Evidence map›Paper›PMID 35954882›Full record

ArticleInternational journal of environmental research and public health2022

Affective States and Virtual Reality to Improve Gait Rehabilitation: A Preliminary Study.

Jafet Rodriguez, Carolina Del-Valle-Soto, Javier Gonzalez-Sanchez

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Affective Computing in Serious Games for Physical Rehabilitation: Scoping Review.JMIR rehabilitation and assistive technologies · 2026
    Review
  2. Enhanced Rehabilitation Outcomes of Robotic-Assisted Gait Training with EksoNR Lower Extremity Exoskeleton in 19 Stroke Patients.Medical science monitor : international medical journal of experimental and clinical research · 2023
    Observational
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

3 authors.

Jafet RodriguezUniversidad Panamericana, Facultad de Ingeniería, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico.ORCID 0000-0002-4057-3191
Carolina Del-Valle-SotoUniversidad Panamericana, Facultad de Ingeniería, Álvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico.ORCID 0000-0002-0272-3275
Javier Gonzalez-SanchezSchool of Computing and Augmented Intelligence, Arizona State University, 699 S Mill Ave, Tempe, AZ 85281, USA.ORCID 0000-0001-6444-1858

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over seven million people suffer from an impairment in Mexico; 64.1% are gait-related, and 36.2% are children aged 0 to 14 years. Furthermore, many suffer from neurological disorders, which limits their verbal skills to provide accurate feedback. Robot-assisted gait therapy has shown significant benefits, but the users must make an active effort to accomplish muscular memory, which usually is only around 30% of the time. Moreover, during therapy, the patients' affective state is mostly unsatisfied, wide-awake, and powerless. This paper proposes a method for increasing the efficiency by combining affective data from an Emotiv Insight, an Oculus Go headset displaying an immersive interaction, and a feedback system. Our preliminary study had eight patients during therapy and eight students analyzing the footage using the self-assessment Manikin. It showed that it is possible to use an EEG headset and identify the affective state with a weighted average precision of 97.5%, recall of 87.9%, and F1-score of 92.3% in general. Furthermore, using a VR device could boost efficiency by 16% more. In conclusion, this method allows providing feedback to the therapist in real-time even if the patient is non-verbal and has a limited amount of facial and body expressions.

Indexed as

Exercise TherapyVirtual RealityChildEmotionsGaitHumansaffective stateBCIEEGgaitHCIrehabilitationrobot-assistedvirtual reality

Identifiers

PMID35954882
PMCPMC9368422

What OpenQuestion holds

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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.