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Sumi Jo Performing Arts Research Center Opens
Distinguished visiting scholar soprano Sumi Jo gave a special lecture on May 13 at the KAIST auditorium. During the lecture, she talked about new technologies that will be introduced for future performing art stages while sharing some of the challenges she experienced before reaching to the stardom of the world stage. She also joined the KAIST student choral club ‘Chorus’ to perform the KAIST school song.
Professor Jo also opened the Sumi Jo Performing Arts Research Center on the same day along with President Kwang Hyung Lee and faculty members from the Graduate School of Culture Technology. The center will conduct AI and metaverse-based performing art technologies such as performer modeling via AI playing and motion creation, interactions between virtual and human players via sound analysis and motion recognition, as well as virtual stage and performing center modeling. The center will also carry out extensive stage production research applied to media convergence technologies.
Professor Juhan Nam, who heads the research center, said that the center is seeking collaborations with other universities such as Seoul National University and the Korea National University of Arts as well as top performing artists at home and abroad. He looks forward to the center growing into a collaborative center for future performing arts.
Professor Jo added that she will spare no effort to offer her experience and advice for the center’s future-forward performing arts research projects.
2022.05.16 View 4909 -
Professor Hyo-Sang Shin at Cranfield University Named the 18th Jeong Hun Cho Awardee
Professor Hyo-Sang Shin at Cranfield University in the UK was named the 18th Jeong Hun Cho Award recipient. PhD candidate Kyu-Sob Kim from the Department of Aerospace Engineering at KAIST, Master’s candidate from Korea University Kon-Hee Chang, Jae-Woo Chang from Kongju National University High School were also selected.
Professor Shin, a PhD graduate from the KAIST Department of Aerospace Engineering in 2016 works at Cranfield University. Professor Shin, whose main research focus covers guidance, navigation, and control, conducts research on information-based control. He has published 66 articles in SCI journals and presented approximately 70 papers at academic conference with more than 12 patent registrations. He is known for his expertise in areas related to unmanned aerospace systems and urban aero traffic automation. Professor Shin is participating in various aerospace engineering development projects run by the UK government.
The award recognizes promising young scientists who have made significant achievements in the field of aerospace engineering in honor of Jeong Hun Cho, the former PhD candidate in KAIST’s Department of Aerospace Engineering. Cho died in a lab accident in May 2003. Cho’s family endowed the award and scholarship to honor him and a recipient from each of his three alma maters (Kongju National High School, Korea University, and KAIST) are selected every year.
Professor Shin was awarded 25 million KRW in prize money. KAIST student Kim and Korea University student Chang received four million KRW while Kongju National University High School student Chang received three million KRW.
2022.05.16 View 4824 -
Professor Sang Su Lee’s Team Wins Seven iF Design Awards 2022
Professor Sang Su Lee from the Department of Industrial Design and his team’s five apps made in collaboration with NH Investment and Securities won iF Design Awards in the fields of UI, UX, service design, product design, and communication. These apps are now offered as NH Investment and Securities mobile applications.
The iF Design Awards recognize top quality creativity in product design, communication, packaging, service design and concepts, and architecture and interior design, as well as user experience (UX) and interface for digital media (UI).
In the field of UI, ‘Gretell’ is a mobile stock investment app service designed by Lee and his team to support investors struggling to learn about investing by archiving personalized information. Gretell provides investment information including news and reports. Users learn, evaluate, and leave comments. This shows both quantitative and qualitative indications, leading to rational decision-making. Other user’s comments are shared to reduce confirmation bias. Through this process, Gretell helps users who are impulsive or easily swayed by others’ opinions to grow as independent investors.
‘Bright’ is another app created by Lee’s team. It helps people exercise their rights as shareholders. As the need to exercise shareholders’ rights increases, many people are frustrated that investors with a small number of shares don’t have a lot of power. Bright provides a space for shareholders to share their opinions and brings people together so that individuals can be more proactive as shareholders. The Integrated Power of Attorney System (IPAS) expands the chances for shareholders to exercise their rights and allows users to submit proposals that can be communicated during the general meeting. Bright fosters influential shareholders, responsible companies, and a healthy society.
