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‘WalkON Suit 4’ Releases Paraplegics from Wheelchairs
- KAIST Athletes in ‘WalkON Suit 4’ Dominated the Cybathlon 2020 Global Edition. - Paraplegic athletes Byeong-Uk Kim and Joohyun Lee from KAIST’s Team Angel Robotics won a gold and a bronze medal respectively at the Cybathlon 2020 Global Edition last week. ‘WalkON Suit 4,’ a wearable robot developed by the Professor Kyoungchul Kong’s team from the Department of Mechanical Engineering topped the standings at the event with double medal success. Kim, the former bronze medallist, clinched his gold medal by finishing all six tasks in 3 minutes and 47 seconds, whereas Lee came in third with a time of 5 minutes and 51 seconds. TWIICE, a Swiss team, lagged 53 seconds behind Kim’s winning time to be the runner-up. Cybathlon is a global championship, organized by ETH Zurich, which brings together people with physical disabilities to compete using state-of-the-art assistive technologies to perform everyday tasks. The first championship was held in 2016 in Zurich, Switzerland. Due to the COVID-19 pandemic, the second championship was postponed twice and held in a new format in a decentralized setting. A total of 51 teams from 20 countries across the world performed the events in their home bases in different time zones instead of traveling to Zurich. Under the supervision of a referee and timekeeper, all races were filmed and then reviewed by judges. KAIST’s Team Angel Robotics participated in the Powered Exoskeleton Race category, where nine pilots representing five nations including Korea, Switzerland, the US, Russia, and France competed against each other. The team installed their own arena and raced at the KAIST Main Campus in Daejeon according to the framework, tasks, and rules defined by the competition committee. The two paraplegic pilots were each equipped with exoskeletal devices, the WalkON Suit 4, and undertook six tasks related to daily activities. The WalkON Suit 4 recorded the fastest walking speed for a complete paraplegic ever reported. For a continuous walk, it achieved a maximum speed of 40 meters per minute. This is comparable to the average walking pace of a non-disabled person, which is around two to four kilometers per hour. The research team raised the functionality of the robot by adding technology that can observe the user’s level of anxiety and external factors like the state of the walking surface, so it can control itself intelligently. The assistive functions a robot should provide vary greatly with the environment, and the WalkON Suit 4 made it possible to analyze the pace of the user within 30 steps and provide a personally optimized walking pattern, enabling a high walking speed. The six tasks that Kim and Lee had to complete were:1) sitting and standing back up, 2) navigating around obstacles while avoiding collisions, 3) stepping over obstacles on the ground, 4) going up and down stairs, 5) walking across a tilted path, and 6) climbing a steep slope, opening and closing a door, and descending a steep slope. Points were given based on the accuracy of each completed task, and the final scores were calculated by adding all of the points that were gained in each attempt, which lasted 10 minutes. Each pilot was given three opportunities and used his/her highest score. Should pilots have the same final score, the pilot who completed the race in the shortest amount of time would win. Kim said in his victory speech that he was so thrilled to see all his and fellow researchers’ years of hard work paying off. “This will be a good opportunity to show how outstanding Korean wearable robot technologies are,” he added. Lee, who participated in the competition for the first time, said, “By showing that I can overcome my physical disabilities with robot technology, I’d like to send out a message of hope to everyone who is tired because of COVID-19”. Professor Kong’s team collaborated in technology development and pilot training with their colleagues from Angel Robotics Co., Ltd., Severance Rehabilitation Hospital, Yeungnam University, Stalks, and the Institute of Rehabilitation Technology. Footage from the competition is available at the Cybathlon’s official website. (END)
2020.11.20
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KAIST Showcases Healthcare Technologies at K-Hospital Fair 2020
KAIST Pavilion showcased its innovative medical and healthcare technologies and their advanced applications at the K-Hospital Fair 2020. Five KAIST research groups who teamed up for the Post-COVID-19 New Deal R&D Initiative Project participated in the fair held in Seoul last week. The K-Hospital Fair is a yearly event organized by the Korean Hospital Association to present the latest research and practical innovations to help the medical industry better serve the patients. This year, 120 healthcare organizations participated in the fair and operated 320 booths. At the fair, a research group led by Professor Il-Doo Kim from the Department of Materials Science and Engineering demonstrated the manufacturing process of orthogonal nanofibers used to develop their ‘recyclable nano-fiber filtered face mask’ introduced in March of this year. This mask has garnered immense international attention for maintaining its sturdy frame and filtering function even after being washed more than 20 