THE EFFECT OF CONCUSSION ON THE METABOLIC COST OF TRANSPORT IN WALKING. Jessica A. La Farga. A Thesis Presented to

THE EFFECT OF CONCUSSION ON THE METABOLIC COST OF TRANSPORT IN WALKING By Jessica A. La Farga A Thesis Presented to The Faculty of Humboldt State University In Partial Fulfillment of the Requirements for the Degree Master of Kinesiology: Exercise Science Committee Membership Dr. Justus Ortega, Committee Chair Dr. Rock Braithwaite, Committee Member and Graduate Coordinator Beth Larson, M.S., Committee Member July, 2015

Abstract THE EFFECT OF CONCUSSION ON THE METABOLIC COST OF TRANSPORT IN WALKING Jessica A. La Farga A concussion is a type of traumatic brain injury that results in an overall decrease in executive function. Previous literature has reported that significant reductions in balance occur in the concussed during the acute phases of recovery. However, it is unknown whether changes in stability associated with concussive injury result in changes to conservation of mechanical energy and metabolic cost during walking. The purpose of this study was to determine the effect of concussion the mechanics and energetics of walking. I hypothesized that within the first 2-7 days following injury, individuals who have sustained a concussion would exhibit a greater the metabolic cost of walking and impaired inverted pendulum mechanics. To address this problem, I collected neurocognitive, metabolic, and kinematic data on 14 normal subjects (5 female and 9 male) and 10 concussed subjects (5 female and 5 male). I found no significant differences in the metabolic cost of transport due to concussive status across the speeds of 0.75 m s -1, 1.25 m s -1, and 1.50 m s -1 (p<.05). Key words: concussion, inverted pendulum, cost of transport, executive function ii

Acknowledgements To Rhonda, To Terry, To Kevin, To Jenn, To Cecelia. To using my brain because I can. To the women in this world who are not given the same opportunity. To the lessons that I learned in 256B. To the mentors who taught me true grit. To the relentless hearts that raised me- Thank you. iii

Table of Contents PAGE Abstract... ii Acknowledgements... iii Table of Contents... iv List of Tables... vi List of Figures... vii Introduction... 1 The Neurophysiology of Concussion... 1 Executive Function and Postural Stability... 2 Determinants of Walking Energetics... 4 Altered Walking Mechanics in the Concussed... 6 Assumptions... 7 Delimitations... 8 Operational Definitions... 8 Methods... 11 Subjects... 11 Protocol... 11 The Metabolic Cost of Transport... 12 Walking Mechanics... 13 Neurocognitive Assessment... 15 Statistics... 16 iv

Results... 17 Metabolic Cost of Transport... 17 Walking Mechanics... 17 Neurocognitive Function... 19 Discussion... 20 References... 33 v

List of Tables Table 1. Subject Characteristics. 25 Table 2. Spatio-temporal Variables...26 Table 3. Inverted Pendulum Mechanics Variables...27 Table 4. Neurocognitive Performance Composite Scores.28 vi

List of Figures Figure 1. Cost of Transport vs. Speed...29 Figure 2. Inverted Pendulum Energy Recovery vs. Speed..........30 Figure 3. External Work vs. Speed...31 Figure 4. Gross Metabolic Power vs. Speed......32 vii

1 Introduction A concussion is a type of brain injury that is caused when an impulsive force is transmitted through the head at a relatively low velocity (Paul McCrory et al., 2013). The injury may or may not involve loss of consciousness (P. McCrory et al., 2009; Paul McCrory, et al., 2013). Transient physiological changes challenge the brain s ability to integrate multiple forms of sensory information and lead to an increased difficulty in maintaining balance during walking. In healthy adults, the metabolic cost of maintaining balance has been shown to account for as much as 5-8% of the total metabolic cost of walking (J. Maxwell Donelan, Shipman, Kram, & Kuo, 2004; J. D. Ortega, Fehlman, & Farley, 2008). Moreover, changes in walking mechanics similar to those observed in concussed individuals have been associated with increases in the metabolic cost of walking. The Neurophysiology of Concussion A concussion is caused by direct or indirect biomechanical forces (Paul McCrory, et al., 2013; Signoretti et al., 2001) and the results in a transient period of axonal injury and metabolic disturbances (Barkhoudarian, Hovda, & Giza, 2011; Giza & Hovda, 2001). As a force is transmitted through the brain, it will stretch and compresses the cell membranes of the neurons (Barkhoudarian, et al., 2011; Giza & Hovda, 2001). Breaches in the neuronal membrane cause diffuse depolarization, indiscriminate neurotransmitter release, and may overstress the sodium / potassium pump (Barkhoudarian, et al., 2011; Giza & Hovda, 2001). If restoration of neurometabolism is

