Evidence map›Paper›PMID 28684744›Full record

ArticleScientific reports2017

Learning new movements after paralysis: Results from a home-based study.

Camilla Pierella, Farnaz Abdollahi, Elias Thorp, Ali Farshchiansadegh, Jessica Pedersen, Ismael Seáñez-González, Ferdinando A Mussa-Ivaldi, Maura Casadio

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. An Exploratory Multi-Session Study of Learning High-Dimensional Body-Machine Interfacing for Assistive Robot Control.IEEE ... International Conference on Rehabilitation Robotics : [proceedings] · 2023
    Article
  5. A Non-Linear Body Machine Interface for Controlling Assistive Robotic Arms.IEEE transactions on bio-medical engineering · 2023
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. 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

8 authors.

Camilla PierellaDepartment of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145, Genova, Italy. camilla.pierella@epfl.ch.ORCID 0000-0002-8108-9363
Farnaz AbdollahiDepartment of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA.
Elias ThorpSensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, 60611, USA.
Ali FarshchiansadeghSensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, 60611, USA.
Jessica PedersenSensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, 60611, USA.
Ismael Seáñez-GonzálezSensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, 60611, USA.ORCID 0000-0003-0068-7124
Ferdinando A Mussa-IvaldiDepartment of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, 60611, USA.
Maura CasadioDepartment of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145, Genova, Italy.

Funding

Motor Learning in a Customized Body-Machine Interface for Persons with ParalysisR01HD072080 · NICHD · REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB · PI MUSSA-IVALDI, FERDINANDO ALESSANDRO · 2012 to 2016
$1.4M
NICHD NIH HHS R01 HD072080
6 · The paper itself

Abstract

Body-machine interfaces (BMIs) decode upper-body motion for operating devices, such as computers and wheelchairs. We developed a low-cost portable BMI for survivors of cervical spinal cord injury and investigated it as a means to support personalized assistance and therapy within the home environment. Depending on the specific impairment of each participant, we modified the interface gains to restore a higher level of upper body mobility. The use of the BMI over one month led to increased range of motion and force at the shoulders in chronic survivors. Concurrently, subjects learned to reorganize their body motions as they practiced the control of a computer cursor to perform different tasks and games. The BMI allowed subjects to generate any movement of the cursor with different motions of their body. Through practice subjects demonstrated a tendency to increase the similarity between the body motions used to control the cursor in distinct tasks. Nevertheless, by the end of learning, some significant and persistent differences appeared to persist. This suggests the ability of the central nervous system to concurrently learn operating the BMI while exploiting the possibility to adapt the available mobility to the specific spatio-temporal requirements of each task.

Indexed as

User-Computer InterfaceAdultAgedFemaleHumansLearningMaleMiddle AgedMotor SkillsMovementParalysisPsychomotor PerformanceRange of Motion, ArticularShoulderSpinal Cord Injuries

Identifiers

PMID28684744
PMCPMC5500508

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.