Evidence map›Paper›PMID 42741243›Full record

ArticleMethodsX2026

A protocol for assessing virtual and mixed reality environments with real-time electromyographic (EMG) biofeedback during upper limb physical exercises.

Mazen Talaat Haggag, Mohammed Ibrahim Awad, Ahmed Mohamed Elbokl, Bassem Amin Abdullah

Abstract read
In one paragraph

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

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

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

4 authors.

Mazen Talaat HaggagDepartment of Mechatronics Engineering, Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Mohammed Ibrahim AwadDepartment of Mechatronics Engineering, Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Ahmed Mohamed ElboklHuman Centered Mechatronics (HCM) Lab, Virtual Hospital, Ain Shams University, Cairo, Egypt.
Bassem Amin AbdullahDepartment of Computer and Systems Engineering, Faculty of Engineering, Ain Shams University, Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper describes a protocol for a controlled laboratory study designed to evaluate how immersive real-time electromyographic (EMG) biofeedback affects standardized shoulder exercise performance and user experience in healthy adults. Participants aged 20-30 years will be randomly allocated to virtual reality (VR), mixed reality (MR), or a non-immersive control condition. Within the immersive arms, each participant will experience three EMG visualization modes (an anatomically mapped avatar, a dynamic bar display, and a live waveform graph) in randomized order. During five standardized shoulder exercises, bilateral deltoid activity will be recorded using six wireless EMG sensors, while three-dimensional kinematics will be captured with an optical motion-capture system. Outcomes will include joint-angle accuracy, normalized muscle activation, compensatory motion, range of motion, movement speed, task completion time, together with perceived exertion, simulator sickness, and system usability. By integrating synchronized EMG and motion-capture data with immersive feedback delivery, this protocol provides a reproducible framework for comparing VR and MR biofeedback environments and evaluating how visualization mode may influence exercise execution and user experience.•Compares VR, MR, and non-immersive shoulder exercise conditions.•Evaluates avatar, bar, and waveform EMG visualization modes.•Combines EMG, motion capture, and subjective assessments.

Indexed as

BiofeedbackElectromyographyKinematicsMotion captureRehabilitation engineeringShoulder exercise

Identifiers

PMID42741243
PMCPMC13572515

What OpenQuestion holds

Textmetadata
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.