times. Professor Kim is now extending his facilities for the mass production of this mask at his start-up company. While awaiting final approval from the Ministry of Food and Drug Safety to bring his product into the market, Professor Kim is developing other mask variations such as eco-friendly biodegradable masks and transparent masks to aid the hearing-impaired who rely on lip reading to communicate. The team working under Professor Wonho Choe from the Department of Nuclear and Quantum Engineering presented two low-temperature plasma sterilizers for medical use, co-developed with Plasmapp, a start-up company founded by a KAIST alumnus. Their sterilizers are the first ones that can sterilize medical devices by diffusing hydrogen peroxide vapor into the pouch. They rapidly sterilize medical instruments and materials in just seven minutes without leaving toxic residue, while reducing sterilization time and costs by 90%. Professor Hyung-Soon Park and his researchers from the Department of Mechanical Engineering introduced a smart protective suit ventilation system that features high cooling capacity and a slimmed-down design. For comfortable use, the suit is equipped with a technique that monitors its inner temperature and humidity and automatically controls its inner circulation accordingly. The group also presented a new system that helps a person in a contaminated suit undress without coming into contact with the contaminated outer part of the suit. Professor Jong Chul Ye's group from the Department of Bio and Brain Engineering demonstrated AI software that can quickly diagnose an infectious disease based on chest X-ray imaging. The technique compares the differences in the severity of pneumonia in individual patients to distinguish whether their conditions fall under viral pneumonia including COVID-19, bacterial pneumonia, tuberculosis, other diseases, or normal conditions. The AI software visualizes the basis of its reasoning for each of the suspected diseases and provides them as information that can be utilized by medical personnel. Finally, researchers of Professor Ki-Hun Jeong’s team from the Department of Bio and Brain Engineering demonstrated their ultra-high-speed sub-miniature molecular diagnostic system for the on-site diagnosis of diseases. The existing Polymerase Chain Reaction (PCR) diagnostic usually takes from 30 minutes to an hour to provide results, but their new technique using an LED light source can present results within just three minutes and it is expected to be used actively for on-site diagnosis. Professor Choongsik Bae, the Director of the Post-COVID-19 New Deal R&D Initiative Project, said, “KAIST will build a healthy relationship amongst researchers, enterprises, and hospitals to contribute to the end of COVID-19 and build a new paradigm of Korean disease prevention and control.” KAIST launched the Post-COVID-19 New Deal R&D Initiative in July with the support of the Ministry of Science and ICT of Korea. This unit was created to overcome the pandemic crisis by using science and technology, and to contribute to economic development by creating a new antiviral drug industry. The unit is comprised of 464 KAIST members including professors, researchers, and students as well as 503 professionals from enterprises, hospitals, and research centers. (END)
2020.10.26
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Scientist of October: Professor Jungwon Kim
Professor Jungwon Kim from the Department of Mechanical Engineering was selected as the ‘Scientist of the Month’ for October 2020 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Kim was recognized for his contributions to expanding the horizons of the basics of precision engineering through his research on multifunctional ultrahigh-speed, high-resolution sensors. He received 10 million KRW in prize money. Professor Kim was selected as the recipient of this award in celebration of “Measurement Day”, which commemorates October 26 as the day in which King Sejong the Great established a volume measurement system. Professor Kim discovered that the time difference between the pulse of light created by a laser and the pulse of the current produced by a light-emitting diode was as small as 100 attoseconds (10-16 seconds). He then developed a unique multifunctional ultrahigh-speed, high-resolution Time-of-Flight (TOF) sensor that could take measurements of multiple points at the same time by sampling electric light. The sensor, with a measurement speed of 100 megahertz (100 million vibrations per second), a resolution of 180 picometers (1/5.5 billion meters), and a dynamic range of 150 decibels, overcame the limitations of both existing TOF techniques and laser interferometric techniques at the same time. The results of this research were published in Nature Photonics on February 10, 2020. Professor Kim said, “I’d like to thank the graduate students who worked passionately with me, and KAIST for providing an environment in which I could fully focus on research. I am looking forward to the new and diverse applications in the field of machine manufacturing, such as studying the dynamic phenomena in microdevices, or taking ultraprecision measurement of shapes for advanced manufacturing.” (END)
2020.10.15
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Slippery When Wet: Fish and Seaweed Inspire Ships to Reduce Fluid Friction
