Detection of balance disorders using rotations around vertical axis and an artificial neural network

Sci Rep. 2022 May 6;12(1):7472. doi: 10.1038/s41598-022-11425-z.

Abstract

Vestibular impairments affect patients' movements and can result in difficulties with daily life activities. The main aim of this study is to answer the question whether a simple and short test such as rotation about a vertical axis can be an objective method of assessing balance dysfunction in patients with unilateral vestibular impairments. A 360˚ rotation test was performed using six MediPost devices. The analysis was performed in three ways: (1) the analytical approach based only on data from one sensor; (2) the analytical approach based on data from six sensors; (3) the artificial neural network (ANN) approach based on data from six sensors. For approaches 1 and 2 best results were obtained using maximum angular velocities (MAV) of rotation and rotation duration (RD), while approach 3 used 11 different features. The following sensitivities and specificities were achieved: for approach 1: MAV-80% and 60%, RD-69% and 74%; for approach 2: 61% and 85% and RD-74% and 56%; for approach 3: 88% and 84%. The ANN-based six-sensor approach revealed the best sensitivity and specificity among parameters studied, however one-sensor approach might be a simple screening test used e.g. for rehabilitation purposes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Movement*
  • Neural Networks, Computer
  • Vestibular Function Tests*