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DOI 10.1016/j.mex.2026.104122

Медицинская библиотека · MethodsX · 2026

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

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

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Аннотация

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.

Для цитирования: Haggag Mazen Talaat, Awad Mohammed Ibrahim, Elbokl Ahmed Mohamed, Abdullah Bassem Amin. A protocol for assessing virtual and mixed reality environments with real-time electromyographic (EMG) biofeedback during upper limb physical exercises.. MethodsX. 2026. DOI: 10.1016/j.mex.2026.104122.
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