapidly toward becoming real technology. However, the complex nature of e-skin technology presents significant challenges in terms of materials, devices, sophisticated integration methods, and interference-free data acquisition. These challenges range from functional materials, device architecture, pixel design, array structure, and data acquisition method to multimodal sensing performance with negligible interference. In this article, we present recent research trends and approaches in the field of flexible and stretchable multimodal sensors for e-skin focusing on the following aspects: 1) flexible and stretchable platforms; 2) operating principles and materials suitable for pressure, temperature, strain, photograph, and hairy sensor devices; 3) device and integration architectures, including multimodal single cells, three-axis tactile sensors, vertical-stacked sensor arrays, active matrix sensor arrays, and integration electronics; 4) reliable acquisition methods for various texture sensing and machine-learning algorithms for processing tactile sensing data; and 5) future outlook.
Published in: Proceedings of the IEEE ( Early Access )
Page(s): 1 – 19

Journal Paper 게재(Sensors) : An Efficient Three-Dimensional Convolutional Neural Network for Inferring Physical Interaction Force from Video

8월 19th, 2019 댓글이 없습니다.

An Efficient Three-Dimensional Convolutional Neural Network for Inferring Physical Interaction Force from Video
Dongyi Kim, Hyeon Cho, Hochul Shin, Soo-Chul Lim  and Wonjun Hwang

ABSTRACT : Interaction forces are traditionally predicted by a contact type haptic sensor. In this paper, we propose a novel and practical method for inferring the interaction forces between two objects based only on video data—one of the non-contact type camera sensors—without the use of common haptic sensors. In detail, we could predict the interaction force by observing the texture changes of the target object by an external force. For this purpose, our hypothesis is that a three-dimensional (3D) convolutional neural network (CNN) can be made to predict the physical interaction forces from video images. In this paper, we proposed a bottleneck-based 3D depthwise separable CNN architecture where the video is disentangled into spatial and temporal information. By applying the basic depthwise convolution concept to each video frame, spatial information can be efficiently learned; for temporal information, the 3D pointwise convolution can be used to learn the linear combination among sequential frames. To validate and train the proposed model, we collected large quantities of datasets, which are video clips of the physical interactions between two objects under different conditions (illumination and angle variations) and the corresponding interaction forces measured by the haptic sensor (as the ground truth). Our experimental results confirmed our hypothesis; when compared with previous models, the proposed model was more accurate and efficient, and although its model size was 10 times smaller, the 3D convolutional neural network architecture exhibited better accuracy. The experiments demonstrate that the proposed model remains robust under different conditions and can successfully estimate the interaction force between objects.

US patent 등록 “Variable stiffness film, variable stiffness flexible display, and method of manufacturing the variable stiffness film”, US10257929

4월 25th, 2019 댓글이 없습니다.

Abstract

A variable stiffness film, a variable stiffness flexible display, and a manufacturing method thereof may include a lower electrode, a variable fluid, and an upper electrode. A polymer layer may be formed on the lower electrode, and a variable fluid receiving portion is patterned on the polymer layer. A variable stiffness layer is formed by putting a variable fluid in the variable fluid receiving portion. The upper electrode is formed on the variable fluid layer.

Filed: August 7, 2014
Date of Patent: April 9, 2019
Assignee: Samsung Electronics Co., Ltd.
Inventors: Lim; Soo Chul (Seoul, KR), Park; Joon Ah (Seoul, KR), Lee; Hyun Jeong (Hwaseong-si, KR), Han; Seung Ju (Seoul, KR)
http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=10257929.PN.&OS=PN/10257929&RS=PN/10257929

EP patent 등록 “Apparatus, computer program product, and method for controlling vibration transfer between vibration devices”, EP2626770

4월 25th, 2019 댓글이 없습니다.

 

Inventors: Soo Chul Lim, Joon Ah Park

 

https://patents.google.com/patent/EP2626770B1/de?oq=EP2626770

https://patentimages.storage.googleapis.com/b8/42/5f/707404fb273e86/EP2626770B1.pdf

Prof. Lim received Best Teaching Professor 2018 Award from Dongguk University.

3월 7th, 2019 댓글이 없습니다.

Prof. Lim received Best Teaching Professor 2018 Award from Dongguk University.

