본문 바로가기
대메뉴 바로가기
KAIST
Newsletter Vol.25
Receive KAIST news by email!
View
Subscribe
Close
Type your e-mail address here.
Subscribe
Close
KAIST
NEWS
유틸열기
홈페이지 통합검색
-
검색
KOREAN
메뉴 열기
THE
by recently order
by view order
KAIST Awarded the IPBC R&D Institution Team of the Year
KAIST was awarded the R&D Institution Team of the Year during the annual IPBC (Intellectual Property Business Congress) Asia 2019 held in Tokyo October 28-30. IPBC is a conference dedicated to IP value creation strategies hosted by IAM Media, a world’s leading IP business media platform. IPBC Asia 2019 recognized the institutions and businesses that employed innovative IP strategies and management to produce the greatest IP value in 11 categories covering automotive, electronics, healthcare and biotechnology, internet and software, R&D institutions, semiconductors, industrials, mobile and telecommunications, Asia IP deals, Asia teams, and Asia individuals. This year, KAIST was recognized as one of the most active patentees in the Asia-Pacific region by significantly increasing its IP value through licensing and tech transfers. Associate Vice President Kyung Cheol Choi of the Office of University-Industry Cooperation remarked, “We are so delighted to prove the strong research capacity of KAIST. This will help us accomplish our vision of being a leading university that creates global impact.”
2019.12.04
View 6228
KAIST and Google Jointly Develop AI Curricula
KAIST selected the two professors who will develop AI curriculum under the auspices of the KAIST-Google Partnership for AI Education and Research. The Graduate School of AI announced the two authors among the 20 applicants who will develop the curriculum next year. They will be provided 7,500 USD per subject. Professor Changho Suh from the School of Electrical Engineering and Professor Yong-Jin Yoon from the Department of Mechanical Engineering will use Google technology such as TensorFlow, Google Cloud, and Android to create the curriculum. Professor Suh’s “TensorFlow for Information Theory and Convex Optimization “will be used for curriculum in the graduate courses and Professor Yoon’s “AI Convergence Project Based Learning (PBL)” will be used for online courses. Professor Yoon’s course will explore and define problems by utilizing AI and experiencing the process of developing products that use AI through design thinking, which involves product design, production, and verification. Professor Suh’s course will discus“information theory and convergence,” which uses basic sciences and engineering as well as AI, machine learning, and deep learning.
2019.12.04
View 10488
Gallium-Based Solvating Agent Efficiently Analyzes Optically Active Alcohols
A KAIST research team has developed a gallium-based metal complex enabling the rapid chiral analysis of alcohols. A team working under Professor Hyunwoo Kim reported the efficient new alcohol analysis method using nuclear magnetic resonance (NMR) spectroscopy in iScience. Enantiopure chiral alcohols are ubiquitous in nature and widely utilized as pharmaceuticals. This importance of chirality in synthetic and medicinal chemistry has advanced the search for rapid and facile methods to determine the enantiomeric purities of compounds. To date, chiral analysis has been performed using high-performance liquid chromatography (HPLC) with chiral columns. Along with the HPLC technique, chiral analysis using NMR spectroscopy has gained tremendous attention as an alternative to traditionally employed chromatographic methods due to its simplicity and rapid detection for real-time measurement. However, this method carries drawbacks such as line-broadening, narrow substrate scope, and poor resolution. Thus, compared with popular methods of chromatographic analysis, NMR spectroscopy is infrequently used for chiral analysis. In principle, a chiral solvating agent is additionally required for the NMR measurement of chiral alcohols to obtain two distinct signals. However, NMR analysis of chiral alcohols has been challenging due to weak binding interactions with chiral solvating agents. To overcome the intrinsic difficulty of relatively weak molecular interactions that are common for alcohols, many researchers have used multifunctional alcohols to enhance interactions with solvating agents. Instead, the KAIST team successfully varied the physical properties of metal complexes to induce stronger interactions with alcohols rather than the strategy of using multifunctional analytes, in the hopes of developing a universal chiral solvating agent for alcohols. Compared to the current method of chiral analysis used in the pharmaceutical industry, alcohols that do not possess chromophores can also be directly analyzed with the gallium complexes. Professor Kim said that this method could be a complementary chiral analysis technique at the industry level in the near future. He added that since the developed gallium complex can determine enantiomeric excess within minutes, it can be further utilized to monitor asymmetric synthesis. This feature will benefit a large number of researchers in the organic chemistry community, as well as the pharmaceutical industry. (Figure: Schematic view of the in-situ direct 1H NMR chiral analysis.) -Profile: Professor Hyunwoo Kim Department of Chemistry KAIST http://mdos.kaist.ac.kr hwk34@kaist.ac.kr For more on this article, please go to https://doi.org/10.1016/j.isci2019.07051