For communications, ‘Rewind’ is a stock information services app that visualizes past stock charts through sentiment analysis. Existing services focus on numbers, while Rewind takes a qualitative approach. Rewind analyzes public sentiment toward each event by collecting opinions on social media and then visualizes them chronologically along with the stock chart. Rewind allows users to review stock market movements and record their thoughts. Users can gain their own insights into current events in the stock market and make wiser investment decisions. The intuitive color gradient design provides a pleasant and simplified information experience.
In the area of interfaces for digital media and service design, ‘Groo’ is a green bond investing service app that helps users participate in green investment though investing in green bonds that support green projects for environmental improvement. Not restricted to trading bonds, Groo joins users in the holistic experience of green investing, from taking an interest in environmental issues to confirming the impact of the investment.
Next, ‘Modu’ is a story-based empathy expression training game for children with intellectual disabilities. Modu was developed to support emotion recognition and empathy behavior training in children with mild intellectual disabilities (MID) and borderline intellectual functioning (BIF).
Finally, the diving VR device for neutral buoyancy training, ‘Blow-yancy’, also made winner’s list. The device mimics scuba diving training without having to go into the water, therefore beginner divers are able getting feeling of diving while remaining perfectly safe and not harming any corals. It is expected that the device will be able to help protect at-risk underwater ecosystems.
2022.05.10 View 5992 -
Machine Learning-Based Algorithm to Speed up DNA Sequencing
The algorithm presents the first full-fledged, short-read alignment software that leverages learned indices for solving the exact match search problem for efficient seeding
The human genome consists of a complete set of DNA, which is about 6.4 billion letters long. Because of its size, reading the whole genome sequence at once is challenging. So scientists use DNA sequencers to produce hundreds of millions of DNA sequence fragments, or short reads, up to 300 letters long. Then the DNA sequencer assembles all the short reads like a giant jigsaw puzzle to reconstruct the entire genome sequence. Even with very fast computers, this job can take hours to complete.
A research team at KAIST has achieved up to 3.45x faster speeds by developing the first short-read alignment software that uses a recent advance in machine-learning called a learned index.
The research team reported their findings on March 7, 2022 in the journal Bioinformatics. The software has been released as open source and can be found on github (https://github.com/kaist-ina/BWA-MEME).
Next-generation sequencing (NGS) is a state-of-the-art DNA sequencing method. Projects are underway with the goal of producing genome sequencing at population scale. Modern NGS hardware is capable of generating billions of short reads in a single run. Then the short reads have to be aligned with the reference DNA sequence. With large-scale DNA sequencing operations running hundreds of next-generation sequences, the need for an efficient short read alignment tool has become even more critical. Accelerating the DNA sequence alignment would be a step toward achieving the goal of population-scale sequencing. However, existing algorithms are limited in their performance because of their frequent memory accesses.
BWA-MEM2 is a popular short-read alignment software package currently used to sequence the DNA. However, it has its limitations. The state-of-the-art alignment has two phases – seeding and extending. During the seeding phase, searches find exact matches of short reads in the reference DNA sequence. During the extending phase, the short reads from the seeding phase are extended. In the current process, bottlenecks occur in the seeding phase. Finding the exact matches slows the process.
The researchers set out to solve the problem of accelerating the DNA sequence alignment. To speed the process, they applied machine learning techniques to create an algorithmic improvement. Their algorithm, BWA-MEME (BWA-MEM emulated) leverages learned indices to solve the exact match search problem. The original software compared one character at a time for an exact match search. The team’s new algorithm achieves up to 3.45x faster speeds in seeding throughput over BWA-MEM2 by reducing the number of instructions by 4.60x and memory accesses by 8.77x. “Through this study, it has been shown that full genome big data analysis can be performed faster and less costly than conventional methods by applying machine learning technology,” said Professor Dongsu Han from the School of Electrical Engineering at KAIST.
The researchers’ ultimate goal was to develop efficient software that scientists from academia and industry could use on a daily basis for analyzing big data in genomics. “With the recent advances in artificial intelligence and machine learning, we see so many opportunities for designing better software for genomic data analysis. The potential is there for accelerating existing analysis as well as enabling new types of analysis, and our goal is to develop such software,” added Han.
