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Maxwell Herman

dblp:164/8521 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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 · 100%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.212015
Soft robotic glove for hand rehabilitation and task specific training · ICRA 2015
Health and well-being technologies › rehabilitation technology
rehabilitation robotics
0.212015
Soft robotic glove for hand rehabilitation and task specific training · ICRA 2015
Health and well-being technologies › rehabilitation technology
soft robotic glove
0.212015
Soft robotic glove for hand rehabilitation and task specific training · ICRA 2015

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

soft actuator design · 0.4motion capture · 0.4
YearPublicationVenuePosition
2015 Soft robotic glove for hand rehabilitation and task specific training
abstract
This paper presents advancements in the design of a portable, soft robotic glove for individuals with functional grasp pathologies. The robotic glove leverages soft material actuator technology to safely distribute forces along the length of the finger and provide active flexion and passive extension. These actuators consist of molded elastomeric bladders with anisotropic fiber reinforcements that produce specific bending, twisting, and extending trajectories upon fluid pressurization. In particular, we present a method for customizing a soft actuator to a wearer's biomechanics and demonstrate in a motion capture system that the ranges of motion (ROM) of the two are nearly equivalent. The active ROM of the glove is further evaluated using the Kapandji test. Lastly, in a case study, we present preliminary results of a patient with very weak hand strength performing a timed Box-and-Block test with and without the soft robotic glove.
Panagiotis Polygerinos, Kevin C. Galloway, Emily Savage, Maxwell Herman, Kathleen O'Donnell, Conor J. Walsh
ICRA4