Faster ships could be on the horizon after KAIST scientists develop a slippery surface inspired by fish and seaweed to reduce the hull's drag through the water. Long-distance cargo ships lose a significant amount of energy due to fluid friction. Looking to the drag reduction mechanisms employed by aquatic life can provide inspiration on how to improve efficiency. Fish and seaweed secrete a layer of mucus to create a slippery surface, reducing their friction as they travel through water. A potential way to mimic this is by creating lubricant-infused surfaces covered with cavities. As the cavities are continuously filled with the lubricant, a layer is formed over the surface. Though this method has previously been shown to work, reducing drag by up to 18%, the underlying physics is not fully understood. KAIST researchers in collaboration with a team of researchers from POSTECH conducted simulations of this process to help explain the effects, and their findings were published in the journal Physics of Fluids on September 15. The group looked at the average speed of a cargo ship with realistic material properties and simulated how it behaves under various lubrication setups. Specifically, they monitored the effects of the open area of the lubricant-filled cavities, as well as the thickness of the cavity lids. They found that for larger open areas, the lubricant spreads more than it does with smaller open areas, leading to a slipperier surface. On the other hand, the lid thickness does not have much of an effect on the slip, though a thicker lid does create a thicker lubricant buildup layer. Professor Emeritus Hyung Jin Sung from the KAIST Department of Mechanical Engineering who led this study said, “Our investigation of the hydrodynamics of a lubricant layer and how it results in drag reduction with a slippery surface in a basic configuration has provided significant insight into the benefits of a lubricant-infused surface.” Now that they have worked on optimizing the lubricant secretion design, the authors hope it can be implemented in real-life marine vehicles. “If the present design parameters are adopted, the drag reduction rate will increase significantly,” Professor Sung added. This work was supported by the National Research Foundation (NRF) of Korea. Source: Materials provided by American Institute of Physics. Publication: Kim, Seung Joong, et al. (2020). A lubricant-infused slip surface for drag reduction. Physics of Fluids. Available online at https://doi.org/10.1063/5.0018460 Profile: Hyung Jin Sung Professor Emeritus hyungjin@kaist.ac.kr http://flow.kaist.ac.kr/index.php Flow Control Lab. (FCL) Department of Mechanical Engineering http://kaist.ac.kr Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea (END)
2020.10.12
View 7194
Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis. Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %. Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room. Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image. To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else. In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places. The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances. The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment. In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer. The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image. A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms. Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff." This study was conducted in collaboration with SM Instruments Inc. Profile: Yong-Hwa Park, Ph.D. Associate Professor yhpark@kaist.ac.kr http://human.kaist.ac.kr/ Human-Machine Interaction Laboratory (HuMaN Lab.) Department of Mechanical Engineering (ME) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr/en/ Daejeon 34141, Korea Profile: Gyeong Tae Lee PhD Candidate hansaram@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Seong Hu Kim PhD Candidate tjdgnkim@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Hyeonuk Nam PhD Candidate frednam@kaist.ac.kr HuMaN Lab., ME, KAIST Profile: Young-Key Kim CEO sales@smins.co.kr http://en.smins.co.kr/ SM Instruments Inc. Daejeon 34109, Korea (END)
2020.08.13
View 15661
Hubo Debuts as a News Anchor
HUBO, a humanoid robot developed by Professor Jun-Ho Oh’s team, made its debut as a co-anchor during the TJB prime time news 8 on May 14. “Un-contact" became the new normal after Covid-19 and many business solutions are being transformed using robotics. HUBO made two news reports on contactless services using robots in medical, manufacturing, and logistics industries. HUBO 2, the second generation of HUBO, appeared as a special anchor on the local broadcasting network’s special program in celebration of its 25th anniversary. HUBO is the champion of the 2015 DARPA Robotics Challenge held in the USA. Its FX-2 riding robot also participated in the Olympic torch relay during the 2018 PyeongChang Winter Olympics. Click here to watch a full video of HUBO anchoring the news. (END)
2020.05.14
View 11572
Professor Sukyung Park Named Presidential Science and Technology Adviser