2 mismanaged, then chronic unresolved disturbances may result in the loss of microtubule structure and may eventually lead to apoptosis (Baldwin, Fugaccia, Brown, Brown, & Scheff, 1996; Barkhoudarian, et al., 2011; Gavett, Stern, Cantu, Nowinski, & McKee, 2010; Giza & Hovda, 2001). Research has found that repetitive trauma to the brain leads to a progressive and distinctive taupathy that is characterized by wide disposition of neurofibrillary tangles, relative absence of amyloid-b tau deposits, (Gavett, et al., 2010; McKee et al., 2009; McKee et al., 2010) and is recognized by the medical community as chronic traumatic encephalopathy (CTE) (McKee, et al., 2009; Omalu et al., 2006; Omalu et al., 2005; Stern et al., 2011; Yi, Padalino, Chin, Montenegro, & Cantu, 2013). Acute symptoms due to receiving a concussion are reported to resolve in the first 24 hrs. to 7 days after an injury has occurred (Signoretti, et al., 2001). Cognitive, emotional, physical, or sleeping symptoms are commonly reported (Moser et al., 2007). Manifestations of cognitive dysfunctions include impaired attention, memory, processing speed and reaction time (Schatz, Pardini, Lovell, Collins, & Podell, 2006). Depression, anger, and irritability are commonly reported as changes in emotion (Chen, Kareken, Fastenau, Trexler, & Hutchins, 2003). Physical symptoms such as light sensitivity, sound sensitivity, dizziness, nausea, and vomiting also occur. Finally, changes in balance are also commonly reported and used to measure the severity of concussion in the acute phases of concussion recovery (Kevin M. Guskiewicz, 2001). Executive Function and Postural Stability Postural stability is essential for the maintenance of balance in both static (still) and dynamic (moving) tasks. Postural control is an attention demanding process that requires

3 the use of executive function (Resch, May, Tomporowski, & Ferrara, 2011). Executive function describes the processes of integrating information through various neural networks located in the cerebral cortex, cerebellum, basal ganglia, brain stem, and spinal cord, amongst other balance systems (Geurts, Ribbers, Knoop, & van Limbeek, 1996; K. M. Guskiewicz, 2003). Dynamic stability is the ability to respond to changes in balance during movement, and is a process that requires coordination of numerous muscle groups in a specific sequence and magnitude in order to respond to perturbations in balance. The concussed experience altered brain function, which results in a decrease in postural control. Researchers and medical personnel can observe the acute period of postural instability by utilizing static balance tests such as the Balance Error Scoring System (BESS), the Clinical Test of Sensory Integration and Balance (CTSIB), the Sensory Organization Test (SOT), and the Romberg Test (Bell, Guskiewicz, Clark, & Padua, 2011; Murray, Ambati, Contreras, Salvatore, & Reed-Jones, 2014). These tests report that the greatest changes in stability occur within 24-72 hours of receiving a concussion (Kevin M. Guskiewicz, 2001; K. M. Guskiewicz, 2003). Changes in stability are reported as an increase in sway velocity in the anterior/posterior (A-P) or the mediolateral (M-L) directions (Geurts, et al., 1996; Kevin M. Guskiewicz, 2001; K. M. Guskiewicz et al., 2003). Concussion related changes in gait stability have been observed during obstacle crossing tasks as significantly faster CoM motion in the M-L direction (R. D. Catena, van Donkelaar, & Chou, 2009; Chou, Kaufman, Walker-Rabatin, Brey, & Basford, 2004), significantly slower peak anterior velocities during walking (R. Catena, Donkelaar, & Chou, 2007), and an increase sway velocity in the M-L direction during static balance tests in conditions calling for reduced proprioceptive input (Kevin M.

