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KAIST Team Wins IEEE RA-L Best Paper Award for Second Year in a Row
A research team led by Professor Jee-Hwan Ryu of the Department of Civil and Environmental Engineering at KAIST has received the Best Paper Award from IEEE Robotics and Automation Letters (RA-L), one of the world's most prestigious journals in robotics, for the second consecutive year.
KAIST(President Kwang Hyung Lee) announced on June 22 that Professor Ryu's team received the award during ICRA 2026, held in Vienna, Austria, with the award ceremony taking place on June 4. Following its recognition in 2025, the team has now achieved the rare distinction of winning the RA-L Best Paper Award in two consecutive years, underscoring the global competitiveness and sustained impact of KAIST's soft robotics research.
The RA-L Best Paper Award is presented annually to a select group of papers demonstrating outstanding scientific contribution, technical originality, experimental rigor, and future impact. This year, only five papers were selected from more than 1,700 papers published in IEEE Robotics and Automation Letters during 2025.
The award-winning paper, titled “Self-Wearing Adaptive Garments via Soft Robotic Unfurling,” presents a novel assistive dressing technology in which garments autonomously unfold and move along the user's body using soft robotic principles. The research was led by Dr. Namgyun Kim of KAIST in collaboration with the research group of Professor Allison M. Okamura at Stanford University.
Conventional dressing-assistance systems often rely on external robotic devices and complex control systems, which can restrict user movement and comfort. In contrast, the KAIST team incorporated the core principles of soft growing robots into garment structures, enabling the clothing itself to gently unfold and assist the wearer without requiring a separate external robotic manipulator.
The researchers integrated a pneumatic eversion mechanism into lightweight and flexible garments. When pressurized, the structure gradually unfolds along the user's body, providing reliable dressing assistance while maintaining safety and compliance. The soft robotic architecture is particularly advantageous for applications involving direct human contact, as it minimizes physical burden and reduces the need for sophisticated control systems.
The team developed and evaluated multiple garment prototypes, including sleeves, jackets, and pants. Experimental results demonstrated that the garments could reliably unfold along the user's body, reducing physical effort during dressing while maintaining safe interaction forces.
This work highlights how soft growing robotics can expand beyond traditional applications such as locomotion, exploration, and manipulation to directly support activities of daily living. The technology has strong potential for assistive applications for older adults, people with disabilities, and rehabilitation patients, while also opening new directions for wearable robotics, rehabilitation engineering, and human-robot interaction.
“This second consecutive award demonstrates the sustained global competitiveness of KAIST robotics research,” said Professor Jee-Hwan Ryu. “Our work extends the core principles of soft growing robots into assistive dressing technologies that can directly improve daily life. We will continue developing safe, flexible, and human-centered robotic technologies.”
The paper was published in IEEE Robotics and Automation Letters on November 19, 2025.
Paper Title: Self-Wearing Adaptive Garments via Soft Robotic Unfurling DOI: 10.1109/LRA.2025.3634909
2026.06.22 View 1042 -
Humanoid Robot Pilot PIBOT Wins Best Paper Award at the World’s Most Prestigious Robotics Magazine
< (From left of the award recipients) Ph. D candidate Sungjae Min, Ph. D candidate Gyuree Kang, Professor David Hyunchul Shim, Ph.D candidate Hyungjoo Kim >
KAIST announced on June 5th that a paper proposing an aircraft autonomous piloting framework based on the humanoid robot pilot ‘PIBOT,’ developed by a research team led by Professor David Hyunchul Shim of the School of Electrical Engineering, was selected as the Best Paper Award among the papers published in the IEEE Robotics & Automation Magazine (IEEE RAM) in 2025.