Professor Sukyung Park from the Department of Mechanical Engineering was appointed as the science and technology adviser to the President Jae-in Moon on May 4. Professor Park, at the age of 47, became the youngest member of the president’s senior aide team at Chong Wa Dae. A Chong Wa Dae spokesman said on May 4 while announcing the appointment, “Professor Park, a talent with a great deal of policymaking participation in science and technology, will contribute to accelerating the government’s push for science and technology innovation, especially in the information and communications technology (ICT) sector.” Professor Park joined KAIST in 2004 as the first female professor of mechanical engineering. She is a biomechanics expert who has conducted extensive research on biometric mechanical behaviors. Professor Park is also a member of the KAIST Board of Trustees. Before that, she served as a senior researcher at the Korea Institute of Machinery and Materials (KIMM) as well as a member of the Presidential Advisory Council on Science and Technology. After graduating from Seoul Science High School as the first ever two-year graduate, Professor Park earned a bachelor and master’s degrees in mechanical engineering at KAIST. She then finished her Ph.D. from the University of Michigan. (END)
2020.05.06
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Wearable Strain Sensor Using Light Transmittance Helps Measure Physical Signals Better
KAIST researchers have developed a novel wearable strain sensor based on the modulation of optical transmittance of a carbon nanotube (CNT)-embedded elastomer. The sensor is capable of sensitive, stable, and continuous measurement of physical signals. This technology, featured in the March 4th issue of ACS Applied Materials & Interfaces as a front cover article, shows great potential for the detection of subtle human motions and the real-time monitoring of body postures for healthcare applications. A wearable strain sensor must have high sensitivity, flexibility, and stretchability, as well as low cost. Those used especially for health monitoring should also be tied to long-term solid performance, and be environmentally stable. Various stretchable strain sensors based on piezo-resistive and capacitive principles have been developed to meet all these requirements. Conventional piezo-resistive strain sensors using functional nanomaterials, including CNTs as the most common example, have shown high sensitivity and great sensing performance. However, they suffer from poor long-term stability and linearity, as well as considerable signal hysteresis. As an alternative, piezo-capacitive strain sensors with better stability, lower hysteresis, and higher stretchability have been suggested. But due to the fact that piezo-capacitive strain sensors exhibit limited sensitivity and strong electromagnetic interference caused by the conductive objects in the surrounding environment, these conventional stretchable strain sensors are still facing limitations that are yet to be resolved. A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering suggested that an optical-type stretchable strain sensor can be a good alternative to resolve the limitations of conventional piezo-resistive and piezo-capacitive strain sensors, because they have high stability and are less affected by environmental disturbances. The team then introduced an optical wearable strain sensor based on the light transmittance changes of a CNT-embedded elastomer, which further addresses the low sensitivity problem of conventional optical stretchable strain sensors. In order to achieve a large dynamic range for the sensor, Professor Park and his researchers chose Ecoflex as an elastomeric substrate with good mechanical durability, flexibility, and attachability on human skin, and the new optical wearable strain sensor developed by the research group actually shows a wide dynamic range of 0 to 400%. In addition, the researchers propagated the microcracks under tensile strain within the film of multi-walled CNTs embedded in the Ecoflex substrate, changing the optical transmittance of the film. By doing so, it was possible for them to develop a wearable strain sensor having a sensitivity 10 times higher than conventional optical stretchable strain sensors. The proposed sensor has also passed the durability test with excellent results. The sensor’s response after 13,000 sets of cyclic loading was stable without any noticeable drift. This suggests that the sensor response can be used without degradation, even if the sensor is repeatedly used for a long time and in various environmental conditions. Using the developed sensor, the research team could measure the finger bending motion and used it for robot control. They also developed a three-axes sensor array for body posture monitoring. The sensor was able to monitor human motions with small strains such as a pulse near the carotid artery and muscle movement around the mouth during pronunciation. Professor Park said, “In this study, our group developed a new wearable strain sensor platform that overcomes many limitations of previously developed resistive, capacitive, and optical-type stretchable strain sensors. Our sensor could be widely used in a variety of fields including soft robotics, wearable electronics, electronic skin, healthcare, and even entertainment.” This work was supported by the National Research Foundation (NRF) of Korea. Publication: Jimin Gu, Donguk Kwon, Junseong Ahn, and Inkyu Park. (2020) “Wearable Strain sensors Using Light Transmittance Change of Carbon Nanotube-Embedded Elastomers with Microcracks” ACS Applied Materials & Interfaces. Volume 12. Issue 9. Available online at https://doi.org/10.1021/acsami.9b18069 Profile: Inkyu Park Professor inkyu@kaist.ac.kr http://mintlab1.kaist.ac.kr Micro/Nano Transducers Laboratory (MINT Lab) Department of Mechanical Engineering (ME)Korea Advanced Institute of Science and Technology (KAIST) Profile: Jimin Gu Ph.D. Candidate mint9411@kaist.ac.kr http://mintlab1.kaist.ac.kr MINT Lab KAIST ME (END)
