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KAIST Professor Uichin Lee Receives Distinguished Paper Award from ACM
< Photo. Professor Uichin Lee (left) receiving the award > KAIST (President Kwang Hyung Lee) announced on the 25th of October that Professor Uichin Lee’s research team from the School of Computing received the Distinguished Paper Award at the International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computing (Ubicomp / ISWC) hosted by the Association for Computing Machinery (ACM) in Melbourne, Australia on October 8. The ACM Ubiquitous Computing Conference is the most prestigious international conference where leading universities and global companies from around the world present the latest research results on ubiquitous computing and wearable technologies in the field of human-computer interaction (HCI). The main conference program is composed of invited papers published in the Proceedings of the ACM (PACM) on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), which covers the latest research in the field of ubiquitous and wearable computing. The Distinguished Paper Award Selection Committee selected eight papers among 205 papers published in Vol. 7 of the ACM Proceedings (PACM IMWUT) that made outstanding and exemplary contributions to the research community. The committee consists of 16 prominent experts who are current and former members of the journal's editorial board which made the selection after a rigorous review of all papers for a period that stretched over a month. < Figure 1. BeActive mobile app to promote physical activity to form active lifestyle habits > The research that won the Distinguished Paper Award was conducted by Dr. Junyoung Park, a graduate of the KAIST Graduate School of Data Science, as the 1st author, and was titled “Understanding Disengagement in Just-in-Time Mobile Health Interventions” Professor Uichin Lee’s research team explored user engagement of ‘Just-in-Time Mobile Health Interventions’ that actively provide interventions in opportune situations by utilizing sensor data collected from health management apps, based on the premise that these apps are aptly in use to ensure effectiveness. < Figure 2. Traditional user-requested digital behavior change intervention (DBCI) delivery (Pull) vs. Automatic transmission (Push) for Just-in-Time (JIT) mobile DBCI using smartphone sensing technologies > The research team conducted a systematic analysis of user disengagement or the decline in user engagement in digital behavior change interventions. They developed the BeActive system, an app that promotes physical activities designed to help forming active lifestyle habits, and systematically analyzed the effects of users’ self-control ability and boredom-proneness on compliance with behavioral interventions over time. The results of an 8-week field trial revealed that even if just-in-time interventions are provided according to the user’s situation, it is impossible to avoid a decline in participation. However, for users with high self-control and low boredom tendency, the compliance with just-in-time interventions delivered through the app was significantly higher than that of users in other groups. In particular, users with high boredom proneness easily got tired of the repeated push interventions, and their compliance with the app decreased more quickly than in other groups. < Figure 3. Just-in-time Mobile Health Intervention: a demonstrative case of the BeActive system: When a user is identified to be sitting for more than 50 mins, an automatic push notification is sent to recommend a short active break to complete for reward points. > Professor Uichin Lee explained, “As the first study on user engagement in digital therapeutics and wellness services utilizing mobile just-in-time health interventions, this research provides a foundation for exploring ways to empower user engagement.” He further added, “By leveraging large language models (LLMs) and comprehensive context-aware technologies, it will be possible to develop user-centered AI technologies that can significantly boost engagement." < Figure 4. A conceptual illustration of user engagement in digital health apps. Engagement in digital health apps consists of (1) engagement in using digital health apps and (2) engagement in behavioral interventions provided by digital health apps, i.e., compliance with behavioral interventions. Repeated adherences to behavioral interventions recommended by digital health apps can help achieve the distal health goals. > This study was conducted with the support of the 2021 Biomedical Technology Development Program and the 2022 Basic Research and Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT. < Figure 5. A conceptual illustration of user disengagement and engagement of digital behavior change intervention (DBCI) apps. In general, user engagement of digital health intervention apps consists of two components: engagement in digital health apps and engagement in behavioral interventions recommended by such apps (known as behavioral compliance or intervention adherence). The distinctive stages of user can be divided into adoption, abandonment, and attrition. > < Figure 6. Trends of changes in frequency of app usage and adherence to behavioral intervention over 8 weeks, ● SC: Self-Control Ability (High-SC: user group with high self-control, Low-SC: user group with low self-control) ● BD: Boredom-Proneness (High-BD: user group with high boredom-proneness, Low-BD: user group with low boredom-proneness). The app usage frequencies were declined over time, but the adherence rates of those participants with High-SC and Low-BD were significantly higher than other groups. >