< The proposed PIBOT system framework capable of piloting based on aviation manuals and voice communication without modifying existing aircraft >
This award is highly meaningful as it signifies that grassroots research based entirely on domestic, independent initiatives has been recognized as a world-class achievement in robotics. The award ceremony took place in Vienna, Austria, on June 4, 2026 (local time) during the International Conference on Robotics and Automation (ICRA 2026). IEEE Robotics & Automation Magazine (IEEE RAM) is a prestigious academic magazine published by the IEEE Robotics and Automation Society (RAS), under the umbrella of IEEE, the world's largest technical professional organization. It is well known for delivering the latest research achievements, industry trends, and tutorials in the fields of robotics and automation, widely conveying robot technologies applicable to actual industrial sites to researchers in both industry and academia. As of 2025, IEEE RAM recorded an Impact Factor (IF) of 7.1, holding the second highest impact among IEEE publications in the field of robotics. In particular, it presents the Best Paper Award to research that has a significant academic and industrial impact among the papers published after undergoing rigorous peer review. This study was selected as a Future Challenge Defense Technology Research and Development Project by the Agency for Defense Development (ADD) in 2021 and was conducted based purely on domestic technology with support of approximately 5.7 billion won over five years. The research team received high praise for implementing Physical AI technology at an exceptionally high level, enabling a humanoid robot to systematically and adaptively perform complex tasks such as piloting aircraft based on artificial intelligence, going beyond simple walking or carrying items. Recently, humanoid robot technology has been developing rapidly in terms of athletic performance, such as tumbling or implementing complex movements. However, in the industrial sector, the applicability to actual industrial sites is drawing attention as a more critical factor. The pilot robot ‘PIBOT’ being developed by Professor David Hyunchul Shim's research team is designed to acquire specialized knowledge required for aircraft operation and to recognize and respond to actual flight situations in real time, going beyond simple repetitive tasks or logistics processing. Accordingly, it is evaluated as presenting a new direction for the utilization of humanoid robot technology, termed as Expert Physical AI.
< The research team's PIBOT sitting in an actual aircraft (KLA-100) and operating the instruments and control stick >
The research team has successfully completed Phase 1 of the research since the project launched in 2021, and since 2024, they have been developing Phase 2 of the pilot robot, which features a human-like physique and joint structure suitable for actual aircraft piloting. In addition, they are pursuing collaborative research with relevant organizations to expand and apply this technology to various mobile vehicle piloting fields, such as ground vehicles and ships, as well as aircraft.
< PIBOT performing piloting in an aircraft simulator device >
Professor David Hyunchul Shim said, “It is very meaningful that the pilot robot technology, proposed for the first time in the world by Korean researchers, has been recognized as a world-class research achievement thanks to the support of a large-scale national project. We will further develop our research in a direction where humanoid robots can help humans in real-world environments and safely operate complex systems.” In this study, PhD students Sungjae Min, Gyuree Kang, and Hyungjoo Kim participated as co-first authors, and Professor David Hyunchul Shim served as the corresponding author. The paper can be found through IEEE Xplore. ※ Paper Title: “Toward Fully Autonomous Aviation: PIBOT, a Humanoid Robot Pilot for Human-Centric Aircraft Cockpits”, Paper Links: https://doi.org/10.1109/MRA.2024.3505774, https://ieeexplore.ieee.org/document/10798973/ Meanwhile, this research was conducted with support from the Agency for Defense Development's Future Challenge Defense Technology Research and Development Project.
2026.06.05 View 1070 -
KAIST Predicts Human Group Behavior with AI! 1st Place at the World’s Top Conference… Major Success after 23 Years
<(From Left) Ph.D candidate Geon Lee, Ph.D candidate Minyoung Choe, M.S candidate Jaewan Chun, Professor Kijung Shin, M.S candidate Seokbum Yoon>
KAIST (President Kwang Hyung Lee) announced on the 9th of December that Professor Kijung Shin’s research team at the Kim Jaechul Graduate School of AI has developed a groundbreaking AI technology that predicts complex social group behavior by analyzing how individual attributes such as age and role influence group relationships.