2020.03.20
View 17959
‘OSK Rising Stars 30’ Recognizes Four KAISTians
Four KAISTians were selected as star researchers to brighten the future of optics in commemoration of the 30th anniversary of the Optical Society of Korea (OSK). As ‘OSK Rising Stars 30’, the OSK named 27 domestic researchers under the age of 40 who have made significant contributions and will continue contributing to the development of Korea’s optics academia and industry. Professor YongKeun Park from the Department of Physics was selected in recognition of his contributions to the field of biomedical optics. Professor Park focuses on developing novel optical methods for understanding, diagnosing, and treating human diseases, based on light scattering, light manipulation, and interferometry. As a member of numerous international optics societies including the OSA and the SPIE and a co-founder of two start-up companies, Professor Park continues to broaden his boundaries as a leading opticist and entrepreneur. Professor Jonghwa Shin from the Department of Materials Science and Engineering was recognized for blazing a trail in the field of broadband metamaterials. Professor Shin’s research on the broadband enhancement of the electric permittivity and refractive index of metamaterials has great potential in both academia and industry. Professor Hongki Yoo from the Department of Mechanical Engineering is expected to create a significant ripple effect in the diagnosis of cardiovascular disorders through the development of new optical imaging techniques and applications. Finally, Dr. Sejeong Kim, a KAIST graduate and a Chancellor’s postdoctoral research fellow at the University of Technology Sydney (UTS), was acknowledged for her optical device research utilizing two-dimensional materials. Dr. Kim’s research at UTS now focuses on the introduction of micro/nano cavities for new materials. (END)
2020.03.16
View 11055
A System Controlling Road Active Noise to Hit the Road
The research team led by Professor Youngjin Park of the Department of Mechanical Engineering has developed a road noise active noise control (RANC) system to be commercialized in partnership with Hyundai Motor Group. On December 11, Hyundai Motor Group announced the successful development of the RANC system, which significantly reduces the road noise flowing into cars. The carmaker has completed the domestic and American patent applications for the location of sensors and the signal selection method, the core technology of RANC. RANC is a technology for reducing road noise during driving. This system consists of an acceleration sensor, digital signal processor (the control computer to analyze sound signals), microphone, amplifier, and audio system. To make the system as simple as possible, the audio system utilizes the original audio system embedded in the car instead of a separate system. The acceleration sensor first calculates the vibration from the road into the car. The location of the sensor is important for accurately identifying the vibration path. The research team was able to find the optimal sensor location through a number of tests. The System Dynamics and Applied Control Laboratory of Professor Park researched ways to significantly reduce road noise with Hyundai Motor Group for four years from 1993 as a G7 national project and published the results in international journals. In 2002, the researchers published an article titled “Noise Quietens Driving” in Nature, where they announced the first success in reducing road noise in actual cars. The achievement did not lead to commercialization, however, due to the lack of auxiliary technologies at the time, digital amplifiers and DSP for cars for example, and pricing issues. Since 2013, Professor Park’s research team has participated in one technology transfer and eight university-industry projects. Based on these efforts, the team was able to successfully develop the RANC system with domestic technology in partnership with Hyundai’s NVH Research Lab (Research Fellow, Dr. Gangdeok Lee; Ph.D. in aviation engineering, 1996), Optomech (Founder, Professor Gyeongsu Kim; Ph.D. in mechanical engineering, 1999), ARE (CEO Hyeonseok Kim; Ph.D. in mechanical engineering, 1998), WeAcom, and BurnYoung. Professor Park’s team led the project by performing theory-based research during the commercialization stage in collaboration with Hyundai Motor Group. For the commercialization of the RANC system, Hyundai Motor Group is planning to collaborate with the global car audio company Harman to increase the degree of completion and apply the RANC system to the GV 80, the first SUV model of the Genesis brand. “I am very delighted as an engineer to see the research I worked on from my early days at KAIST be commercialized after 20 years,” noted Professor Park. “I am thrilled to make a contribution to such commercialization with my students in my lab.”