4 Guskiewicz, 2001). Overall, the concussed are reported to and have a significantly slower preferred walking speed, walk with shorter stride lengths, and experience an increase in step width variability (Chou, et al., 2004). Determinants of Walking Energetics Walking is an energy-requiring task that is accomplished by the cyclical transfer the center of mass (CoM) from one stance leg to the next (Kuo, Donelan, & Ruina, 2005) Cavagna, Willems et al. (2002). During walking, the stance leg acts as an inverted pendulum that allows for the exchange of potential energy (PE) and kinetic energy (KE). More specifically, during the first half of the gait cycle as the center of mass rises in height and slows down, KE is transferred into PE. During the second half of the gait cycle as the center of mass is lowed and accelerated forward, PE is transferred back in KE. The magnitude of inverted pendulum energy exchange depends on three key factors including 1) the magnitude of KE and PE fluctuations, 2) the relative phase angle between KE and PE and 3) the rates of decrease and increase of PE and KE. In a perfect inverted pendulum KE and PE would have exactly the same magnitude and fluctuate exactly opposite one another leading to 100% conservation of mechanical energy (Cavagna & Franzetti, 1986). However, walking only recovers about 65% of the mechanical energy exchange via the inverted pendulum mechanics. The rest of the mechanical energy required for walking must them be supplied by the mechanical work performed by the muscles of the body. (Johnston, 1984). The greatest recovery of mechanical energy occurs at the intermediate speeds of walking, i.e.1.20-1.35 m s -1. At

5 these intermediate walking speeds, the metabolic cost of moving the body a given distance (cost of transporting) is minimized (J. M. Donelan, Kram, & Kuo, 2001b). At faster and slower walking speed both the mechanical work required for walking and the metabolic cost of walking increase as the inverted pendulum exchange of mechanical energy decreases.. During walking the body must perform mechanical work to lift and accelerate the body. The amount of mechanical work performed during walking is inversely related to the inverted pendulum exchange of mechanical energy and thus is directly related to the metabolic cost of walking (J. M. Donelan, Kram, & Kuo, 2002b). Mechanical energy is conserved the most when the fluctuations of PE and KE 180 degrees out of phase with each other (Cavagna, et al., 2002; Johnston, 1984). When the inverted pendulum exchange of mechanical energy is altered, the body must perform more external work to lift and accelerate the CoM, and thus use more metabolic energy to travel the same distance. Thus, inverted pendulum mechanics heavily influence the amount of metabolic energy required for walking. There are certain parameters that contribute to inverted pendulum energy recovery. In addition to choosing energetically optimal walking speeds (Kuo, et al., 2005), humans choose a stride frequency (strides per second) that minimizes energy expenditure by optimizing external and internal work (J. M. Donelan, Kram, & Kuo, 2002a; Minetti, Capelli, Zamparo, di Prampero, & Saibene, 1995). Other parameters that dictate the amount of mechanical energy recovered in a system include stride length and stride width. (Minetti, et al., 1995).

6 Altered Walking Mechanics in the Concussed The concussed tend to walk with characteristics similar to other populations known to have conservative gait mechanics. Those populations with diminished balance typically use a slower preferred walking speed (Fait, McFadyen, Swaine, & Cantin, 2009; Pai & Patton, 1997), shorter stride lengths (Pai & Patton, 1997; Parker, Osternig, Lee, Donkelaar, & Chou, 2005), a reduction in sagittal plane, A-P CoM velocity (R. D. Catena, et al., 2009) and an increase in ML CoM velocity (R. Catena, et al., 2007). Research has found that walking with an increased step width causes an increase in external work to redirect the CoM in the ML direction (Ortega & Farley, 2007). Moreover, prior research suggests that walking at a slower walking speed and with a greater step frequency increases the overall metabolic cost of walking (Cavagna & Franzetti, 1986). Prior to this study, there was not sufficient literature investigating the effect of mild traumatic brain injuries such as a concussion on walking energetics and walking mechanics. Conservative gait mechanics typically observed during the acute phase of recovery may lead to impaired inverted pendulum energy exchange and a higher cost of transport during walking. The purpose of this research project was to determine if young adults who have sustained a concussion exhibit impaired walking mechanics including reduced mechanical energy exchange, increased mechanical work and thus a greater metabolic cost of transport during walking in the concussed. Based on evidence that the concussed individuals walk slower with a shorter stride length and have reduced stability compared to healthy controls, I hypothesized that the metabolic cost of transport will be greater in concussed as a result of impaired inverted pendulum mechanics. I predict that