With this technology, the research team achieved the remarkable feat of winning the Best Paper Award at the world-renowned data mining conference “IEEE ICDM,” hosted by the Institute of Electrical and Electronics Engineers (IEEE). This is the highest honor awarded to only one paper out of 785 submissions worldwide, and marks the first time in 23 years that a Korean university research team has received this award, once again demonstrating KAIST’s technological leadership on the global research stage.
Today, group interactions involving many participants at the same time—such as online communities, research collaborations, and group chats—are rapidly increasing across society. However, there has been a lack of technology that can precisely explain both how such group behavior is structured and how individual characteristics influence it at the same time.
To overcome this limitation, Professor Kijung Shin’s research team developed an AI model called “NoAH (Node Attribute-based Hypergraph Generator),” which realistically reproduces the interplay between individual attributes and group structure.
NoAH is an artificial intelligence that explains and imitates what kinds of group behaviors emerge when people’s characteristics come together. For example, it can analyze and faithfully reproduce how information such as a person’s interests and roles actually combine to form group behavior.
As such, NoAH is an AI that generates “realistic group behavior” by simultaneously reflecting human traits and relationships. It was shown to reproduce various real-world group behaviors—such as product purchase combinations in e-commerce, the spread of online discussions, and co-authorship networks among researchers—far more realistically than existing models.
< The process of generating group interactions using NoAH >
Professor Kijung Shin stated, “This study opens a new AI paradigm that enables a richer understanding of complex interactions by considering not only the structure of groups but also individual attributes together,” and added, “Analyses of online communities, messengers, and social networks will become far more precise.”
This research was conducted by a team consisting of Professor Kijung Shin and KAIST Kim Jaechul Graduate School of AI students: master’s students Jaewan Chun and Seokbum Yoon, and doctoral students Minyoung Choe and Geon Lee, and was presented at IEEE ICDM on November 18.
※ Paper title: “Attributed Hypergraph Generation with Realistic Interplay Between Structure and Attributes” Original paper: https://arxiv.org/abs/2509.21838
< Photo from the award ceremony held on November 14 at the International Spy Museum in Washington, D.C.>
Meanwhile, including this award-winning paper, Professor Shin’s research team presented a total of four papers at IEEE ICDM this year. In addition, in 2023, the team also received the Best Student Paper Runner-up (4th place) at the same conference.
This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. RS-202400457882, AI Research Hub Project) (RS-2019-II190075, Artificial Intelligence Graduate School Program (KAIST)) (No. RS-2022-II220871, Development of AI Autonomy and Knowledge Enhancement for AI Agent Collaboration).
2025.12.09 View 3918 -
KAIST Professor Jee-Hwan Ryu Receives Global IEEE Robotics Journal Best Paper Award
- Professor Jee-Hwan Ryu of Civil and Environmental Engineering receives the Best Paper Award from the Institute of Electrical and Electronics Engineers (IEEE) Robotics Journal, officially presented at ICRA, a world-renowned robotics conference.
- This is the highest level of international recognition, awarded to only the top 5 papers out of approximately 1,500 published in 2024.
- Securing a new working channel technology for soft growing robots expands the practicality and application possibilities in the field of soft robotics.
< Professor Jee-Hwan Ryu (left), Nam Gyun Kim, Ph.D. Candidate (right) from the KAIST Department of Civil and Environmental Engineering and KAIST Robotics Program >
KAIST (President Kwang-Hyung Lee) announced on the 6th that Professor Jee-Hwan Ryu from the Department of Civil and Environmental Engineering received the 2024 Best Paper Award from the Robotics and Automation Letters (RA-L), a premier journal under the IEEE, at the '2025 IEEE International Conference on Robotics and Automation (ICRA)' held in Atlanta, USA, on May 22nd.
This Best Paper Award is a prestigious honor presented to only the top 5 papers out of approximately 1,500 published in 2024, boasting high international competition and authority.