2019.12.27
View 11264
Professor Sung Yong Kim Elected as the Chair of PICES MONITOR
< Professor Sung Yong Kim > Professor Sung Yong Kim from the Department of Mechanical Engineering was elected as the chair of the Technical Committee on Monitoring (MONITOR) of the North Pacific Marine Science Organization (PICES). PICES is an intergovernmental marine science organization that was established in 1992 through a collaboration between six North Pacific nations including South Korea, Russia, the United States, Japan, China, and Canada to exchange and discuss research on the Pacific waters. Its headquarters is located in Canada and the organization consists of seven affiliated maritime science and marine technology committees. Professor Kim was elected as the chair of the technical committee that focuses on monitoring and will be part of the Science Board as an ex-officio member. His term will last three years from November 2019. Professor Kim was recognized for his academic excellence, expertise, and leadership among oceanographers both domestically and internationally. Professor Kim will also participate as an academia civilian committee member of the Maritime and Fisheries Science and Technology Committee under the Korean Ministry of Oceans and Fisheries for two years from December 18, 2019. He stated, “I will give my full efforts to broaden Korean oceanography research by participating in maritime leadership positions at home and abroad, and help South Korea become a maritime powerhouse.” (END)
2019.12.22
View 9258
New Liquid Metal Wearable Pressure Sensor Created for Health Monitoring Applications
Soft pressure sensors have received significant research attention in a variety of fields, including soft robotics, electronic skin, and wearable electronics. Wearable soft pressure sensors have great potential for the real-time health monitoring and for the early diagnosis of diseases. A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering developed a highly sensitive wearable pressure sensor for health monitoring applications. This work was reported in Advanced Healthcare Materials on November 21 as a front cover article. This technology is capable of sensitive, precise, and continuous measurement of physiological and physical signals and shows great potential for health monitoring applications and the early diagnosis of diseases. A soft pressure sensor is required to have high compliance, high sensitivity, low cost, long-term performance stability, and environmental stability in order to be employed for continuous health monitoring. Conventional solid-state soft pressure sensors using functional materials including carbon nanotubes and graphene have showed great sensing performance. However, these sensors suffer from limited stretchability, signal drifting, and long-term instability due to the distance between the stretchable substrate and the functional materials. To overcome these issues, liquid-state electronics using liquid metal have been introduced for various wearable applications. Of these materials, Galinstan, a eutectic metal alloy of gallium, indium, and tin, has great mechanical and electrical properties that can be employed in wearable applications. But today’s liquid metal-based pressure sensors have low-pressure sensitivity, limiting their applicability for health monitoring devices. The research team developed a 3D-printed rigid microbump array-integrated, liquid metal-based soft pressure sensor. With the help of 3D printing, the integration of a rigid microbump array and the master mold for a liquid metal microchannel could be achieved simultaneously, reducing the complexity of the manufacturing process. Through the integration of the rigid microbump and the microchannel, the new pressure sensor has an extremely low detection limit and enhanced pressure sensitivity compared to previously reported liquid metal-based pressure sensors. The proposed sensor also has a negligible signal drift over 10,000 cycles of pressure, bending, and stretching and exhibited excellent stability when subjected to various environmental conditions. These performance outcomes make it an excellent sensor for various health monitoring devices. First, the research team demonstrated a wearable wristband device that can continuously monitor one’s pulse during exercise and be employed in a noninvasive cuffless BP monitoring system based on PTT calculations. Then, they introduced a wireless wearable heel pressure monitoring system that integrates three 3D-BLiPS with a wireless communication module. Professor Park said, “It was possible to measure health indicators including pulse and blood pressure continuously as well as pressure of body parts using our proposed soft pressure sensor. We expect it to be used in health care applications, such as the prevention and the monitoring of the pressure-driven diseases such as pressure ulcers in the near future. There will be more opportunities for future research including a whole-body pressure monitoring system related to other physical parameters.” This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT. < Figure 1. The front cover image of Advanced Healthcare Materials, Volume 8, Issue 22. > < Figure 2. Highly sensitive liquid metal-based soft pressure sensor integrated with 3D-printed microbump array. > < Figure 3. High pressure sensitivity and reliable sensing performances of the proposed sensor and wireless heel pressure monitoring application. > -ProfileProfessor Inkyu ParkMicro/Nano Transducers Laboratoryhttp://mintlab1.kaist.ac.kr/ Department of Mechanical EngineeringKAIST
2019.12.20
View 13697
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