No abstract

There is a dearth of knowledge about how symptom severity affects gait in the chronic (>3 months) mild traumatic brain injury (mTBI) population despite up to 53% of people reporting persisting symptoms following mTBI. The purpose of this investigation was to determine if gait is affected in a symptomatic, chronic mTBI group and to assess the relationship between gait performance and symptom severity on the Neurobehavioral Symptom Inventory (NSI). Gait was assessed under single-and dual-task conditions using five inertial sensors in 57 control subjects and 65 people with chronic mTBI (1.1 year from mTBI).The single-and dual-task gait domains of Pace, Rhythm, Variability, and Turning were calculated from individual gait characteristics. Dual-task cost (DTC) was calculated for each domain. The mTBI group walked (domain z-score mean difference: single-task = 0.70; dual-task = 0.71) and turned (z-score mean difference: single-task = 0.69; dual-task = 0.70) slower (p<0.001) under both gait conditions, with less rhythm under dual-task gait (z-score difference = 0.21, p=0.001). DTC was not different between groups.Higher NSI somatic sub-score was related to higher single-and dual-task gait variability as well as slower dual-task pace and turning (p<0.01). People with chronic mTBI and persistent symptoms exhibited altered gait, particularly under dual-task, and worse gait performance related to greater symptom severity. Future gait research in chronic mTBI should assess the possible underlying physiological mechanisms for persistent symptoms and gait deficits.

Balance during stance is regulated by active control mechanisms that continuously estimate body motion, via a “sensory integration” mechanism, and generate corrective actions, via a “sensory-to-motor transformation” mechanism. The balance control system can be modeled as a closed-loop feedback control system for which appropriate system identification methods are available to separately quantify the sensory integration and sensory-to-motor components of the system. A detailed, functionally meaningful characterization of balance control mechanisms has potential to improve clinical assessment and to provide useful tools for answering clinical research questions. However, many researchers and clinicians do not have the background to develop systems and methods appropriate for performing identification of balance control mechanisms. The purpose of this report is to provide detailed information on how to perform what we refer to as “central sensorimotor integration” (CSMI) tests on a commercially available balance test device (SMART EquiTest CRS, Natus Medical Inc, Seattle WA) and then to appropriately analyze and interpret results obtained from these tests. We describe methods to (1) generate pseudorandom stimuli that apply cyclically-repeated rotations of the stance surface and/or visual surround (2) measure and calibrate center-of-mass (CoM) body sway, (3) calculate frequency response functions (FRFs) that quantify the dynamic characteristics of stimulus-evoked CoM sway, (4) estimate balance control parameters that quantify sensory integration by measuring the relative contribution of different sensory systems to balance control (i.e., sensory weights), and (5) estimate balance control parameters that quantify sensory-to-motor transformation properties (i.e., feedback time delay and neural controller stiffness and damping parameters). Additionally, we present CSMI test results from 40 subjects (age range 21–59 years) with normal sensory function, 2 subjects with results illustrating deviations from normal balance function, and we summarize results from previous studies in subjects with vestibular deficits. A bootstrap analysis was used to characterize confidence limits on parameters from CSMI tests and to determine how test duration affected the confidence with which parameters can be measured. Finally, example results are presented that illustrate how various sensory and central balance deficits are revealed by CSMI testing.

Balance and mobility issues are common non-resolving symptoms following mild traumatic brain injury (mTBI). Current approaches for evaluating balance and mobility following an mTBI can be subjective and sub-optimal as they may not be sensitive to subtle deficits, particularly in those with chronic mTBI. Wearable inertial measurement units (IMU) allow objective quantification of continuous mobility outcomes in natural free-living environments. This study aimed to explore free-living mobility (physical activity and turning) of healthy and chronic mild traumatic brain injury (mTBI) participants using a single IMU. Free-living mobility was examined in twenty-three healthy control (48.56±23.07years) and twentynine symptomatic mTBI (40.2±12.1years) participants (average 419days post-injury, persistent balance complaints) over one week, using a single IMU placed at the waist. Free-living mobility was characterized in terms of Macro (physical activity volume, pattern and variability) and Microlevel (discrete measures of turning) features. Macro-level outcomes showed those with chronic mTBI had similar quantities of mobility compared to controls. Micro-level outcomes within walking bouts showed that chronic mTBI participants had impaired quality of mobility. Specifically, people with chronic mTBI made larger turns, had longer turning durations, slower average and peak velocities (all p<.001) and greater turn variability compared to controls. Results highlighted that the quality, rather than quantity of mobility differentiated chronic mTBI from controls. Our findings support the use of free-living IMU continuous monitoring to enhance understanding of specific chronic mTBI-related mobility deficits. Future work is required to develop an optimal battery of free-living measures across the mTBI spectrum to aid application within clinical practice.