Evidence map›Paper›PMID 41321501›Full record

ArticleFrontiers in physiology2025

Sensory reweighting for postural stability in individuals with low vision and blindness: balance adaptation and muscle co-contraction.

Yue Li, Shilun Hou, Xin Zhang, Anli Wang

Abstract read
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Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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.

Yue LiCollege of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing, China.
Shilun HouCollege of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing, China.
Xin ZhangCollege of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing, China.
Anli WangCollege of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Individuals with visual impairments frequently experience postural instability during daily activities, considerably increasing the risk of falls. However, the mechanisms by which visually impaired individuals maintain balance through sensory reweighting remain unclear. We therefore aimed to investigate sensory reweighting for postural control in individuals with low vision and blindness by integrating measures of postural performance, biomechanical forces, and muscle co-contraction. Methods: Seventy-four participants were recruited (19 participants with normal vision, 36 participants with low vision, and 19 participants being blind). Each participant completed postural tasks under two conditions: open/closed eyes and firm/foam surfaces. Postural performance was evaluated with single-leg and tandem stance durations. The center of pressure (COP) during bipedal stance was collected using a force platform. Simultaneously, integrated EMG was acquired via wireless surface electromyography from six dominant-side muscles: erector spinae, rectus abdominis, rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius. Results: We observed significant group × vision interactions for COP Path Length and Sway Area. The blind group exhibited the highest AP_HF% on a firm surface, confirming that individuals with visual impairment exhibit somatosensory compensation to maintain postural control. Individuals with low vision presented heightened sensitivity to partial sensory deprivation, with significantly increased Path Length and Sway Velocity. Additionally, a significant interaction between vision and somatosensation was observed, along with significant main effects of vision and somatosensation of all COP parameters. Muscle activity further supported these findings. The rectus abdominis/erector spinae ratio decreased significantly with somatosensory deprivation, whereas the gastrocnemius/tibialis anterior co-contraction index increased significantly under both visual and somatosensory deprivation, with higher co-contraction observed in both low-vision and blind participants. Conclusion: Blind individuals rely primarily on somatosensory input for sensory reweighting, while those with low vision show impaired compensation due to residual vision, resulting in the most impaired postural control. Ankle muscle co-contraction serves as the primary strategy for maintaining postural stability in visually impaired individuals.

Indexed as

center of pressuremuscle co-contractionposture controlsensory reweightingvisual impairment

Identifiers

PMID41321501
PMCPMC12660077

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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.