Evidence map›Paper›PMID 33501275›Full record

ArticleFrontiers in robotics and AI2020

A Novel User Control for Lower Extremity Rehabilitation Exoskeletons.

Kiran K Karunakaran, Kevin Abbruzzese, Ghaith Androwis, Richard A Foulds

Open access · goldAbstract read
In one paragraph

Article in Frontiers in robotics and AI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review of control strategies for lower-limb exoskeletons to assist gait.Journal of neuroengineering and rehabilitation · 2021
    Review
  3. Article
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

4 authors at 1 institution in 1 country.

Kiran K KarunakaranKessler Foundation, West Orange, NJ, United States.
Kevin AbbruzzeseDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States.
Ghaith AndrowisKessler Foundation, West Orange, NJ, United States.
Richard A FouldsDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States.
New Jersey Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lower extremity exoskeletons offer the potential to restore ambulation to individuals with paraplegia due to spinal cord injury. However, they often rely on preprogrammed gait, initiated by switches, sensors, and/or EEG triggers. Users can exercise only limited independent control over the trajectory of the feet, the speed of walking, and the placement of feet to avoid obstacles. In this paper, we introduce and evaluate a novel approach that naturally decodes a neuromuscular surrogate for a user's neutrally planned foot control, uses the exoskeleton's motors to move the user's legs in real-time, and provides sensory feedback to the user allowing real-time sensation and path correction resulting in gait similar to biological ambulation. Users express their desired gait by applying Cartesian forces via their hands to rigid trekking poles that are connected to the exoskeleton feet through multi-axis force sensors. Using admittance control, the forces applied by the hands are converted into desired foot positions, every 10 milliseconds (ms), to which the exoskeleton is moved by its motors. As the trekking poles reflect the resulting foot movement, users receive sensory feedback of foot kinematics and ground contact that allows on-the-fly force corrections to maintain the desired foot behavior. We present preliminary results showing that our novel control can allow users to produce biologically similar exoskeleton gait.

Indexed as

gaitlower extremity exoskeletonsrehabilitation roboticsrobot control systemsspinal cord injury

Identifiers

PMID33501275
PMCPMC7805763
OpenAlexW3084317986

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.