2019.11.14
View 9694
Ultrafast Quantum Motion in a Nanoscale Trap Detected
< Professor Heung-Sun Sim (left) and Co-author Dr. Sungguen Ryu (right) > KAIST researchers have reported the detection of a picosecond electron motion in a silicon transistor. This study has presented a new protocol for measuring ultrafast electronic dynamics in an effective time-resolved fashion of picosecond resolution. The detection was made in collaboration with Nippon Telegraph and Telephone Corp. (NTT) in Japan and National Physical Laboratory (NPL) in the UK and is the first report to the best of our knowledge. When an electron is captured in a nanoscale trap in solids, its quantum mechanical wave function can exhibit spatial oscillation at sub-terahertz frequencies. Time-resolved detection of such picosecond dynamics of quantum waves is important, as the detection provides a way of understanding the quantum behavior of electrons in nano-electronics. It also applies to quantum information technologies such as the ultrafast quantum-bit operation of quantum computing and high-sensitivity electromagnetic-field sensing. However, detecting picosecond dynamics has been a challenge since the sub-terahertz scale is far beyond the latest bandwidth measurement tools. A KAIST team led by Professor Heung-Sun Sim developed a theory of ultrafast electron dynamics in a nanoscale trap, and proposed a scheme for detecting the dynamics, which utilizes a quantum-mechanical resonant state formed beside the trap. The coupling between the electron dynamics and the resonant state is switched on and off at a picosecond so that information on the dynamics is read out on the electric current being generated when the coupling is switched on. NTT realized, together with NPL, the detection scheme and applied it to electron motions in a nanoscale trap formed in a silicon transistor. A single electron was captured in the trap by controlling electrostatic gates, and a resonant state was formed in the potential barrier of the trap. The switching on and off of the coupling between the electron and the resonant state was achieved by aligning the resonance energy with the energy of the electron within a picosecond. An electric current from the trap through the resonant state to an electrode was measured at only a few Kelvin degrees, unveiling the spatial quantum-coherent oscillation of the electron with 250 GHz frequency inside the trap. Professor Sim said, “This work suggests a scheme of detecting picosecond electron motions in submicron scales by utilizing quantum resonance. It will be useful in dynamical control of quantum mechanical electron waves for various purposes in nano-electronics, quantum sensing, and quantum information”. This work was published online at Nature Nanotechnology on November 4. It was partly supported by the Korea National Research Foundation through the SRC Center for Quantum Coherence in Condensed Matter. For more on the NTT news release this article, please visit https://www.ntt.co.jp/news2019/1911e/191105a.html -ProfileProfessor Heung-Sun Sim Department of PhysicsDirector, SRC Center for Quantum Coherence in Condensed Matterhttps://qet.kaist.ac.kr KAIST -Publication:Gento Yamahata, Sungguen Ryu, Nathan Johnson, H.-S. Sim, Akira Fujiwara, and Masaya Kataoka. 2019. Picosecond coherent electron motion in a silicon single-electron source. Nature Nanotechnology (Online Publication). 6 pages. https://doi.org/10.1038/s41565-019-0563-2
2019.11.05
View 15031
A Mathematical Model Reveals Long-Distance Cell Communication Mechanism
How can tens of thousands of people in a large football stadium all clap together with the same beat even though they can only hear the people near them clapping? A combination of a partial differential equation and a synthetic circuit in microbes answers this question. An interdisciplinary collaborative team of Professor Jae Kyoung Kim at KAIST, Professor Krešimir Josić at the University of Houston, and Professor Matt Bennett at Rice University has identified how a large community can communicate with each other almost simultaneously even with very short distance signaling. The research was reported at Nature Chemical Biology. Cells often communicate using signaling molecules, which can travel only a short distance. Nevertheless, the cells can also communicate over large distances to spur collective action. The team revealed a cell communication mechanism that quickly forms a network of local interactions to spur collective action, even in large communities. The research team used an engineered