The award-winning paper by Professor Ryu proposes a novel working channel securing mechanism that significantly expands the practicality and application possibilities of 'Soft Growing Robots,' which are based on soft materials that move or perform tasks through a growing motion similar to plant roots.
< IEEE Robotics Journal Award Ceremony >
Existing soft growing robots move by inflating or contracting their bodies through increasing or decreasing internal pressure, which can lead to blockages in their internal passages. In contrast, the newly developed soft growing robot achieves a growing function while maintaining the internal passage pressure equal to the external atmospheric pressure, thereby successfully securing an internal passage while retaining the robot's flexible and soft characteristics.
This structure allows various materials or tools to be freely delivered through the internal passage (working channel) within the robot and offers the advantage of performing multi-purpose tasks by flexibly replacing equipment according to the working environment.
The research team fabricated a prototype to prove the effectiveness of this technology and verified its performance through various experiments. Specifically, in the slide plate experiment, they confirmed whether materials or equipment could pass through the robot's internal channel without obstruction, and in the pipe pulling experiment, they verified if a long pipe-shaped tool could be pulled through the internal channel.
< Figure 1. Overall hardware structure of the proposed soft growing robot (left) and a cross-sectional view composing the inflatable structure (right) >
Experimental results demonstrated that the internal channel remained stable even while the robot was growing, serving as a key basis for supporting the technology's practicality and scalability.
Professor Jee-Hwan Ryu stated, "This award is very meaningful as it signifies the global recognition of Korea's robotics technology and academic achievements. Especially, it holds great significance in achieving technical progress that can greatly expand the practicality and application fields of soft growing robots. This achievement was possible thanks to the dedication and collaboration of the research team, and I will continue to contribute to the development of robotics technology through innovative research."
< Figure 2. Material supplying mechanism of the Soft Growing Robot >
This research was co-authored by Dongoh Seo, Ph.D. Candidate in Civil and Environmental Engineering, and Nam Gyun Kim, Ph.D. Candidate in Robotics. It was published in IEEE Robotics and Automation Letters on September 1, 2024.
(Paper Title: Inflatable-Structure-Based Working-Channel Securing Mechanism for Soft Growing Robots, DOI: 10.1109/LRA.2024.3426322)
This project was supported simultaneously by the National Research Foundation of Korea's Future Promising Convergence Technology Pioneer Research Project and Mid-career Researcher Project.
2025.06.09 View 11530 -
KAIST & CMU Unveils Amuse, a Songwriting AI-Collaborator to Help Create Music
Wouldn't it be great if music creators had someone to brainstorm with, help them when they're stuck, and explore different musical directions together? Researchers of KAIST and Carnegie Mellon University (CMU) have developed AI technology similar to a fellow songwriter who helps create music.
KAIST (President Kwang-Hyung Lee) has developed an AI-based music creation support system, Amuse, by a research team led by Professor Sung-Ju Lee of the School of Electrical Engineering in collaboration with CMU. The research was presented at the ACM Conference on Human Factors in Computing Systems (CHI), one of the world’s top conferences in human-computer interaction, held in Yokohama, Japan from April 26 to May 1. It received the Best Paper Award, given to only the top 1% of all submissions.
< (From left) Professor Chris Donahue of Carnegie Mellon University, Ph.D. Student Yewon Kim and Professor Sung-Ju Lee of the School of Electrical Engineering >
The system developed by Professor Sung-Ju Lee’s research team, Amuse, is an AI-based system that converts various forms of inspiration such as text, images, and audio into harmonic structures (chord progressions) to support composition.
For example, if a user inputs a phrase, image, or sound clip such as “memories of a warm summer beach”, Amuse automatically generates and suggests chord progressions that match the inspiration.
Unlike existing generative AI, Amuse is differentiated in that it respects the user's creative flow and naturally induces creative exploration through an interactive method that allows flexible integration and modification of AI suggestions.
