Validation of an accelerometer-based gait assessment: Establishing test-retest reliability, convergent validity, and predictive validity for concussion symptom endorsement

Abstract

Gait accelerometer (sensor) technology has proven effective in predicting several medical outcomes, but less is known regarding its prediction of concussion symptoms relative to conventional measures of gait and balance. To establish the reliability and validity of gait accelerometer data. We first examine test-retest reliability and the impact of footwear and walking surfaces on gait. We then examine the convergent validity between gait accelerometer data and the NIH 4-meter gait test. Finally, we compare gait accelerometer data to gait speed and balance measures for predicting concussion symptoms. Study 1 used a crossover study design with 60 participants to evaluate retest reliability and examine the effects of footwear (shoes/no-shoes) and walking surface (tile floor/grass) on gait accelerometer data. Study 2 employed a cross-sectional design with 1008 participants to assess gait accelerometer correlations with NIH 4-meter gait and the prediction of Centers for Disease Control and Prevention (CDC) concussion symptoms relative to previously validated gait and balance measures. Retest reliability (4-day average retest interval) for the no shoes/tile surface condition ranged from .72-.91 (mean = .80). Significant effects of footwear and especially walking surface revealed by Analysis of Variances (ANOVAs) on gait accelerometer data for the power, stride, balance, and symmetry domains indicate the need to standardize these variables. Gait accelerometer data correlates significantly with NIH 4-meter gait scores. Regression analyses found that gait accelerometer data predicts CDC concussion symptom endorsement, outperforming the BESS and NIH 4-meter gait at least three-fold. When standardized on footwear and walking surface, gait accelerometers achieve strong test-retest reliability, converge with established measures of gait speed, and are superior to established measures of gait speed and balance when predicting concussion symptoms. Gait accelerometers represent a rapid tool for collecting additional gait information to quantify the behavioral sequelae of concussion and potentially inform return-to-play decision-making.