Whole genome sequencing has traditionally been used for discovering genomic mutations and identifying the root causes of diseases, which leads to the discovery and development of new drugs and cures. There could be many potential applications. Whole genome sequencing is used not only for research, but also for clinical purposes. “The science and technology for analyzing genomic data is making rapid progress to make it more accessible for scientists and patients. This will enhance our understanding about diseases and develop a better cure for patients of various diseases.”
The research was funded by the National Research Foundation of the Korean government’s Ministry of Science and ICT.
-PublicationYoungmok Jung, Dongsu Han, “BWA-MEME:BWA-MEM emulated with a machine learning approach,” Bioinformatics, Volume 38, Issue 9, May 2022
(https://doi.org/10.1093/bioinformatics/btac137)
-ProfileProfessor Dongsu HanSchool of Electrical EngineeringKAIST
2022.05.10 View 6940 -
VP Sang Yup Lee Receives Honorary Doctorate from DTU
Vice President for Research, Distinguished Professor Sang Yup Lee at the Department of Chemical & Biomolecular Engineering, was awarded an honorary doctorate from the Technical University of Denmark (DTU) during the DTU Commemoration Day 2022 on April 29. The event drew distinguished guests, students, and faculty including HRH The Crown Prince Frederik Andre Henrik Christian and DTU President Anders Bjarklev.
Professor Lee was recognized for his exceptional scholarship in the field of systems metabolic engineering, which led to the development of microcell factories capable of producing a wide range of fuels, chemicals, materials, and natural compounds, many for the first time.
Professor Lee said in his acceptance speech that KAIST’s continued partnership with DTU in the field of biotechnology will lead to significant contributions in the global efforts to respond to climate change and promote green growth.
DTU CPO and CSO Dina Petronovic Nielson, who heads DTU Biosustain, also lauded Professor Lee saying, “It is not only a great honor for Professor Lee to be induced at DTU but also great honor for DTU to have him.”
Professor Lee also gave commemorative lectures at DTU Biosustain in Lingby and the Bio Innovation Research Institute at the Novo Nordisk Foundation in Copenhagen while in Denmark.
DTU, one of the leading science and technology universities in Europe, has been awarding honorary doctorates since 1921, including to Nobel laureate in chemistry Professor Frances Arnold at Caltech. Professor Lee is the first Korean to receive an honorary doctorate from DTU.
2022.05.03 View 7529 -
President-Elect Suk-Yeol Yoon Meets and Talks with KAIST Students
President-Elect Yoon stresses science and technology-powered economic growth during his visit to KAIST
Korean President-elect Suk-Yeol Yoon stressed that semiconductors are the key strategical industry that will take the lead during the fourth industrial revolution powered by AI and data during a meeting with KAIST graduate students on April 29. President-elect Yoon promised systemic policy support for making science and technology breakthroughs possible and better rewarding young researchers who are devoted to advances in R&D during his meeting at KAIST.
Before he met with the students, he toured the National Nanofab Center, which is affiliated with KAIST, and was briefed on the center’s role and responsibilities.
President-elect Yoon, who will take office on May 10, said that the best way to ensure prompt growth in Korea’s aging society hinges on advances in science and technology. “All-out investments in science and technology will help us move forward to improve people’s quality of life and lessen the social divide,” he explained.
Eight Master’s and PhD candidates majoring in nuclear engineering, AI robotics, semiconductors, electrical engineering, aerospace, and bioengineering attended the meeting with President-elect Yoon. The students asked for help dealing with the challenges they are experiencing while researching and called for deregulation in the process of forming startups.
PhD candidate Jae Wan Cho from the Department Nuclear and Quantum Engineering stressed the importance of energy security. He asked for the prompt development of new types of nuclear reactors such as small modular reactors, adding, “Korea has very excellent technologies in nuclear plant construction and parts manufacturing, but lags behind in the new types of nuclear reactors. This sector will develop new energy markets and create synergy along with the shipbuilding industry, which will emerge as new pillars of our export.”