The core technology of the Amuse system is a generation method that blends two approaches: a large language model creates music code based on the user's prompt and inspiration, while another AI model, trained on real music data, filters out awkward or unnatural results using rejection sampling.
< Figure 1. Amuse system configuration. After extracting music keywords from user input, a large language model-based code progression is generated and refined through rejection sampling (left). Code extraction from audio input is also possible (right). The bottom is an example visualizing the chord structure of the generated code. >
The research team conducted a user study targeting actual musicians and evaluated that Amuse has high potential as a creative companion, or a Co-Creative AI, a concept in which people and AI collaborate, rather than having a generative AI simply put together a song.
The paper, in which a Ph.D. student Yewon Kim and Professor Sung-Ju Lee of KAIST School of Electrical and Electronic Engineering and Carnegie Mellon University Professor Chris Donahue participated, demonstrated the potential of creative AI system design in both academia and industry. ※ Paper title: Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations DOI: https://doi.org/10.1145/3706598.3713818
※ Research demo video: https://youtu.be/udilkRSnftI?si=FNXccC9EjxHOCrm1
※ Research homepage: https://nmsl.kaist.ac.kr/projects/amuse/
Professor Sung-Ju Lee said, “Recent generative AI technology has raised concerns in that it directly imitates copyrighted content, thereby violating the copyright of the creator, or generating results one-way regardless of the creator’s intention. Accordingly, the research team was aware of this trend, paid attention to what the creator actually needs, and focused on designing an AI system centered on the creator.”
He continued, “Amuse is an attempt to explore the possibility of collaboration with AI while maintaining the initiative of the creator, and is expected to be a starting point for suggesting a more creator-friendly direction in the development of music creation tools and generative AI systems in the future.”
This research was conducted with the support of the National Research Foundation of Korea with funding from the government (Ministry of Science and ICT). (RS-2024-00337007)
2025.05.07 View 16896 -
Professor Hojong Chang’s Research Team Wins ISIITA 2020 Best Paper Award
The paper written by Professor Hojong Chang’s research team from KAIST Institute for IT Convergence won the best paper award from the International Symposium on Innovation in Information Technology Application (ISIITA) 2020, held this month at Ton Duc Thang University in Vietnam.
ISIITA is a networking symposium where leading researchers from various fields including information and communications, biotechnology, and computer systems come together and share on the convergence of technology.
Professor Chang’s team won the best paper award at this year’s symposium with its paper, “A Study of Single Photon Counting System for Quantitative Analysis of Luminescence”. The awarded paper discusses the realization of a signal processing system for silicon photomultipliers.
The silicon photomultiplier is the core of a urinalysis technique that tests for sodium and potassium in the body using simple chemical reactions. If our bodily sodium and potassium levels exceed a certain amount, it can lead to high blood pressure, cardiovascular problems, and kidney damage.
Through this research, the team has developed a core technique that quantifies the sodium and potassium discharged in the urine. When the reagent is injected into the urine, a very small amount of light is emitted as a result of the chemical reaction. However, if there is a large amount of sodium and potassium, they interrupt the reaction and reduce the emission. The key to this measurement technique is digitizing the strength of this very fine emission of light. Professor Chang’s team developed a system that uses a photomultiplier to measure the chemiluminescence.
Professor Chang said, “I look forward for this signal processing system greatly helping to prevent diseases caused by the excessive consumption of sodium and potassium through quick and easy detection.”
Researcher Byunghun Han who carried out the central research for the system design added, “We are planning to focus on miniaturizing the developed technique, so that anyone can carry our device around like a cellphone.”
The research was supported by the Ministry of Science and ICT.
(END)
2020.02.27 View 17910 -
Professor Hojong Chang Wins the Best Paper Award at ISIITA 2018
Professor Hojong Chang from the KAIST Institute won the best paper award at the International Symposium on Innovation in Information Technology and Application (ISIITA) 2018.
