Reliability of assessing trunk motor control using position and force tracking and stabilization tasks

N. Peter Reeves, John M. Popovich, M. Cody Priess, Jacek Cholewicki, Jongeun Choi, Clark J. Radcliffe

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


System-based methods have been applied to assess trunk motor control in people with and without back pain, although the reliability of these methods has yet to be established. Therefore, the goal of this study was to quantify within- and between-day reliability using systems-based methods involving position and force tracking and stabilization tasks. Ten healthy subjects performed six tasks, involving tracking and stabilizing of trunk angular position in the sagittal plane, and trunk flexion and extension force. Tracking tasks involved following a one-dimensional, time-varying input signal displayed on a screen by changing trunk position (position tracking) or trunk force (force tracking). Stabilization tasks involved maintaining a constant trunk position (position stabilization) or constant trunk force (force stabilization) while a sagittal plane disturbance input was applied to the pelvis using a robotic platform. Time and frequency domain assessments of error (root mean square and H2 norm, respectively) were computed for each task on two separate days. Intra-class correlation coefficients (ICC) for error and coefficients of multiple correlations (CMC) for frequency response curves were used to quantify reliability of each task. Reliability for all tasks was excellent (between-day ICC≥0.8 and CMC>0.75, within-day CMC>0.85). Therefore, position and force control tasks used to assess trunk motor control can be deemed reliable.

Original languageEnglish
Pages (from-to)44-49
Number of pages6
JournalJournal of Biomechanics
Issue number1
Publication statusPublished - 2014 Jan 3

Bibliographical note

Funding Information:
This study was supported by a National Institutes of Health U19 research award (Grant no. AT006057 ) involving a partnership with the National Center for Complementary and Alternative Medicine. The authors would like to thank Kiilani Kaaikala for her assistance in data collection and Angela Lee for her assistance in developing data collection software.

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Orthopedics and Sports Medicine
  • Biomedical Engineering
  • Rehabilitation


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