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Edwin van Asseldonk

dblp:04/10289 · also Edwin H. F. van Asseldonk · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0003-1534-2348ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

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
1 paper
Health and well-being technologies · 87% Wearable and physiological sensing · 13%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
human-robot interaction
0.212016
Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer · IEEE Trans. Robotics 2016
Health and well-being technologies › rehabilitation technology › rehabilitation robotics
gait rehabilitation
0.212016
Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer · IEEE Trans. Robotics 2016
Health and well-being technologies › rehabilitation technology
rehabilitation robotics
0.212016
Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer · IEEE Trans. Robotics 2016
Wearable and physiological sensing
biomechanical sensing
0.112016
Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer · IEEE Trans. Robotics 2016

Methods — techniques the papers use, named apart from their topics

system identification · 0.5MIMO identification · 0.5
YearPublicationVenuePosition
2016 Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer
abstract
In this study, we present and evaluate a novel method to estimate multi-joint leg impedance, using a robotic gait training device. The method is based on multi-input-multi-output system identification techniques and is designed for continuous torque perturbations at the hip and knee joint simultaneously. Eight elderly subjects (age 67-82) performed relax and position tasks in three different leg orientations. Multi-joint impedance was estimated nonparametrically and was subsequently modeled in terms of inertia and (inter)joint stiffness and damping. The results indicate that all stiffness and damping parameters were significantly higher during the position task compared to the relax task. The majority of the stiffness and damping parameters were not significantly affected by leg orientation. The results also emphasize the importance of considering the visco-elastic coupling between joints when modeling multi-joint dynamics. Measuring joint stiffness with the same device that is used for robotic gait training allows convenient testing of joint properties in conjunction with the robotic gait training protocol. These measures might serve as a good basis for quantitative assessment and follow up of patients with abnormal joint stiffness due to neurological disorders, and may reveal how changes in these joint properties affect their gait function.
Bram Koopman, Edwin van Asseldonk, Herman van der Kooij
IEEE Trans. Robotics2
2013 Actively controlled lateral gait assistance in a lower limb exoskeleton
abstract
Various powered wearable lower limb exoskeletons are designed for paraplegics to make them walk again. Control methods are developed and implemented in these exoskeletons to provide active gait assistance in the sagittal plane while active control in the frontal plane is still missing. This paper proposed a control method that provided gait assistance in both lateral and sagittal plane. First, in the lateral plane, the exoskeleton was controlled to support the weight shift during stepping by providing assisting hip ab/adduction torques when the subject initiated a small amount of weight shift to the stance side to trigger a step. Second, the exoskeleton's hip ab/adduction during stepping was controlled to improve lateral stability. This was achieved by altering the amount of hip ab/adduction to change step width at heel strike. Using these controls, an able-bodied subject could walk in the exoskeleton without any external balance aids, i.e. crutches or a walker, where his hip and knee joints were controlled by the exoskeleton and his ankle joints were constrained by the exoskeleton. The next step is to test whether the proposed method improves balance in spinal cord injured subjects.
Shiqian Wang, Edwin van Asseldonk, Herman van der Kooij
IROS3