Neuromotor changes in participants with a concussion history can be detected with a custom smartphone app.

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture.

Gait dynamics when wearing a treadmill safety harness.

Nonlinear dynamics quantifies gait variability patterns, which can be useful in evaluating functional ability. A commonly used nonlinear technique is detrended fluctuation analysis (DFA). Safety support structures have previously been shown to alter DFA during gait. However, the effect of a nonweight-supporting treadmill harness on DFA during gait has yet to be determined. The purpose of this study was to determine whether a nonweight-supporting harness influenced the DFA alpha metric (DFA α) of variables typically used to examine gait function. Twenty participants (10 young adults and 10 older adults) were recruited for this study. Each participant completed one testing session on a treadmill consisting of three conditions: (1) no harness, (2) harnessed, but not attached to the support frame, and (3) harnessed and attached to the support frame. Participants walked for 15 min at the same self-selected speed for each condition. The gait variables of stride time, stride length, and step width for each condition were analyzed using DFA α to examine gait function. There were no significant interactions between age group and condition for DFA α of each variable. Additionally, there were no main effects for DFA α for age group or condition. These data indicate that a nonweight-supporting harness can be used for safety without impeding the emergence of natural gait dynamics when stride time, stride length, and step width are the primary variables of interest.