Bazanova, O M, Kovaleva, A V · Human physiology · 2022 · DOI
This review examines how balance training using computer feedback can help improve thinking, mood, and symptom management in people with chronic fatigue syndrome and other neurological conditions. The researchers looked at studies from Russia and other countries that used a technique called stabilometric biofeedback, which shows patients real-time information about their body's balance and posture to help them improve control and function.
For ME/CFS patients, this review is significant because it explores non-pharmacological rehabilitation approaches targeting postural control and balance dysfunction, symptoms commonly experienced in the condition. Understanding biofeedback-based interventions could offer potential complementary strategies for cognitive and emotional symptoms that accompany physical dysfunction in ME/CFS.
This review does not prove that stabilometric biofeedback is effective specifically for ME/CFS, as it combines evidence across multiple different conditions with potentially distinct mechanisms. It does not establish causation between postural control improvements and cognitive/affective gains, nor does it compare biofeedback to other rehabilitation approaches or identify which ME/CFS patients might benefit most.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
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Primary citation
Bazanova, O M & Kovaleva, A V (2022). Stabilometric Biofeedback Training in Cognitive and Affective Function Improvement. Contribution of the Russian Scientific School. Part II.. Human physiology. https://doi.org/10.1134/S0362119722030021
BibTeX
@article{mecfsatlas-bazanova-2022-stabilometric-biofeedback,
author = {Bazanova, O M and Kovaleva, A V},
title = {Stabilometric Biofeedback Training in Cognitive and Affective Function Improvement. Contribution of the Russian Scientific School. Part II.},
journal = {Human physiology},
year = {2022},
doi = {10.1134/S0362119722030021},
note = {PubMed: 35677212},
url = {https://www.mecfsatlas.com/evidence/bazanova-2022-stabilometric-biofeedback},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-27. https://www.mecfsatlas.com/evidence/bazanova-2022-stabilometric-biofeedback
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