 

DSC_2731

20190225_171024599_14580

Journal Paper Accepted (Composites Part B: Engineering): Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network

1월 2nd, 2019 댓글이 없습니다.

Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network 

Asif Khan, Dae-Kwan Ko, Soo Chul Lim*, Heung Soo Kim* (* : corresponding author)

Abstract

This paper proposes a Convolutional Neural Network (CNN) based approach for the classification and prediction of various types of in-plane and through-the-thickness delamination in smart composite laminates using low-frequency structural vibration outputs. An electromechanically coupled mathematical model is developed for the healthy and delaminated smart composite laminates, and their structural vibration responses are obtained in the time domain. Short Time Fourier Transform (STFT) is employed to transform the transient responses into two-dimensional spectral frame representation. A convolutional neural network is incorporated to distinguish between the damaged and undamaged states, as well as various types of damage of the laminated composites, by automatically extracting discriminative features from the vibration-based spectrograms. The CNN showed a classification accuracy of 90.1% on one healthy and 12 delaminated cases. The study of the confusion matrix of CNN provided further insights into the physics of the problem. The predictive performance of a pre-trained CNN classifier was also evaluated on unseen cases of delamination, and physically consistent results were obtained.

https://doi.org/10.1016/j.compositesb.2018.12.118

US patent 등록 “Apparatus and method for controlling vibration transfer between vibration devices”, US10152127

12월 20th, 2018 댓글이 없습니다.

Abstract
Provided is an apparatus and method for controlling a vibration transfer between vibration devices. The apparatus for controlling a vibration transfer may change vibration values of a plurality of vibration devices according to a movement of a virtual vibration body, thereby providing a user with a sense of touch of a movement of the virtual vibration body.

Inventors: Soo Chul Lim, Joon Ah Park

https://patents.google.com/patent/US10152127B2/en?oq=10152127

Journal Paper Accepted (IEEE Sensors Journal): Interaction Force Estimation using Camera and Electrical Current without Force/Torque Sensor

9월 6th, 2018 댓글이 없습니다.

Interaction Force Estimation using Camera and Electrical Current without Force/Torque Sensor

Dong-Han Lee ;  Wonjun Hwang ;  Soo-Chul Lim

Abstract:

In this paper, we propose a method for the estimation of the interaction forces between the motorized system and object through visual and electric information. In particular, we propose a new interaction force sensing method based on sequential images and the electrical current from the motor during the interaction between the system and environment to estimate the interaction force using deep learning. In the previous method, to measure the interaction force using only visual information, the prediction is inaccurate when the system interacts with an undeformable target, even though the aspect of the change appears small in the image. We use a neural network structure for estimating the interaction force from the time-series data of visual and electric information using deep learning, which combines the convolution neural network and long short-term memory models. From the evaluation to show the feasibility of the interaction force estimation, the proposed learning models successfully estimate the forces for four targets (rigid box, rigid box on sponge, sponge, and stapler), which are both deformable and undeformable objects. The proposed method demonstrates the best results in the interaction force estimation between the motorized system and object.
Published in: IEEE Sensors Journal ( Early Access )

US patent 등록 “Certification device and method using image sensor”, US10038867

9월 4th, 2018 댓글이 없습니다.
Patent number: 10038867
Abstract: A mobile device method for certifying a mobile device includes: generating first fixed pattern noise (FPN) information based on column FPN of an image sensor included in the mobile device; and controlling the mobile device to perform a certification by using the first FPN information.
Type: Grant
Filed: October 11, 2016
Date of Patent: July 31, 2018
Assignee: Samsung Electronics Co., Ltd.
Inventors: Seung-chan Kim, Jae Hyuk Choi, Soo Chul Lim, Joon Ah Park, Du-sik Park, Jung Soon Shin

Journal Paper 게재(Scientific Reports) : Mechanical Vibration Influences the Perception of Electrovibration

3월 15th, 2018 댓글이 없습니다.