7 individuals diagnosed with a concussion via ImPACT Test (ImPACT Applications, Inc., Pittsburgh, PA) will consume metabolic energy at a faster rate and perform a greater amount of mechanical work during walking. I also predict that the difference in rate of metabolic energy consumption between concussed and healthy subjects will be proportional to the difference in mechanical work performed. In order to better understand the potential mechanisms that may be responsible for change in metabolic cost and mechanical work resulting from concussion. I will also determine any difference in the percentage of mechanical energy recovered via inverted pendulum energy exchange. Assumptions The following were assumptions of the study: 1. Participants completed the medical history questionnaire and Immediate Post Injury and Cognitive Test (ImPACT ) accurately. 2. Participants were free of any orthopedic, cognitive, or neuromuscular diseases (other than concussion). 3. The equipment was calibrated correctly. 4. The data collected was valid & reliable. 5. Subjects walked with their own normal walking mechanics at each speed. 6. Subjects had experienced a concussive injury at least 24 hours after, and no more than seven days after a concussion.

8 Delimitations The following factors influenced the external validity of the study: 1. Participation in this study was delimited by its inclusion criteria (age, free of neurological and orthopedic, etc.). 2. The study did not include participants who had received a concussion in the past year. 3. The study was limited to 24 participants (14 healthy and 10 concussed). The study did not have equally balanced groups. 4. The study only included people living in Humboldt County, CA. 5. The results of the study will be generalizable to concussed young adults who (a) are between ages of 18-35, (b) and have no history of neurological, orthopedic, or cardiovascular diseases. 6. The study did not observe the cumulative effects of concussion. 7. There is no previous literature observing the metabolic changes, if any, in the concussed. This being said, the concussed were tested up to the seventh day past receiving a concussion. Researchers felt it appropriate to cast a widenet in hopes to aide in subject recruitment, adherence, symptom resolution, and data collection. Operational Definitions 1. Double support phase: the portion of the gait cycle when both feet are on the ground.

9 2. Executive function: The generalized term for the management of cognitive integration, including memory, reasoning, and execution. 3. External Mechanical Work (J kg -1 ): The work associated with lifting and accelerating the center of mass during walking normalized per kilogram of body mass. 4. Gravitational Potential Energy (PE, J kg -1 ): A form of mechanical energy associated with the height of the center of mass normalized per kilogram of body mass; Potential energy = (mass)(gravity)(height). 5. Inverted Pendulum Mechanics: Theory of describing walking locomotion, where the center of mass is above the pivot point (foot). 6. Kinetic Energy (KE, J kg -1 ):A form of mechanical energy associated with motion of the center of mass normalized per kilogram of body mass; Kinetic Energy = ½ (mass)(velocity) 2. 7. Mechanical Power: The rate of performing mechanical work (Watt kg -1 ) 8. Metabolic Cost: The rate of chemical energy consumption. Metabolic cost is most often normalized to body mass and is expressed as J kg -1 s -1. 9. Metabolic cost of transport (J kg -1 m -1 ) : Metabolic cost moving one kilogram of body mass one meter. 10. Stance time: the time that either foot is on the ground during a gait cycle including both double support and single support phase. 11. Single support phase: the portion of the gait cycle when only one foot is on the ground.

10 12. Stride frequency (Hz): strides per second measured from the duration of a gait cycle from foot strike of one foot the next ipsilateral foot strike. 13. Stride length: the distance traveled by the center of mass over the course of a gait cycle, from foot strike of one foot the next ipsilateral foot strike. 14. Swing phase: the time that either foot is NOT on the ground during a gait cycle and occurs after toe off until the subsequent foot strike.

11 Methods Subjects Subjects were recruited through the North Coast Concussion Program, the Humboldt State Student Health Center, local hospitals, and word of mouth. Twenty four participants [N = 24; 10 concussed and 14 healthy] were included in this study. All subjects were between the ages of 18 and 35 years (concussed 21.4 yrs. ± 3.1; healthy 22.0 yrs. ±2.6), free of any orthopedic, neuromuscular, or cognitive (other than concussion) diseases that may have altered inverted pendulum mechanics. To be included in the study, concussed subjects must have sustained a direct or indirect injury to the head and exhibit a significant decrease in cognitive function ImPACT Test administered by the North Coast Concussion Program (NCCP) within seven days of injury. The healthy group was composed of members of the Humboldt State University and Humboldt County community. Protocol Subjects participated in an experimental session that was approximately 2.5 hours long. After the orientation, each subject completed a neurocognitive assessment (approximately 30 minutes) and a walking assessment (approximately 90 minutes). The neurocognitive assessment took measures of neurocognitive function and symptom severity. To complete the test, subjects were taken to a quiet, segregated room where they were given a general overview of how the neurocognitive test was set designed in