ISIITA is a global networking symposium in which leading researchers in the field of information technology and applications gather to exchange knowledge on technological convergence.
Professor Chang won the prize for his paper, titled ‘A Study on the Measurement of Aptamer in Urine Using SiPM’.
This paper proposes using aptamer to measure and analyze the density of sodium and potassium contained in urine, allowing diseases to be diagnosed in advance.
Professor Chang said, “With a point-of-care test system that facilitates a quick diagnosis without extra processes, such as centrifugation, it is possible to get an early diagnosis and check infection in real time. Through generalizing this crucial technology, we expect to develop adequate technology for enhancing quality of life.
2018.02.12 View 14050 -
Professor Lee Recognized by the KMS as Best Paper Awardee
Professor Ji Oon Lee of the Department of Mathematical Sciences was selected as the 2017 Best Paper Awardee by the Korean Mathematical Society. The award will be presented during the KMS spring meeting on April 29. Dr. Lee is being honored for proving a necessary and sufficient condition for the Tracy-Wisdom law of Wigner matrices. In a paper titled ‘A Necessary and Sufficient Condition for Edge Universality of Wigner Matrices,’ he proposed a solution for one of the many unanswered problems in the field of random matrix theory that have existed for decades. The paper, co-authored with Professor Jun Yin at the University of Wisconsin – Madison, was published in the Duke Mathematical Journal in 2014. Professor Lee joined KAIST in 2010 after finishing his Ph.D. at Harvard University. He was named a ‘POSCI Science Fellow’ and received the ‘Young Scientist Award’ from the KMS in 2014.
2017.04.27 View 15785 -
EEWS Graduate School Team Receives the S-Oil Best Paper Award
Professor Hyungjun Kim and Dr. He-Young Shin from the EEWS (Energy, Environment, Water and Sustainability) Graduate School at KAIST received the Best Paper Award in Chemistry from S-Oil, a Korean petroleum and refinery company, on November 29, 2016.
Established in 2011, the S-Oil Best Paper Awards are bestowed annually upon ten young scientists in the fields of five basic sciences: mathematics, physics, chemistry, biology, and earth science. The scientists are selected at the recommendation of the Korean Academy of Science and Technology and the Association of Korean Universities. The awards grant a total of USD 230,000 for research funding.
Dr. Shin, the lead author of the awarded research paper, said, “My research interest has been catalyst studies based on theoretical chemistry. I am pleased to accept this award that will support my studies, and will continue to research catalyst design that can predict parameters and integrate them into catalytic systems.”
Professor Hyungjun Kim (left) and Dr. He-Young Shin (right)
2016.12.23 View 16783 -
Mobile Software Platform Research Center Recognized by the MSIP
The Mobile Software Platform Research Center (MSPRC) at KAIST received an award from the Minister of Science, ICT and Future Planning of Korea on November 29, 2016, at Coex in Seoul. The award was presented at the Conference of Software R&D Annual Report 2016 hosted by the Ministry of Science, ICT and Future Planning (MISP) and the Institute for Information and Communications Technology Promotion (IITP).
The research center developed user experience (UX)-oriented mobile software platforms that support the invention of next-generation UX service technologies. The center has filed 37 patents and registered 15 technologies. Its researchers received ten Best Paper Awards and published a total of 133 papers in Korean and international journals.
Research teams at MSPRC expect that their software platforms will offer training programs for software engineers and new UX services. They also said that their extensive event processing platforms would reduce energy consumption on mobile devices.
Professor Seungryoul Maeng of the School of Computing, the Director of MSPRC, said, “This is a great honor for us. I am greatly thankful for the teamwork of participating departments--Computer Science, Industrial Design, and Industrial and Systems Engineering. We will continue to introduce our research outcomes and to work towards commercializing these results.”