transcriptional circuit of combined positive and negative feedback loops in E. coli, which can periodically release two types of signaling molecules: activator and repressor. As the signaling molecules travel over a short distance, cells can only talk to their nearest neighbors. However, cell communities synchronize oscillatory gene expression in spatially extended systems as long as the transcriptional circuit contains a positive feedback loop for the activator. Professor Kim said that analyzing and understanding such high-dimensional dynamics was extremely difficult. He explained, “That’s why we used high-dimensional partial differential equation to describe the system based on the interactions among various types of molecules.” Surprisingly, the mathematical model accurately simulates the synthesis of the signaling molecules in the cell and their spatial diffusion throughout the chamber and their effect on neighboring cells. The team simplified the high-dimensional system into a one-dimensional orbit, noting that the system repeats periodically. This allowed them to discover that cells can make one voice when they lowered their own voice and listened to the others. “It turns out the positive feedback loop reduces the distance between moving points and finally makes them move all together. That’s why you clap louder when you hear applause from nearby neighbors and everyone eventually claps together at almost the same time,” said Professor Kim. Professor Kim added, “Math is a powerful as it simplifies complex thing so that we can find an essential underlying property. This finding would not have been possible without the simplification of complex systems using mathematics." The National Institutes of Health, the National Science Foundation, the Robert A. Welch Foundation, the Hamill Foundation, the National Research Foundation of Korea, and the T.J. Park Science Fellowship of POSCO supported the research. (Figure: Complex molecular interactions among microbial consortia is simplified as interactions among points on a limit cycle (right).)
2019.10.15
View 23293
Professor Byong-Guk Park Named Scientist of October
< Professor Byong-Guk Park > Professor Byong-Guk Park from the Department of Materials Science and Engineering was selected as the ‘Scientist of the Month’ for October 2019 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Park was recognized for his contributions to the advancement of spin-orbit torque (SOT)-based magnetic random access memory (MRAM) technology. He received 10 million KRW in prize money. A next-generation, non-volatile memory device MRAM consists of thin magnetic films. It can be applied in “logic-in-memory” devices, in which logic and memory functionalities coexist, thus drastically improving the performance of complementary metal-oxide semiconductor (CMOS) processors. Conventional MRAM technology is limited in its ability to increase the operation speed of a memory device while maintaining a high density. Professor Park tackled this challenge by introducing a new material, antiferromagnet (IrMn), that generates a sizable amount of SOT as well as an exchange-bias field, which makes successful data writing possible without an external magnetic field. This research outcome paved the way for the development of MRAM, which has a simple device structure but features high speeds and density. Professor Park said, “I feel rewarded to have forwarded the feasibility and applicability of MRAM. I will continue devoting myself to studying further on the development of new materials that can help enhance the performance of memory devices." (END)
2019.10.10
View 7560
Sungjoon Park Named Google PhD Fellow
PhD candidate Sungjoon Park from the School of Computing was named a 2019 Google PhD Fellow in the field of natural language processing. The Google PhD fellowship program has recognized and supported outstanding graduate students in computer science and related fields since 2009. Park is one of three Korean students chosen as the recipients of Google Fellowships this year. A total of 54 students across the world in 12 fields were awarded this fellowship. Park’s research on computational psychotherapy using natural language processing (NLP) powered by machine learning earned him this year’s fellowship. He presented of learning distributed representations in Korean and their interpretations during the 2017 Annual Conference of the Association for Computational Linguistics and the 2018 Conference on Empirical Methods in Natural Language Processing. He also applied machine learning-based natural language processing into computational psychotherapy so that a trained machine learning model could categorize client's verbal responses in a counseling dialogue. This was presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics. More recently, he has been developing on neural response generation model and the prediction and extraction of complex emotion in text, and computational psychotherapy applications.