2024.10.25
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AI to Determine When to Intervene with Your Driving
(Professor Uichin Lee (left) and PhD candidate Auk Kim) Can your AI agent judge when to talk to you while you are driving? According to a KAIST research team, their in-vehicle conservation service technology will judge when it is appropriate to contact you to ensure your safety. Professor Uichin Lee from the Department of Industrial and Systems Engineering at KAIST and his research team have developed AI technology that automatically detects safe moments for AI agents to provide conversation services to drivers. Their research focuses on solving the potential problems of distraction created by in-vehicle conversation services. If an AI agent talks to a driver at an inopportune moment, such as while making a turn, a car accident will be more likely to occur. In-vehicle conversation services need to be convenient as well as safe. However, the cognitive burden of multitasking negatively influences the quality of the service. Users tend to be more distracted during certain traffic conditions. To address this long-standing challenge of the in-vehicle conversation services, the team introduced a composite cognitive model that considers both safe driving and auditory-verbal service performance and used a machine-learning model for all collected data. The combination of these individual measures is able to determine the appropriate moments for conversation and most appropriate types of conversational services. For instance, in the case of delivering simple-context information, such as a weather forecast, driver safety alone would be the most appropriate consideration. Meanwhile, when delivering information that requires a driver response, such as a “Yes” or “No,” the combination of driver safety and auditory-verbal performance should be considered. The research team developed a prototype of an in-vehicle conversation service based on a navigation app that can be used in real driving environments. The app was also connected to the vehicle to collect in-vehicle OBD-II/CAN data, such as the steering wheel angle and brake pedal position, and mobility and environmental data such as the distance between successive cars and traffic flow. Using pseudo-conversation services, the research team collected a real-world driving dataset consisting of 1,388 interactions and sensor data from 29 drivers who interacted with AI conversational agents. Machine learning analysis based on the dataset demonstrated that the opportune moments for driver interruption could be correctly inferred with 87% accuracy. The safety enhancement technology developed by the team is expected to minimize driver distractions caused by in-vehicle conversation services. This technology can be directly applied to current in-vehicle systems that provide conversation services. It can also be extended and applied to the real-time detection of driver distraction problems caused by the use of a smartphone while driving. Professor Lee said, “In the near future, cars will proactively deliver various in-vehicle conversation services. This technology will certainly help vehicles interact with their drivers safely as it can fairly accurately determine when to provide conversation services using only basic sensor data generated by cars.” The researchers presented their findings at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp’19) in London, UK. This research was supported in part by Hyundai NGV and by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. (Figure: Visual description of safe enhancement technology for in-vehicle conversation services)
2019.11.13
View 14792
KAST Opened the Campus to the Public
KAIST hosted OPEN KAIST 2017 on the main campus from November 2 to 3, 2017. OPEN KAIST is a science and cultural event designed for students and the general public to experience and take a glance at research labs. More than 10,000 visitors came to KAIST this year. Groups of families and students came to KAIST to experience various programs related to science. Twenty departments, including Mechanical Engineering, Aerospace Engineering, the Graduate School of Cultural Technology, and Materials Science and Engineering participated in the event, along with three research centers and the Public Relations Office. The event was composed of a total of 70 programs in four sections: lab tour, research performance exhibition, department introduction, and special lectures. The kick off activity for the event was a trial game of the AI World Cup 2017 which will be hosted by KAIST in December 2017. Many people also visited the mobile health care showroom where they could experience what a future smart home and hospital would look like. It was also interesting to visit a futuristic living space for one-person households that provides virtual reality services. KAIST hopes that the event offers an opportunity for children and students to get to know about science better. Professor Jong-Hwan Kim, the Dean of the College of Engineering at KAIST said, “OPEN KAIST is the one and only opportunity to visit and experience our research labs. KAIST will make every effort to take a step closer to the public by focusing on research that contributes to human society.”