Student entrepreneurs such as PhD candidate Kwang Min Kim from the Department of Bio and Brain Engineering and PhD candidate Dong Yoon Shin from the Department of Mechanical and Aerospace Engineering asked for more deregulation in the process of creating startups. PhD candidate Dong Hon Lee from the School of Electrical Engineering pointed out the insecure future caused by the ‘special research fellow system,’ where the number of fellows who have been designated alternative military service has drastically decreased.
2022.05.02 View 4595 -
LightPC Presents a Resilient System Using Only Non-Volatile Memory
Lightweight Persistence Centric System (LightPC) ensures both data and execution persistence for energy-efficient full system persistence
A KAIST research team has developed hardware and software technology that ensures both data and execution persistence. The Lightweight Persistence Centric System (LightPC) makes the systems resilient against power failures by utilizing only non-volatile memory as the main memory.
“We mounted non-volatile memory on a system board prototype and created an operating system to verify the effectiveness of LightPC,” said Professor Myoungsoo Jung. The team confirmed that LightPC validated its execution while powering up and down in the middle of execution, showing up to eight times more memory, 4.3 times faster application execution, and 73% lower power consumption compared to traditional systems.
Professor Jung said that LightPC can be utilized in a variety of fields such as data centers and high-performance computing to provide large-capacity memory, high performance, low power consumption, and service reliability.
In general, power failures on legacy systems can lead to the loss of data stored in the DRAM-based main memory. Unlike volatile memory such as DRAM, non-volatile memory can retain its data without power. Although non-volatile memory has the characteristics of lower power consumption and larger capacity than DRAM, non-volatile memory is typically used for the task of secondary storage due to its lower write performance. For this reason, nonvolatile memory is often used with DRAM. However, modern systems employing non-volatile memory-based main memory experience unexpected performance degradation due to the complicated memory microarchitecture.
To enable both data and execution persistent in legacy systems, it is necessary to transfer the data from the volatile memory to the non-volatile memory. Checkpointing is one possible solution. It periodically transfers the data in preparation for a sudden power failure. While this technology is essential for ensuring high mobility and reliability for users, checkpointing also has fatal drawbacks. It takes additional time and power to move data and requires a data recovery process as well as restarting the system.
In order to address these issues, the research team developed a processor and memory controller to raise the performance of non-volatile memory-only memory. LightPC matches the performance of DRAM by minimizing the internal volatile memory components from non-volatile memory, exposing the non-volatile memory (PRAM) media to the host, and increasing parallelism to service on-the-fly requests as soon as possible.
The team also presented operating system technology that quickly makes execution states of running processes persistent without the need for a checkpointing process. The operating system prevents all modifications to execution states and data by keeping all program executions idle before transferring data in order to support consistency within a period much shorter than the standard power hold-up time of about 16 minutes. For consistency, when the power is recovered, the computer almost immediately revives itself and re-executes all the offline processes immediately without the need for a boot process.
The researchers will present their work (LightPC: Hardware and Software Co-Design for Energy-Efficient Full System Persistence) at the International Symposium on Computer Architecture (ISCA) 2022 in New York in June. More information is available at the CAMELab website (http://camelab.org).
-Profile: Professor Myoungsoo Jung Computer Architecture and Memory Systems Laboratory (CAMEL)http://camelab.org School of Electrical EngineeringKAIST
2022.04.25 View 20730 -
Professor Lik-Hang Lee Offers Metaverse Course for Hong Kong Productivity Council
Professor Lik-Hang Lee from the Department of Industrial System Engineering will offer a metaverse course in partnership with the Hong Kong Productivity Council (HKPC) from the Spring 2022 semester to Hong Kong-based professionals.
“The Metaverse Course for Professionals” aims to nurture world-class talents of the metaverse in response to surging demand for virtual worlds and virtual-physical blended environments. The HKPC’s R&D scientists, consultants, software engineers, and related professionals will attend the course. They will receive a professional certificate on managing and developing metaverse skills upon the completion of this intensive course.
The course will provide essential skills and knowledge about the parallel virtual universe and how to leverage digitalization and industrialization in the metaverse era. The course includes comprehensive modules, such as designing and implementing virtual-physical blended environments, metaverse technology and ecosystems, immersive smart cities, token economies, and intelligent industrialization in the metaverse era.