2019.09.17
View 6507
Researchers Describe a Mechanism Inducing Self-Killing of Cancer Cells
(Professor Kim (left) and lead author Lee) Researchers have described a new mechanism which induces the self-killing of cancer cells by perturbing ion homeostasis. A research team from the Department of Biochemical Engineering has developed helical polypeptide potassium ionophores that lead to the onset of programmed cell death. The ionophores increase the active oxygen concentration to stress endoplasmic reticulum to the point of cellular death. The electrochemical gradient between extracellular and intracellular conditions plays an important role in cell growth and metabolism. When a cell’s ion homeostasis is disturbed, critical functions accelerating the activation of apoptosis are inhibited in the cell. Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death have been unclear and the bio-applicability has been limited. In the study featured at Advanced Science, the team presented an alpha helical peptide-based anticancer agent that is capable of transporting potassium ions with water solubility. The cationic, hydrophilic, and potassium ionic groups were combined at the end of the peptide side chain to provide both ion transport and hydrophilic properties. These peptide-based ionophores reduce the intracellular potassium concentration and at the same time increase the intracellular calcium concentration. Increased intracellular calcium concentrations produce intracellular reactive oxygen species, causing endoplasmic reticulum stress, and ultimately leading to apoptosis. Anticancer effects were evaluated using tumor-bearing mice to confirm the therapeutic effect, even in animal models. It was found that tumor growth was strongly inhibited by endoplasmic stress-mediated apoptosis. Lead author Dr. Dae-Yong Lee said, “A peptide-based ionophore is more effective than conventional chemotherapeutic agents because it induces apoptosis via elevated reactive oxygen species levels. Professor Yeu-Chun Kim said he expects this new mechanism to be widely used as a new chemotherapeutic strategy. This research was funded by the National Research Foundation.
2019.08.28
View 17553
President Shin Shares Innovation Strategy at Moscow
President Sung-Chul Shin shared the recipe for success for rapid national development through university education during the Island 10-22 Conference held at the Skolov Institute of Science and Technology in Moscow on July 16. President Shin stressed how urgent it is for higher education to rapidly embrace the new global economic environment brought about by the Fourth Industrial Revolution in his keynote address entitled ‘Roles and Responsibilities of Universities for Rapid National Development’. The Island 10-22 Conference is a summit co-organized by the National University of Science and Technology MISIS and University of the National Technological Initiative 2035 and supported by the Ministry of Science and Higher Education of the Russian Federation. More than 30 world-renowned experts, presidents of leading technological universities including President Peretz Lavie from the Israel Institute of Technology Technion, President Scott Pulsipher from Western Governors University and specialists in big data participated in the conference as speakers and discussed a diverse spectrum of ideas for making innovations and digital transformations in universities. More than 1,600 participants joined the conference. During his keynote speech, President Shin explained how Korea has achieved such rapid economic growth over the past half century. He cited the Korean government’s vision and innovation policies as factors leading to Korea’s phenomenal success. KAIST, one of the results of the Korean government’s innovation policy, led the nation to advanced technological breakthroughs in industries such as semiconductors. Such visionary policies and investments in science, technology, and education eventually made the Korea of today possible. President Shin said that KAIST distinguished itself through its new vision of C3 that fosters intellectual creativity, caring for others, and a challenging mind . Under Vision 2031, a blueprint for becoming a leading global university, President Shin said the KAIST continues to strive for innovations in convergent education,research and entreprenurship.