12 adherence with NCCP protocol. Next, the walking assessment occurred and individuals were then taken to the HSU Redwood Bowl Track and directed to walk two laps (approximately 800m). Researchers measured the time required to cover a 45.72 meter section of course. This measurement was performed twice over the course of the test and averaged to calculate preferred walking speed (PWS). Next, I collected anthropometric measurements: leg length (mm), height (mm), and weight (kg). I used a caliper to measure ankle width, knee width, elbow width, wrist width, and hand thickness. After collecting all anthropometric measurements, I placed retro reflective marker balls on designated anatomical landmarks in preparation of data collection with motion capture software. These anthropometric measurements would later be used to construct a body model used for data analysis. Kinematic data was collected using Vicon Nexus 1.8.5 (Los Angeles, CA) at a sampling rate of 100 Hz. Subjects completed a total of five treadmill trials; 1 standing trial and 4 speed trials. A resting baseline metabolic trial was collected before the treadmill trials began. Next, subjects completed the four 6-minutes walking trials at four randomized speeds:.75m s -1, 1.25m s -1, 1.50 m s -1, and PWS). These trials were separated by a 3-5 minute rest period. The Metabolic Cost of Transport The metabolic cost of transport was determined using open circuit indirect calorimetry (Parvo Medics TrueOne2400, Sandy, Utah, USA). Indirect calorimetry measured the rates of oxygen consumption (V O 2 ) and carbon dioxide production (V CO 2 ) during a standing resting trial and each treadmill walking trial. Using the rates of O 2 and

13 CO 2 during the last two minutes of each trial when metabolic steady state has been achieved and a standard equation (Brockway, 1987), we calculated the rate of metabolic energy consumption for each trials (J s -1 ). I subtracted the standing metabolic rate from the walking metabolic rate to obtain a net metabolic power for each trial (J s -1 ). We divided net metabolic power by body mass (kg) and walking speed calculates cost of transport (J kg -1 m -1 ). Gross power (GP) was calculated by dividing the amount of work performed over time (Watt; J s -1 kg -1 ). Walking Mechanics Kinematic data was collected using a three-dimensional motion capture system (Vicon Nexus 1.8.5; Vicon, Centennial, CO) and a treadmill (Trackmaster Vision Inc.; Newton, Kansas) placed in the middle of the biomechanics laboratory and surrounded by 8 opto-electric cameras. We placed lightweight retro reflective spheres in accordance with Helen-Hayes Plug in Gait Full Body marker set to identify anatomical landmarks and designate lower and upper extremity segments. The thirty-two retro reflective marker balls were placed on the same anatomical positions of all subjects as follows: (2) toe, (2)heel, (2) ankle, (2) shank, (2) knee, (2) thigh, (2) anterior superior iliac spine, (2) posterior superior iliac spine, (2) radial wrist, (2) ulnar wrist, (2) elbow, (2) shoulder, (2) front head, and (2) back head. Additional retro-reflective marker balls were placed on the manubrium of the sternum, mid-clavicle, cervical spine seven, thoracic spine ten, and on the medial border of the right scapula.

14 Data was analyzed using Vicon Nexus 1.8.5, a digital motion capture and analysis program. Raw marker ball coordinate data was digitized and smoothed using a fourthorder, zero-lag digital Butterworth filter with a cutoff frequency of 6 Hz. Data was then imported into Visual 3D Version 5.0 (Germantown, Maryland) 3-D motion analysis software. Marker ball location was used to determine body segment, joint and whole body center of mass motion for ten consecutive strides of each trial. Center of mass motion (position and velocity) was then used to calculate the gravitation potential energy, or PE, (Joules), kinetic energy, or KE, (Joules), and total energy, PE + KE (Joules). I calculated the positive individual limb work performed on the center of mass by integrating each limb's power with respect to time for the time intervals when its power was positive (J. M. Donelan, et al., 2002b). I calculated the positive limb work because the positive limb work reflects the net positive external work performed on the center of mass to maintain walking speed (Ortega & Farley, 2007). In addition to center of mass motion, other spatio-temporal parameters that influence inverted pendulum energy and were measured included stride length, stride frequency, stride width, stride width variability, single support time, double support time, stance time, and swing time. Medio-lateral distance between proximal end position of the foot at ipsilateral heel strike to the proximal end position of the foot at the next contralateral heel strike. Stride width was calculated by taking a stride vector, and the step in between, and computing the cross product (distance between the stride vector and the opposing step (heel) position. Stride frequency (Hz) was determined by measuring the time required to take 20 strides during the last minute. Stride length (m) was calculated as the anterior-posterior distance traveled by the center of mass from one foot strike to