Professor Lee believes in the decades to come that we will see rising numbers of virtual worlds in cyberspace known as the ‘Immersive Internet’ that will be characterized by high levels of immersiveness, user interactivity, and user-machine collaborations.
“Consumers in virtual worlds will create novel content as well as personalized products and services, becoming as catalyst for ‘hyperpersonalization’ in the next industrial revolution,” he said.
Professor Lee said he will continue offering world-class education related to the metaverse to students in KAIST and professionals from various industrial sectors, as his Augmented Reality and Media Lab will focus on a variety of metaverse topics such as metaverse campuses and industrial metaverses.
The HKPC has worked to address innovative solutions for Hong Kong industries and enterprises since 1967, helping them achieve optimized resource utilization, effectiveness, and cost reduction as well as enhanced productivity and competitiveness in both local and international markets. The HKPC has advocated for facilitating Hong Kong’s reindustrialization powered by Industry 4.0 and e-commerce 4.0 with a strong emphasis on R&D, IoT, AI, digital manufacturing.
The Augmented Reality and Media Lab led by Professor Lee will continue its close partnerships with HKPC and its other partners to help build the epicentre of the metaverse in the region. Furthermore, the lab will fully leverage its well-established research niches in user-centric, virtual-physical cyberspace (https://www.lhlee.com/projects-8 ) to serve upcoming projects related to industrial metaverses, which aligns with the departmental focus on smart factories and artificial intelligence.
2022.04.06 View 6312 -
Distinguished Professor Sukbok Chang Named the 2022 Ho-Am Laureate
Distinguished Professor Sukbok Chang from the Department of Chemistry was named the awardee of the Ho-Am Prize in the fields of chemistry and life sciences. The award has recognized the most distinguished scholars, individuals, and organizations in physics and mathematics, chemistry and life sciences, engineering, medicine, arts, and community service in honor of the late founder of Samsung Group Byong-Chul Lee, whose penname is Ho-Am. The awards ceremony will be held on May 31 and awardees will receive 300 million KRW in prize money.
Professor Chang became the fourth KAIST Ho-Am laureate following Distinguished Professor Sang Yup Lee in engineering in 2014, Distinguished Professor Jun Ho Oh in engineering in 2016, and Distinguished Professor Gou Young Koh in medicine in 2018.
Professor Chang is a renowned chemist who has made pioneering research in the area of transition metal catalysis for organic transformations. Professor Chang is also one of the Highly Cited Researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. He has made the list seven years in a row from 2016.
Professor Chang has developed a range of new and impactful C-H bond functionalization reactions. By using his approaches, value-added molecules can be readily produced from chemical feedstocks, representatively hydrocarbons and (hetero)arenes. His research team elucidated fundamental key mechanistic aspects in the course of the essential C-H bond activation process of unreactive starting materials. He was able to utilize the obtained mechanistic understanding for the subsequent catalyst design to develop more efficient and highly (stereo)selective catalytic reactions.
Among the numerous contributions he made, the design of new mechanistic approaches toward metal nitrenoid transfers are of especially high impact to the chemical community. Indeed, a series of important transition metal catalyst systems were developed by Professor Chang to enable the direct and selective C-H amidation of unreactive organic compounds, thereby producing aminated compounds that have important applicability in synthetic, medicinal, and materials science. He has also pioneered in the area of asymmetric C-H amination chemistry by creatively devising various types of chiral transition metal catalyst systems, and his team proved for the first time that chiral lactam compounds can be obtained at an excellent level of stereoselectivity.
Another significant contribution of Professor. Chang was the introduction of dioxazolones as a robust but highly reactive source of acyl nitrenoids for the catalytic C-H amidation reactions, and this reagent is now broadly utilized in synthetic chemistry worldwide.
Professor Chang also leads a research group in the Center for Catalytic Hydrocarbon Functionalizations at the Institute for Basic Science.
