Evidence map›Paper›PMID 31844726›Full record

ArticleHeliyon2019

Modification of knee flexion during walking with use of a real-time personalized avatar.

H Agopyan, J Griffet, T Poirier, J Bredin

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. 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 2 institutions in 1 country.

H AgopyanUniversité côte d'azur, LAMHESS, Nice, France.
J GriffetChirurgie Orthopédique Pédiatrique, Hôpital Couple Enfant, Centre Hospitalier Universitaire de Grenoble, BP 217, 38043 Grenoble cedex 9, France.
T PoirierSAMMed, 91120 Palaiseau, France.
J BredinUniversité côte d'azur, LAMHESS, Nice, France.
Laboratoire Motricité Humaine Éducation Sport Santé · FRCentre Hospitalier Universitaire de Grenoble · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visual feedback is used in different research areas, including clinical science and neuroscience. In this study, we investigated the influence of the visualization of a real-time personalized avatar on gait parameters, focusing on knee flexion during the swing phase. We also studied the impact of the modification of avatar's knee amplitude on kinematic of the knee of healthy subjects. For this purpose, we used an immersive reality treadmill equipment and developed a 3D avatar, with instantly modifiable parameters for knee flexion and extension (acceleration or deceleration). Fourteen healthy young adults, equipped with motion capture markers, were asked to walk at a self-selected pace on the treadmill. A real-time 3D image of their lower limbs was modelized and projected on the screen ahead of them, as if in a walking motion from left to right. The subjects were instructed to continue walking. When we initiated an increase in the knee flexion of the avatar, we observed a similar increase in the subjects' knee flexion. No significant results were observed when the modification involved a decrease in knee flexion. The results and their significance are discussed using theories encompassing empathy, sympathy and sensory re-calibration. The prospect of using this type of modified avatar for stroke rehabilitation is discussed.

Indexed as

AdaptationAvatarBiomedical engineeringEmpathyKnee flexionNeuroscienceRehabilitationSympathy

Identifiers

PMID31844726
PMCPMC6895732
OpenAlexW2988347492

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.