2017.11.06
View 6216
KAIST & the Classic 500 Co Sign for Mobile Healthcare Research
KAIST and The Classic 500 Co., Ltd., an elder care provider based in Seoul, signed a memorandum of understanding to expand medical services by cooperating on the research of medical services and IT on March 24, 2015. Twenty people from the two institutions, including President Steve Kang, Dong-Hyun Bak, CEO of The Classic 500 and Mun-Sul Jeong, a former KAIST Chairman of the Board, attended the signing ceremony. Under the agreement, the two institutions will cooperate on mobile healthcare research and the development of a telemedicine system. They will also research and develop a system to better serve society with medical services. The Classic 500, established by Konkuk University in Korea, provides nursing care services and assisted living facilities for senior citizens.
2015.03.26
View 7926
'Dr. M,' Mobile Healthcare Showroom Opened at KI
Portable and wearable computers have made the way we manage our health easier and potentially more effective. Researchers from six departments and one graduate school at KAIST collaborated and conducted a one-year project called the “Mobile Healthcare Innovation” to develop a mobile healthcare system. Their research results are on exhibit on campus at the “Dr. M Showroom” which was open on March 13, 2015. Located on the second floor of the College of Information and Electrical Engineering building, the showroom displays the entirety of mobile healthcare system developed during 2014, from the collection of biological data through smart sensors to analyzing big data to provide customized healthcare models for patients. Standing in for a mobile doctor, Dr. M is a networked medical service system provided through the Internet of Things (IoC), wearable electronics, smart home, and smart car. Under this care, people can monitor their health on a daily basis at any-time and place, helping them to lower the risk of serious health problems. Patients who have chronic diseases such as diabetes or cardiovascular illness can inform doctors of their health status in real time. Moreover, people living in remote regions can receive quality medical services without traveling long distances. At the showroom, about 40 convergence technologies are displayed, including biological sensors, low-power communication devices, IoC technology, big data, disease analysis, and prediction technology, presenting how these technologies are connected and worked systematically. For example, all the data earned from biological sensors are analyzed to produce relevant user information. Once abnormalities are discovered, the results would be sent immediately to medical staff for treatment. As part of Dr. M, KAIST has been implementing the establishment of a “Mobile Healthcare Campus,” distributing small, wearable wristbands to 100 students. The wristbands read students’ biological signals and send them to researchers for monitoring. In addition, KAIST plans to collaborate with local hospitals, nursing care centers, communications, and mobile healthcare service providers for the commercialization of Dr. M system. Professor Hoi-Jun Yoo of the Electrical Engineering Department, who has led the Mobile Healthcare Innovation project said, “One of the great advantages Dr. M can offer is the capability to customize healthcare service based on individuals and ages. For individuals in their twenties, for example, healthcare services such as skincare and diet programs will be more relevant whereas blood pressure monitoring for patients in their fifties and early diagnosis for the recurrence of diseases for those in their seventies. If we define human history in terms of major technology advancements, the first big one was computation, communication for the second, and I think ubiquitous healthcare will be the third one. We will continue to develop Dr. M in collaboration with medical and research organizations.” A total of 32 professors from the Departments of Electrical Engineering, Computer Science, Industrial and Systems Engineering, Industrial Design, Web Science, Knowledge Service Engineering, and the Information Security Graduate School participated in the Mobile Healthcare Innovation project.
2015.03.17
View 9967
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