ArticleScientific reports2025
A method for detection of functional deficiencies due to unilateral vestibular impairment using the TUG test and IMU sensors.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effects of hydrokinesitherapy on balance and walking ability for stroke survivors: update of a systematic review and meta-analysis of randomized controlled studies.European journal of physical and rehabilitation medicine · 2026Pooled it
- Recognition of Gait Alterations Induced by Alcohol-Impairment Simulation Goggles Using Smartphone Accelerometer Signals.Sensors (Basel, Switzerland) · 2026Article
- A deep learning pipeline for detecting vestibular schwannoma patients with unilateral vestibular loss based on kinematic data.Scientific reports · 2025Article
- Protocol for assessing functional impairments in patients with unilateral and bilateral vestibulopathy: a novel approach to evaluate the impact of vestibular loss in daily life setting.Frontiers in neurology · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Vestibular impairments affect movement and can result in difficulties with daily life activities. The main aim of this study is to determine whether a short, simple test such as the Timed Up and Go test (TUG) can be an objective method of assessing balance dysfunction in patients with unilateral vestibular impairments. The TUG test was performed using six MediPost devices. The analysis was performed in three ways: (1) an analytical approach based only on data from one sensor; (2) an analytical approach based on data from six sensors; (3) an artificial neural network (ANN) approach based on data from six sensors. The best results were obtained using maximum angular velocities (MAV) of rotation and total time (TT) for approaches 1 and 2, and using 43 different features for approach 3. The following sensitivities and specificities were achieved: MAV 95% and 70%, TT 73% and 88% for approach 1; MAV 60% and 91% and TT 64% and 98% for approach 2; 88% and 92% for approach 3. The ANN-based six-sensor approach demonstrated the best sensitivity and specificity; however, the one-sensor approach might be used as a simple screening test.
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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.