2022.04.06 View 6014 -
Mathematicians Identify a Key Source of Cell-to-Cell Variability in Cell Signaling
Systematic inferences identify a major source of heterogeneity in cell signaling dynamics
Why do genetically identical cells respond differently to the same external stimuli, such as antibiotics? This long-standing mystery has been solved by KAIST and IBS mathematicians who have developed a new framework for analyzing cell responses to some stimuli. The team found that the cell-to-cell variability in antibiotic stress response increases as the effective length of the cell signaling pathway (i.e., the number of rate-limiting steps) increases. This finding could identify more effective chemotherapies to overcome the fractional killing of cancer cells caused by cell-to-cell variability.
Cells in the human body contain signal transduction systems that respond to various external stimuli such as antibiotics and changes in osmotic pressure. When an external stimulus is detected, various biochemical reactions occur sequentially. This leads to the expression of relevant genes, allowing the cells to respond to the perturbed external environment. Furthermore, signal transduction leads to a drug response (e.g., antibiotic resistance genes are expressed when antibiotic drugs are given).
However, even when the same external stimuli are detected, the responses of individual cells are greatly heterogeneous. This leads to the emergence of persister cells that are highly resistant to drugs. To identify potential sources of this cell-to cell variability, many studies have been conducted. However, most of the intermediate signal transduction reactions are unobservable with current experimental techniques.
A group of researchers including Dae Wook Kim and Hyukpyo Hong and led by Professor Jae Kyoung Kim from the KAIST Department of Mathematical Sciences and IBS Biomedical Mathematics Group solved the mystery by exploiting queueing theory and Bayesian inference methodology. They proposed a queueing process that describes the signal transduction system in cells. Based on this, they developed Bayesian inference computational software using MBI (the Moment-based Bayesian Inference method). This enables the analysis of the signal transduction system without a direct observation of the intermediate steps. This study was published in Science Advances.
By analyzing experimental data from Escherichia coli using MBI, the research team found that cell-to-cell variability increases as the number of rate-limiting steps in the signaling pathway increases.
The rate-limiting steps denote the slowest steps (i.e., bottlenecks) in sequential biochemical reaction steps composing cell signaling pathways and thus dominates most of the signaling time. As the number of the rate-limiting steps increases, the intensity of the transduced signal becomes greatly heterogeneous even in a population of genetically identical cells. This finding is expected to provide a new paradigm for studying the heterogeneous antibiotic resistance of cells, which is a big challenge in cancer medicine.
Professor Kim said, “As a mathematician, I am excited to help advance the understanding of cell-to-cell variability in response to external stimuli. I hope this finding facilitates the development of more effective chemotherapies.”
This work was supported by the Samsung Science and Technology Foundation, the National Research Foundation of Korea, and the Institute for Basic Science.
-Publication:Dae Wook Kim, Hyukpyo Hong, and Jae Kyoung Kim (2022) “Systematic inference identifies a major source of heterogeneity in cell signaling dynamics: the rate-limiting step number,”Science Advances March 18, 2022 (DOI: 10.1126/sciadv.abl4598)
-Profile:Professor Jae Kyoung Kimhttp://mathsci.kaist.ac.kr/~jaekkim
jaekkim@kaist.ac.kr@umichkim on TwitterDepartment of Mathematical SciencesKAIST
2022.03.29 View 7216 -
Baemin CEO Endows a Scholarship in Honor of the Late Professor Chwa
CEO Beom-Jun Kim of Woowa Brothers also known as ‘Baemin,’ a leading meal delivery app company, made a donation of 100 million KRW in honor of the late Professor Kyong-Yong Chwa from the School of Computing who passed away last year. The fund will be established for the “Kyong-Yong Chwa - Beom-Jun Kim Scholarship” to provide scholarships for four students over five years.
Kim finished his BS in 1997 and MS in 1999 at the School of Computing and Professor Chwa was his advisor. The late Professor Chwa was a pioneering scholar who brought the concept of computer algorithms to Korea. After graduating from Seoul National University in electric engineering, Professor Chwa earned his PhD at Northwestern University and began teaching at KAIST in 1980. Professor Chwa served as the President of the Korean Institute of Information Scientists and Engineers and a fellow emeritus at the Korean Academy of Science and Technology.
