Demo Data from SIGIR 2026 / reviewers in the wild / expert
Minwoo Seong
dblp:352/4698
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0009-0007-5847-9666ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
2 papers |
Haptics and multimodal interaction · 34% Accessibility and assistive technology · 29% Human-robot interaction · 29% | |
| Artificial intelligence
1 paper |
Legged, aerial and field robots · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
intent prediction |
0.9 | 1 | 2025 | Adaptive Walker: User Intention and Terrain Aware Intelligent Walker with High-Resolution Tactile and IMU Sensor · ICRA 2025 |
Accessibility and assistive technology › assistive technology
smart walker |
0.9 | 1 | 2025 | Adaptive Walker: User Intention and Terrain Aware Intelligent Walker with High-Resolution Tactile and IMU Sensor · ICRA 2025 |
Haptics and multimodal interaction › electrical stimulation
electrical muscle stimulation |
0.8 | 1 | 2024 | ErgoPulse: Electrifying Your Lower Body With Biomechanical Simulation-based Electrical Muscle Stimulation Haptic System in Virtual Reality · CHI 2024 |
Robotics › Legged, aerial and field robots
terrain adaptation |
0.3 | 1 | 2025 | Adaptive Walker: User Intention and Terrain Aware Intelligent Walker with High-Resolution Tactile and IMU Sensor · ICRA 2025 |
Haptics and multimodal interaction
tactile sensing |
0.3 | 1 | 2025 | Adaptive Walker: User Intention and Terrain Aware Intelligent Walker with High-Resolution Tactile and IMU Sensor · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
linear motor control · 1.7deep learning · 1.7IMU sensing · 1.7user study · 0.8electrical muscle stimulation · 0.8biomechanical simulation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Adaptive Walker: User Intention and Terrain Aware Intelligent Walker with High-Resolution Tactile and IMU SensorabstractIn this paper, we present an adaptive walker system designed to address limitations in current intelligent walker technologies. While recent advancements have been made in this field, existing systems often struggle to seamlessly interpret user intent for speed control and lack adaptability across diverse scenarios and terrain. Our proposed solution incorporates high-resolution tactile sensors, deep learning algorithms, IMU sensors, and linear motors to dynamically adjust to the user's intentions and terrain changes. The system is capable of predicting the user's desired speed with an error margin of only 20.99%, relying solely on tactile input from hand and arm contact points. Additionally, it maintains the walker's horizontal stability with an error of less than 1 degree by adjusting leg lengths in response to variations in ground angle. This adaptive walker enhances user safety and comfort, particularly for individuals with reduced strength or cognitive abilities, and offers reliable assistance on uneven terrain such as uphill and downhill paths. Seokhyun Hwang, JaeYoung Moon, Hosu Lee 0001, Dohyeon Yeo, Minwoo Seong, Yiyue Luo, Seungjun Kim 0001, Wojciech Matusik, Daniela Rus, Kyung-Joong Kim 0001 |
ICRA | 6 |
| 2024 | ErgoPulse: Electrifying Your Lower Body With Biomechanical Simulation-based Electrical Muscle Stimulation Haptic System in Virtual RealityabstractThis study presents ErgoPulse, a system that integrates biomechanical simulation with electrical muscle stimulation (EMS) to provide kinesthetic force feedback to the lower-body in virtual reality (VR). ErgoPulse features two main parts: a biomechanical simulation part that calculates the lower-body joint torques to replicate forces from VR environments, and an EMS part that translates torques into muscle stimulations. In the first experiment, we assessed users’ ability to discern haptic force intensity and direction, and observed variations in perceived resolution based on force direction. The second experiment evaluated ErgoPulse’s ability to increase haptic force accuracy and user presence in both continuous and impulse force VR game environments. The experimental results showed that ErgoPulse’s biomechanical simulation increased the accuracy of force delivery compared to traditional EMS, enhancing the overall user presence. Furthermore, the interviews proposed improvements to the haptic experience by integrating additional stimuli such as temperature, skin stretch, and impact. Seokhyun Hwang, Jeongseok Oh, Seongjun Kang, Minwoo Seong, Ahmed Elsharkawy 0001, Seungjun Kim 0001 |
CHI | 4 |