Mechanical Vibration Influences the Perception of Electrovibration

Semin Ryu, Dongbum Pyo, Soo-Chul Lim & Dong-Soo Kwon

 

Abstract

Recently, various methods using, simultaneously, two types of tactile feedback have been proposed to emulate a real object. However, the possible masking effect when providing two types of tactile feedback has been scarcely reported. In this study, we investigated the masking effect caused by mechanical vibration on the perception of electrovibration. The absolute and difference thresholds of the electrovibration were measured according to the presence/absence, frequency, and intensity of the mechanical vibration. The absolute threshold of electrovibration tended to increase in the form of a ramp function, as the intensity of the masking stimulus (mechanical vibration) increased. Particularly, the masking effect was more remarkable when the frequency of both the target and the masking stimulus was the same (up to 13 dB increase with 25 dB SL masker). Furthermore, the difference in the threshold (average of 1.21 dB) did not significantly change due to the masking stimulus, when the sensation level intensity of the target stimulus was within the section following the Weber’s law. The results further indicated that electrovibration contributes to the activation of slowly adapting afferents as well. This investigation will provide important guidelines for the design of haptic interface that employs multiple types of tactile feedback.

 

Scientific Reportsvolume 8, Article number: 4555 (2018)

doi:10.1038/s41598-018-22865-x

 

https://www.nature.com/articles/s41598-018-22865-x

 

Journal Paper 게재(Sensors) : Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

2월 26th, 2018 댓글이 없습니다.

Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

Hyundo Choi 1, Keehong Seo 1, Seungyong Hyung 1, Youngbo Shim 1 and Soo-Chul Lim 2,*

Abstract
In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety action. Two FSR (force-sensitive resistors) sensors are used to measure the assistance force when the user is walking. The sensor system directly measures the interaction force between the exoskeleton and the lower limb of the user instead of a previously reported force-sensing method, which estimated the hip assistance force from the current of the motor and lookup tables. Furthermore, the sensor system has the advantage of generating torque in the walking-assistant actuator based on directly measuring the hip-assistance force. Thus, the gait-assistance exoskeleton system can control the delivered power and torque to the user. The force sensing structure is designed to decouple the force caused by hip motion from other directional forces to the sensor so as to only measure that force. We confirmed that the hip-assistance force could be measured with the proposed prototype compact force sensor attached to a thigh frame through an experiment with a real system.

 

Sensors 201818(2), 566; doi:10.3390/s18020566

http://www.mdpi.com/1424-8220/18/2/566

 

Prof. Lim received Young Researcher Award from Korea Haptics community

11월 6th, 2017 댓글이 없습니다.

Prof. Lim received young researcher Award from Korea Haptics Community.

KakaoTalk_20171106_092707585

지난 11월 3일 금요일 임수철 교수가 한국 햅틱스(Haptics) 연구회의 햅틱스 워크샵에서 젊은 연구자 상(Yong Researcher Award)을 수상했다. 한국 햅틱스 연구회는 촉각 분야를 연구하는 연구자들의 한국 협회로서 햅틱스 분야에 공헌 및 발전에 기여한 학회원을 대상으로 1명을 선발해 젊은 연구자 상을 수여한다.

Journal Paper 게재(Sensors) : Inferring Interaction Force from Visual Information without Using Physical Force Sensors

10월 30th, 2017 댓글이 없습니다.

Inferring Interaction Force from Visual Information without Using Physical Force Sensors

Wonjun Hwang, Soo-Chul Lim*

Sensors, 17(11), 2455, 2017

Abstract:

In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating the interaction force against a target object, where the shape of the object is changed by an external force. The force applied to the target can be estimated by means of the visual shape changes. However, the shape differences in the images are not very clear. To address this problem, we formulate a recurrent neural network-based deep model with fully-connected layers, which models complex temporal dynamics from the visual representations. Extensive evaluations show that the proposed learning models successfully estimate the interaction forces using only the corresponding sequential images, in particular in the case of three objects made of different materials, a sponge, a PET bottle, a human arm, and a tube. The forces predicted by the proposed method are very similar to those measured by force sensors.

http://www.mdpi.com/1424-8220/17/11/2455

US patent 등록 “User input method for use in portable device using virtual input area”, US 9727131

10월 23rd, 2017 댓글이 없습니다.