Professor Chwa encouraged younger students to participate in international computer programming contests. Under his wing, Team Korea, which was comprised of four high school students, including Kim, placed fourth in the International Olympiad Informatics (IOI). Kim, who participated in the contest as high school junior, won an individual gold medal in the fourth IOI competition in 1992. Since then, Korean students have actively participated in many competitions including the International Collegiate Programming Contest (ICPC) hosted by the Association for Computing Machinery.
Kim said, “I feel fortunate to have met so many good friends and distinguished professors. With them, I had opportunities to grow. I would like to provide such opportunities to my juniors at KAIST. Professor Chwa was a larger than life figure in the field of computer programming. He was always caring and supported us with a warm heart. I want this donation to help carry on his legacy for our students and for them to seek greater challenges and bigger dreams.”
2022.03.25 View 5821 -
Decoding Brain Signals to Control a Robotic Arm
Advanced brain-machine interface system successfully interprets arm movement directions from neural signals in the brain
Researchers have developed a mind-reading system for decoding neural signals from the brain during arm movement. The method, described in the journal Applied Soft Computing, can be used by a person to control a robotic arm through a brain-machine interface (BMI).
A BMI is a device that translates nerve signals into commands to control a machine, such as a computer or a robotic limb. There are two main techniques for monitoring neural signals in BMIs: electroencephalography (EEG) and electrocorticography (ECoG).
The EEG exhibits signals from electrodes on the surface of the scalp and is widely employed because it is non-invasive, relatively cheap, safe and easy to use. However, the EEG has low spatial resolution and detects irrelevant neural signals, which makes it difficult to interpret the intentions of individuals from the EEG.
On the other hand, the ECoG is an invasive method that involves placing electrodes directly on the surface of the cerebral cortex below the scalp. Compared with the EEG, the ECoG can monitor neural signals with much higher spatial resolution and less background noise. However, this technique has several drawbacks.
“The ECoG is primarily used to find potential sources of epileptic seizures, meaning the electrodes are placed in different locations for different patients and may not be in the optimal regions of the brain for detecting sensory and movement signals,” explained Professor Jaeseung Jeong, a brain scientist at KAIST. “This inconsistency makes it difficult to decode brain signals to predict movements.”
To overcome these problems, Professor Jeong’s team developed a new method for decoding ECoG neural signals during arm movement. The system is based on a machine-learning system for analysing and predicting neural signals called an ‘echo-state network’ and a mathematical probability model called the Gaussian distribution.
In the study, the researchers recorded ECoG signals from four individuals with epilepsy while they were performing a reach-and-grasp task. Because the ECoG electrodes were placed according to the potential sources of each patient’s epileptic seizures, only 22% to 44% of the electrodes were located in the regions of the brain responsible for controlling movement.
During the movement task, the participants were given visual cues, either by placing a real tennis ball in front of them, or via a virtual reality headset showing a clip of a human arm reaching forward in first-person view. They were asked to reach forward, grasp an object, then return their hand and release the object, while wearing motion sensors on their wrists and fingers. In a second task, they were instructed to imagine reaching forward without moving their arms.
The researchers monitored the signals from the ECoG electrodes during real and imaginary arm movements, and tested whether the new system could predict the direction of this movement from the neural signals. They found that the novel decoder successfully classified arm movements in 24 directions in three-dimensional space, both in the real and virtual tasks, and that the results were at least five times more accurate than chance. They also used a computer simulation to show that the novel ECoG decoder could control the movements of a robotic arm.
Overall, the results suggest that the new machine learning-based BCI system successfully used ECoG signals to interpret the direction of the intended movements. The next steps will be to improve the accuracy and efficiency of the decoder. In the future, it could be used in a real-time BMI device to help people with movement or sensory impairments.
This research was supported by the KAIST Global Singularity Research Program of 2021, Brain Research Program of the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning, and the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education.
-PublicationHoon-Hee Kim, Jaeseung Jeong, “An electrocorticographic decoder for arm movement for brain-machine interface using an echo state network and Gaussian readout,” Applied SoftComputing online December 31, 2021 (doi.org/10.1016/j.asoc.2021.108393)
-ProfileProfessor Jaeseung JeongDepartment of Bio and Brain EngineeringCollege of EngineeringKAIST
2022.03.18 View 9164