2019.07.18
View 5032
Mathematical Modeling Makes a Breakthrough for a New CRSD Medication
PhD Candidate Dae Wook Kim (Left) and Professor Jae Kyoung Kim (Right) - Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy - Mathematicians’ new modeling has identified major sources of interspecies and inter-individual variations in the clinical efficacy of a clock-modulating drug: photosensitivity and PER2 level. This enabled precision medicine for circadian disruption. A KAIST mathematics research team led by Professor Jae Kyoung Kim, in collaboration with Pfizer, applied a combination of mathematical modeling and simulation tools for circadian rhythms sleep disorders (CRSDs) to analyze the animal data generated by Pfizer. This study was reported in Molecular Systems Biology as the cover article on July 8. Pharmaceutical companies have conducted extensive studies on animals to determine the candidacy of this new medication. However, the results of animal testing do not always translate to the same effects in human trials. Furthermore, even between humans, efficacy differs across individuals depending on an individual’s genetic and environmental factors, which require different treatment strategies. To overcome these obstacles, KAIST mathematicians and their collaborators developed adaptive chronotherapeutics to identify precise dosing regimens that could restore normal circadian phase under different conditions. A circadian rhythm is a 24-hour cycle in the physiological processes of living creatures, including humans. A biological clock in the hypothalamic suprachiasmatic nucleus in the human brain sets the time for various human behaviors such as sleep. A disruption of the endogenous timekeeping system caused by changes in one’s life pattern leads to advanced or delayed sleep-wake cycle phase and a desynchronization between sleep-wake rhythms, resulting in CRSDs. To restore the normal timing of sleep, timing of the circadian clock could be adjusted pharmacologically. Pfizer identified PF-670462, which can adjust the timing of circadian clock by inhibiting the core clock kinase of the circadian clock (CK1d/e). However, the efficacy of PF-670462 significantly differs between nocturnal mice and diurnal monkeys, whose sleeping times are opposite. The research team discovered the source of such interspecies variations in drug response by performing thousands of virtual experiments using a mathematical model, which describes biochemical interactions among clock molecules and PF-670462. The result suggests that the effect of PF-670462 is reduced by light exposure in diurnal primates more than in nocturnal mice. This indicates that the strong counteracting effect of light must be considered in order to effectively regulate the circadian clock of diurnal humans using PF-670462. Furthermore, the team also found the source of inter-patients variations in drug efficacy using virtual patients whose circadian clocks were disrupted due to various mutations. The degree of perturbation in the endogenous level of the core clock molecule PER2 affects the efficacy. This explains why the clinical outcomes of clock-modulating drugs are highly variable and certain subtypes are unresponsive to treatment. Furthermore, this points out the limitations of current treatment strategies tailored to only the patient’s sleep and wake time but not to the molecular cause of sleep disorders. PhD candidate Dae Wook Kim, who is the first author, said that this motivates the team to develop an adaptive chronotherapy, which identifies a personalized optimal dosing time of day by tracking the sleep-wake up time of patients via a wearable device and allows for a precision medicine approach for CRSDs. Professor Jae Kyoung Kim said, "As a mathematician, I am excited to help enable the advancement of a new drug candidate, which can improve the lives of so many patients. I hope this result promotes more collaborations in this translational research.” This research was supported by a Pfizer grant to KAIST (G01160179), the Human Frontiers Science Program Organization (RGY0063/2017), and a National Research Foundation (NRF) of Korea Grant (NRF-2016 RICIB 3008468 and NRF-2017-Fostering Core Leaders of the Future Basic Science Program/ Global Ph.D. Fellowship Program). Figure 1. Interspecies and Inter-patients Variations in PF-670462 Efficacy Figure 2. Journal Cover Page Publication: Dae Wook Kim, Cheng Chang, Xian Chen, Angela C Doran, Francois Gaudreault, Travis Wager, George J DeMarco, and Jae Kyoung Kim. 2019. Systems approach reveals photosensitivity and PER2 level as determinants of clock-modulator efficacy. Molecular Systems Biology. EMBO Press, Heidelberg, Germany, Vol. 15, Issue No. 7, Article, 16 pages. https://doi.org/10.15252/msb.20198838 Profile: Prof. Jae Kyoung Kim, PhD jaekkim@kaist.ac.kr http://mathsci.kaist.ac.kr/~jaekkim Associate Professor Department of Mathematical Sciences Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Dae Wook Kim, PhD Candidate 0308kdo@kaist.ac.kr http://mathsci.kaist.ac.kr/~jaekkim PhD Candidate Department of Mathematical Sciences Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Dr. Cheng Chang, PhD cheng.chang@pfizer.com Associate Director of Clinical Pharmacology Clinical Pharmacology, Global Product Development Pfizer https://www.pfizer.com/ Groton 06340, USA (END)
2019.07.09
View 32920
