This study evaluated the within- and between-visit reliability of a seated balance test for quantifying trunk motor control using input–output data. Thirty healthy subjects performed a seated balance test under three conditions: eyes open (EO), eyes closed (EC), and eyes closed with vibration to the lumbar muscles (VIB). Each subject performed three trials of each condition on three different visits. The seated balance test utilized a torque-controlled robotic seat, which together with a sitting subject resulted in a physical human-robot interaction (pHRI) (two degrees-of-freedom with upper and lower body rotations). Subjects balanced the pHRI by controlling trunk rotation in response to pseudorandom torque perturbations applied to the seat in the coronal plane. Performance error was expressed as the root mean square (RMSE) of deviations from the upright position in the time domain and as the mean bandpass signal energy (Emb) in the frequency domain. Intra-class correlation coefficients (ICC) quantified the between-visit reliability of both RMSE and Emb. The empirical transfer function estimates (ETFE) from the perturbation input to each of the two rotational outputs were calculated. Coefficients of multiple correlation (CMC) quantified the within- and between-visit reliability of the averaged ETFE. ICCs of RMSE and Emb for all conditions were ≥0.84. The mean within- and between-visit CMCs were all ≥0.96 for the lower body rotation and ≥0.89 for the upper body rotation. Therefore, our seated balance test consisting of pHRI to assess coronal plane trunk motor control is reliable.
Bibliographical noteFunding Information:
This publication was made possible in part by grant number U19 AT006057 from the National Center for Complementary and Integrative Health (NCCIH) at the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NCCIH.
All Science Journal Classification (ASJC) codes
- Orthopedics and Sports Medicine
- Biomedical Engineering