User input method for use in portable device using virtual input area

Patent number: 9727131
Abstract: A portable device and user input method of the portable device using a virtual input area is provided. The portable device may include a sensor configured to sense a user input to an input area, the input area being at least a portion of an area adjacent to the portable device, a determiner configured to determine a target object corresponding to the user input among at least one input object displayed on the portable device, based on an arrangement of the at least one input object, and a controller configured to generate a control command to control the target object.
Type: Grant
Filed:  October, 23, 2014
Date of Patent: Aug 8, 2017
Assignee: Samsung Electronics Co., Ltd.
Inventors: Soochul LIM, Joonah Park, Namjoon KIM, Du-sik Park, Jungsoon SHIN

US patent 등록 “Apparatus and method for adjusting holographic image” US9658596

6월 14th, 2017 댓글이 없습니다.
Patent number: 9658596
Abstract: A holographic object processing apparatus and method are provided. The holographic object processing apparatus may include a display device to output a holographic object, a database (DB) to store change information of the holographic object according to a distance between a control object and the holographic object, a distance measurement sensor to measure the distance between the control object and the holographic object, and a processing unit to extract change information corresponding to the measured distance from the DB and change the holographic object based on the extracted change information. The display device may output the changed holographic object.
Type: Grant
Filed: March 7, 2013
Date of Patent: May 23, 2017
Assignee: Samsung Electronics Co., Ltd.
Inventors: Seung Ju Han, Joon Ah Park, Bho Ram Lee, Hyun Jeong Lee, Soo Chul Lim

US Patent 등록, “Apparatus and method for measuring tactile information”, US9568379

2월 23rd, 2017 댓글이 없습니다.
Patent number: 9568379
Abstract: An apparatus and method for measuring a tactile information, using a material having variable pressure dependent properties is disclosed. The apparatus for measuring the tactile information may include a plurality of pressure measurement units to measure a magnitude of an external pressure using a material having variable properties, and a tactile information measurement unit to measure a three-dimensional (3D) tactile information based on the external pressure using a location of the plurality of pressure measurement units and a pressure measured by the plurality of pressure measurement units.
Type: Grant
Filed: November 8, 2013
Date of Patent: February 14, 2017
Assignees: Samsung Electronics Co., Ltd., Industry-Academic Cooperation Foundation, Yonsei University
Inventors: Soo-Chul Lim, Jong Baeg Kim, Joon Ah Park, Soon Jae Pyo, Min Ook Kim, Jae Ik Lee, Tae Young Chung

US Patent 등록, “Interface controlling apparatus and method using force”, US9519350

1월 1st, 2017 댓글이 없습니다.
Patent number: 9519350
Abstract: An interface controlling apparatus and method may generate content control information by analyzing force input information received from at least one force sensor, and may control content based on the content control information.
Type: Grant
Filed: September 4, 2013
Date of Patent: December 13, 2016
Assignee: Samsung Electronics Co., Ltd.
Inventors: Bho Ram Lee, Joon Ah Park, Hyun Jeong Lee, Soo Chul Lim, Hyung Kew Lee, Seung Ju Han

US Patent 등록, “Interface controlling apparatus and method using force”, US9501098

11월 25th, 2016 댓글이 없습니다.
Patent number: 9501098
Abstract: An interface controlling apparatus and method using a force may generate content control information by analyzing force input information received from at least one force sensor, and may control content based on the content control information.
Type: Grant
Filed: April 16, 2012
Date of Patent: November 22, 2016
Assignee: Samsung Electronics Co., Ltd.
Inventors: Bho Ram Lee, Joon Ah Park, Hyun Jeong Lee, Soo Chul Lim, Hyung Kew Lee, Seung Ju Han

US patent 등록, “Apparatus and method for user input”, US9495035

11월 22nd, 2016 댓글이 없습니다.
Patent number: 9495035
Abstract: A user input apparatus and method may measure, using a first sensor, surface input information that is applied to a surface of a user input apparatus, may measure, using a second sensor, orientation information that is input based on a physical quantity associated with a pose or a rotary motion of the user input apparatus, and may generate a content control signal, by combining the surface input information and the orientation information.
Type: Grant
Filed: January 21, 2016
Date of Patent: November 15, 2016
Assignee: Samsung Electronics Co., Ltd.
Inventors: Bhoram Lee, Joonah Park, Hyun Jeong Lee, Soo Chul Lim, Seung Ju Han