Demo Data from EDBT 2026 / reviewers in the wild / expert
Matthew R. Short
dblp:337/9672
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0000-0002-5090-162XORCID · 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 2021Applied, interdisciplinary, general and emerging 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.
| Artificial intelligence
2 papers |
Motion planning and robot control · 76% Robot manipulation · 24% | |
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
exoskeleton control |
1.5 | 2 | 2024 | Haptic Transparency and Interaction Force Control for a Lower Limb Exoskeleton · IEEE Trans. Robotics 2024 Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation Task · ICRA 2024 |
Robotics › Motion planning and robot control › robot control › force control
interaction force control |
0.8 | 1 | 2024 | Haptic Transparency and Interaction Force Control for a Lower Limb Exoskeleton · IEEE Trans. Robotics 2024 |
Robotics › Robot manipulation
physical human-robot interaction |
0.8 | 1 | 2024 | Haptic Transparency and Interaction Force Control for a Lower Limb Exoskeleton · IEEE Trans. Robotics 2024 |
Robotics › Motion planning and robot control
whole-body control |
0.8 | 1 | 2024 | Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation Task · ICRA 2024 |
Health and well-being technologies › rehabilitation technology
rehabilitation robotics |
0.8 | 1 | 2024 | Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation Task · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
physical human-human interaction · 1.5online feedback · 1.5whole-body dynamics · 0.8constrained optimization · 0.8closed-loop compensation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Exoskeleton-Mediated Physical Human-Human Interaction for a Sit-to-Stand Rehabilitation TaskabstractSit-to-Stand (StS) is a fundamental daily activity that can be challenging for stroke survivors due to strength, motor control, and proprioception deficits in their lower limbs. Existing therapies involve repetitive StS exercises, but these can be physically demanding for therapists while assistive devices may limit patient participation and hinder motor learning. To address these challenges, this work proposes the use of two lower-limb exoskeletons to mediate physical interaction between therapists and patients during a StS rehabilitative task. This approach offers several advantages, including improved therapist-patient interaction, safety enforcement, and performance quantification. The whole body control of the two exoskeletons transmits online feedback between the two users, but at the same time assists in movement and ensures balance, and thus helping subjects with greater difficulty. In this study we present the architecture of the framework, presenting and discussing some technical choices made in the design. Lorenzo Vianello, Emek Baris Küçüktabak, Matthew R. Short, Clément Lhoste, Lorenzo Amato, Kevin M. Lynch, José Luis Pons Rovira |
ICRA | 3 |
| 2024 | Haptic Transparency and Interaction Force Control for a Lower Limb ExoskeletonabstractControlling the interaction forces between a human and an exoskeleton is crucial for providing transparency or adjusting assistance or resistance levels. However, it is an open problem to control the interaction forces of lower-limb exoskeletons designed for unrestricted overground walking. For these types of exoskeletons, it is challenging to implement force/torque sensors at every contact between the user and the exoskeleton for direct force measurement. Moreover, it is important to compensate for the exoskeleton's whole-body gravitational and dynamical forces, especially for heavy lower-limb exoskeletons. Previous works either simplified the dynamic model by treating the legs as independent double pendulums, or they did not close the loop with interaction force feedback. The proposed whole-exoskeleton closed-loop compensation (WECC) method calculates the interaction torques during the complete gait cycle by using whole-body dynamics and joint torque measurements on a hip-knee exoskeleton. Furthermore, it uses a constrained optimization scheme to track desired interaction torques in a closed loop while considering physical and safety constraints. We evaluated the haptic transparency and dynamic interaction torque tracking of WECC control on three subjects. We also compared the performance of WECC with a controller based on a simplified dynamic model and a passive version of the exoskeleton. The WECC controller results in a consistently low absolute interaction torque error during the whole gait cycle for both zero and nonzero desired interaction torques. In contrast, the simplified controller yields poor performance in tracking desired interaction torques during the stance phase Emek Baris Küçüktabak, Yue Wen, Sangjoon J. Kim, Matthew R. Short, Daniel Ludvig, Levi J. Hargrove, Eric J. Perreault, Kevin M. Lynch, José Luis Pons Rovira |
IEEE Trans. Robotics | 4 |