Members of the Mobile Software Platform Research Center, KAIST
2016.12.07 View 10744 -
Dong-Young Lee, a Doctoral Candidate, Receives the Best Paper Award
Dong-Young Lee, a Ph.D. candidate in the Mechanical Engineering Department, KAIST, received the Best Paper Award at the 18th International Conference on Composite Structures (ICCS). The event was held in Lisbon, Portugal, on June 15-18, 2015. Mr. Lee’s adviser is Professor Dai-Gil Lee of the same department.
The ICCS is held every other year, and is one of the largest and long-established conferences on composite materials and structures in the world. At this year’s conference, a total of 680 papers were presented, among which, two papers were chosen for the Best Paper Award, including Mr. Lee’s.
The paper, entitled “Gasket-integrated Carbon and Silicon Elastomer Composite Bipolar Plate for High-temperature PEMFC,” will be published in the September issue of Composite Structures which is one of the top journals in mechanical engineering as judged by the Google Scholar Metrics rankings.
Mr. Lee dropped the conventional method of PEMFC (Proton Exchange Membrane Fuel Cells) assembly and instead developed a gasket-integrated carbon and silicone elastomer composite bipolar plate. This technology significantly increased the energy efficiency of fuel cells and their productivity.
Mr. Lee said, “I would like to thank the many people who supported me, especially my Ph.D. adviser, Professor Dai-Gil Lee. Without their encouragement, I would have not won this award. I hope my research will contribute to solving energy problems in the future.”
In addition, Professor Joon-Woo Im from Chonbuk National University, Senior Researcher Il-Bum Choi from the Agency for Defense Development, and a fellow doctoral candidate Soo-Hyun Nam from KAIST participated in this research project.
2015.07.09 View 15990 -
KAIST's Patina Engraving System Awarded at ACM CHI
Professor Tek-Jin Nam’s research team of the Industrial Design Department of KAIST received the Best Paper Award in the 2015 Association for Computing Machinery’s (ACM) Conference on Human Factors in Computing Systems (CHI) which was held from April 18 to 23, 2015. The team consisted of two KAIST students: Moon-Hwan Lee, a Ph.D. candidate, and Sejin Cha, a master's student. The team was the first in Asia to receive the award.
The ACM CHI represents the premier conference in the field of Human-Computer Interaction (HCI). This year’s event, held in Seoul, South Korea, was the first conference that the ACM had held in Asia in its thirty-three year history. The KAIST team’s paper, entitled “Patina Engraver: Visualizing Activity Logs as Patina in Fashionable Trackers,” ranked in the top 1% of 2,000 submitted papers.
The team developed Patina Engraver, an activity tracker, which monitors and tracks fitness-related metrics such as distances walked or run, calorie consumption, heartbeat, sleep quality, and blood pressure. The device wirelessly connects to a computer or smartphone so that it can store and utilize long-term tracking data.
However, what makes Patina Engraver, a smart wristband, different from other health trackers is its ability to display different design patterns based on users’ activity on the surface of the wristband. The research team was inspired to build this system from the fact that wearable electronics including activity trackers can be used not only as health care devices, but also as fashion items to express emotions and personalities.
Equipped with an engraving feature, the charging pad or holder for Patina Engraver draws individualized patterns to reflect the user’s activities, such as walking or running, while the device is being charged. The pattern display syncs with the frequency of usage, therefore, the more the tracker is used, the greater the number of patterns will show up.
According to the team, since Patina Engraver provides users with a personalized illustration of their activity on the tracker, users are more motivated to put on the tracker and exercise.
Professor Nam said, “This research can be applied in producing other wearable devices to enhance users’ emotional satisfaction. When wearable technology is combined with design and emotion, the industry market will quickly expand.”
Figure 1: Patina engraving system developed by KAIST research team
Figure 2: The process of engraving illustrations of the activity records onto the tracker
Figure 3: Personalized activity trackers based on activity records
2015.05.15 View 20881