Evidence map›Paper›PMID 42898406›Full record

ArticleFrontiers in bioengineering and biotechnology2026

Variable task difficulty with augmented sensory feedback for motor training in virtual reality.

Yu Shi, Sophie Dewil, Zachary Marvin, Noam Y Harel, Raviraj Nataraj

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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.

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

5 authors.

Yu ShiDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
Sophie DewilDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
Zachary MarvinDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
Noam Y HarelSpinal Cord Damage Research Center, James J. Peters VA Medical Center, Bronx, NY, United States.
Raviraj NatarajDepartment of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study examined how motor task difficulty and augmented sensory feedback (ASF) modality influence task performance, physiological responses, and perceptual experience during virtual reality (VR)-based upper-limb motor training. Building on related brace- and VR-based ASF platforms previously examined in neurotypical and spinal cord injury cohorts, the long-term goal is to support neurorehabilitation-oriented adaptive VR training; however, the present study used neurotypical participants as an initial validation step. Methods: Fourteen right-handed neurotypical participants used a supportive upper-limb brace and surface electromyography (EMG) for myoelectric control of a virtual robotic arm in a two-dimensional tracking task. A 2 × 2 within-subject design crossed ASF modality (visual feedback versus visual + haptic feedback) with task difficulty (straight-line versus sinusoidal trajectory). Outcomes included normalized path length, task completion time, movement jerk, alpha- and beta-band electroencephalogram (EEG) power over motor cortex, heart rate, EMG amplitude, EMG-displacement-based virtual work, and perceptual ratings of agency, motivation, and utility. Short-term pre-to-post percentage changes were computed for each measure. Results: VHF straight-line training produced the largest reductions in normalized path length (-4.69%) and completion time (-6.12%), whereas VHF sinusoid training produced the largest reductions in movement jerk (-5.67%) and virtual work (-13.33%). ASF modality affected path length, completion time, jerk, EMG amplitude, and virtual work, whereas task difficulty modulated beta-band EEG power and the physiological index. Changes in path length were positively associated with changes in completion time and EMG amplitude. Discussion: These findings suggest that ASF modality and task difficulty can differentially shape short-term behavioral, physiological, and perceptual responses in healthy participants. The exploratory distribution of participant-specific best-case conditions motivates future studies using independent trial subsets to evaluate whether behavioral and physiological measures can support individualized VR training.

Indexed as

augmented sensory feedbackmovement rehabilitationperceptualphysiological responsetask difficultyvirtual reality

Identifiers

PMID42898406
PMCPMC13677916

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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.