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC) A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions. A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner. DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism. EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction. DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers. In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component. Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method. This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.” “DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim. Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT. Profile: -Professor Hyun Uk Kim (ehukim@kaist.ac.kr) https://sites.google.com/view/ehukim Department of Chemical and Biomolecular Engineering -Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr) Department of Chemical and Biomolecular Engineering http://mbel.kaist.ac.kr
2019.07.09
View 33669
Wearable Robot 'WalkON Suit' Off to Cybathlon 2020
Standing upright and walking alone are very simple but noble motions that separate humans from many other creatures. Wearable and prosthetic technologies have emerged to augment human function in locomotion and manipulation. However, advances in wearable robot technology have been especially momentous to Byoung-Wook Kim, a triplegic for 22 years following a devastating car accident. Kim rejoiced after standing upright and walking again by putting on the ‘WalkON Suit,’ the wearable robot developed by Professor Kyoungchul Kong’s team. Even more, Kim won third prize in the powered exoskeleton race at Cybathlon 2016, an international cyborg Olympics hosted by ETH Zurich. Now Kim and Professor Kong’s team are all geared up for the Cybathlon Championship 2020. Professor Kong and his startup, Angel Robotics, held a kickoff ceremony for Cybathlon 2020 at KAIST on June 24. The 2020 championship will take place in Switzerland. Only pilots with complete paralysis of the legs resulting from spinal cord injuries are eligible to participate in the Cybathlon, which takes place every four years. Pilots compete against each other while completing everyday tasks using technical assistance systems in six different disciplines: a brain-computer interface race, a functional electrical stimulation bike race, a powered arm prosthesis race, a powered leg prosthesis race, a powered exoskeleton race, and a powered wheelchair race. The 2016 championship drew 66 pilots from 56 teams representing 25 countries. In the powered exoskeleton race, pilots complete everyday activities such as getting up from a sofa and overcoming obstacles such as stairs, ramps, or slopes and up to four pilots compete simultaneously on tracks to solve six tasks; and the pilot that solves the most tasks in the least amount of time wins the race. (Kim, a triplegic for 22 years demonstrates walking and climbing the stairs (below photo) wearing the WalkOn Suit during the media day on June 21 at KAIST.) Kim, who demonstrated walking and climbing the stairs wearing the WalkON Suit during the media day for the Cybathlon 2020 kickoff ceremony on June 21 at KAIST, said, “I have been confined to a wheelchair for more than 20 years. I am used to it so I feel like the wheelchair is one of my body parts. Actually, I don’t feel any big difficulties in doing everyday tasks in wheelchair. But whenever I face the fact that I will never be able to stand up with my own two legs again, I am so devastated.” He continued, “I still remember the day when I stood up with my own two legs by myself after 22 years. It was beyond description.” The market for wearable robots, especially for exoskeleton robots, is continuing to grow as the aging population has been a major challenge in almost every advanced country. The global market for these robots expects to see annual growth of 41.2% to 8.3 billion US dollars by 2025. Healthcare wearable robots for the elderly and rehabilitation take up the half of the market share followed by wearable robots for industrial and defense purposes. Professor Kong from the Department of Mechanical Engineering and his colleagues have developed two wearable robot systems in 2014: The "WalkON Suit" for complete paraplegics and “Angel Suit” for those with partial impairment in walking ability such as the elderly and rehabilitation patients. Professor Kong said after 15 years of basic research, the team is now able to develop its own distinct technologies. He said their robots are powered by non-resistant precision drives with algorithms recognizing the user’s moving intention. Incorporated with prosthetic devices technology from the Severance Rehabilitation Hospital, their control technology has led to the production of a customizable robot suit optimized for each user’s physical condition. The WalkON Suit, which boasts a maximum force of 250 Nm and maximum rotation speed of 45 RPM, gives the user high-energy efficiency modeled after the physiology of the human leg. It allows users to walk on flat ground and down stairs, climb up and down inclines, and sit and lie down. Currently the battery lasts five to six hours for locomotion and the approximate 25 kg of robot weight still remains a technical challenge to upgrade. Professor Kong’s team has grafted AR glass technology into the WalkOn Suit that one of his pilots put on for the torch relay of the PyongChang Paralympics in 2018. His team is now upgrading the WalkON Suit 4.0 for next year’s competition. Severance Rehabilitation Hospital will help the seven pilots with their training. Professor Kong said his goal is to make robots that can make people with disabilities much more independent. He stressed, “Wearable robots should be designed for each single user. We provide a very good graphical user interface so that we can design, check, and also verify our optimized design for users’ best performance.” (Seven pilots and Professor Kong (fifth from left in second row) pose with guests who joined the Cybathlon 2020 kickoff ceremony. President Shin (fifth from right) made a congratulatory remarks during the ceremony.)
2019.06.25
View 37476
<<
첫번째페이지
<
이전 페이지
1
2
3
4
5
6
7
8
9
10
>
다음 페이지
>>
마지막 페이지 46