Evidence map›Paper›PMID 35783026›Full record

ArticleFrontiers in robotics and AI2022

Assisting Forearm Function in Children With Movement Disorders

Jonathan Realmuto, Terence D Sanger

Open access · goldAbstract read
In one paragraph

Article in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 59% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Jonathan RealmutoDepartment of Mechanical Engineering, University of California, Riverside, Riverside, CA, United States.
Terence D SangerDepartment of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States.
University of California, Irvine · USUniversity of California, Riverside · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable robots are envisioned to amplify the independence of people with movement impairments by providing daily physical assistance. For portable, comfortable, and safe devices, soft pneumatic-based robots are emerging as a potential solution. However, due to the inherent complexities, including compliance and nonlinear mechanical behavior, feedback control for facilitating human-robot interaction remains a challenge. Herein, we present the design, fabrication, and control architecture of a soft wearable robot that assists in supination and pronation of the forearm. The soft wearable robot integrates an antagonistic pair of pneumatic-based helical actuators to provide active pronation and supination torques. Our main contribution is a bio-inspired equilibrium-point control scheme for integrating proprioceptive feedback and exteroceptive input (e.g., the user's muscle activation signals) directly with the on/off valve behavior of the soft pneumatic actuators. The proposed human-robot controller is directly inspired by the equilibrium-point hypothesis of motor control, which suggests that voluntary movements arise through shifts in the equilibrium state of the antagonistic muscle pair spanning a joint. We hypothesized that the proposed method would reduce the required effort during dynamic manipulation without affecting the error. In order to evaluate our proposed method, we recruited seven pediatric participants with movement disorders to perform two dynamic interaction tasks with a haptic manipulandum. Each task required the participant to track a sinusoidal trajectory while the haptic manipulandum behaved as a Spring-Dominate system or Inertia-Dominate system. Our results reveal that the soft wearable robot, when active, reduced user effort on average by 14%. This work demonstrates the practical implementation of an equilibrium-point volitional controller for wearable robots and provides a foundational path toward versatile, low-cost, and soft wearable robots.

Indexed as

equilibrium-point controlhuman–robot interactionproprioceptionreflexessoft roboticswearable robotics

Identifiers

PMID35783026
PMCPMC9240630
OpenAlexW4282942439

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.