15 the subsequent ipsilateral foot strike and then averaged over 10 consecutive strides of each trial. As an additional measure of the potential for mechanical energy exchange during single support, we quantified the relative timing of gravitational potential energy and kinetic energy fluctuations by calculating phase angle (Cavagna & Franzetti, 1986): PPhaaaaaa AAAAAAAAAA = tt TT 360 + 180 (1) where t represents the time interval between minimum kinetic energy and maximum gravitational potential energy, and T represents the time interval between consecutive foot strikes. Thus when the minimum kinetic energy and maximum gravitational potential occurred simultaneously as required for optimal energy exchange, phase angle was 180. Neurocognitive Assessment The neurocognitive assessment was completed using the Immediate Post- Concussion Assessment and Cognitive Testing software (ImPACT Applications, Inc., Pittsburgh, PA). The ImPACT Test is a video-game like program that takes approximately 25-30 minutes to completes and includes a demographic section, symptom inventory, and six subtests measuring attention, memory, processing speed, and reaction time. The symptom inventory includes examinee self-report of 22 symptoms using a 7- point Likert-type rating scale (0 6) that when summed, provides an overall symptom score. The six subtests yield four individual composite scores including Verbal Memory, Visual Memory, Visual Motor (processing) Speed, Impulse Control and Reaction time.

16 Statistics The group by task interactions and the differences between groups were examined using SPSS 22.0 (SPSS Inc., Chicago, IL). A two (normal vs. concussed status) by three (speeds:.75m s -1, 1.25m s -1, and 1.50 m s -1 ) mixed model statistical model of variance (MANOVA) to determine the effect of status and the effect of speed on the metabolic cost of transport, walking mechanics. In addition, a one-way between groups multivariate analysis of variance (MANOVA) was used to determine the effect of concussion on neurocognitive test performance (p<.05). A post-hoc univariate analysis of variance (ANOVA) was used to determine group differences in each of the six cognitive domains: verbal memory, visual memory, visual motor speed, impulse control, reaction time, and a self-reported symptom score (p<.05).

17 Results Metabolic Cost of Transport Concussion did not have a significant effect on the metabolic cost of walking across the range of speeds tested (A=.72, F (5, 59) = 4.61, P=.53). While metabolic cost of transport was nearly identical between healthy and concussed subjects at the two lowest speeds, concussed subjects tended to have a lower cost of transport at the fastest speed of 1.50 m s -1 (Figure 1). Speed had a significant effect on cost of transport in both groups (A=.09, F(10,118) = 27.78, P=.0001) such that cost of transport was minimized at intermediate speed of 1.25 m s -1 and increase at slower and faster walking speed. Similarly, speed had a significant effect on gross metabolic power whereby gross metabolic power increased by an average 65% across the range of speeds (p<.0001). Walking Mechanics Across the range of speeds tested, concussed subjects exhibited similar walking mechanics when compared to healthy controls (A=.671, F (18, 45) = 1.22, p<.05). Both the concussed and the healthy used similar stride lengths (P=.725) and stride widths (P=.491), and exhibited a similar stance time (P=.669), swing time (P=.338), and double limb support time (P=.819; Table 2).

18 Both healthy and concussed subjects preferred to walk at similar speeds (P>.05; Table 1). Moreover, when concussed individuals walk at the same speeds as healthy controls they use similar gait mechanics (P=.284). Across the range of speeds tested, concussed subjects conserved a similar amount of mechanical energy via inverted pendulum mechanics (P=.072) and performed a similar amount of external mechanical work (P=.441; Figure 2). At the slowest speed of 0.75 m s -1, both groups recovered a similar amount of mechanical energy and performed a similar amount of mechanical work. However, at the faster speed of 1.25 m s -1, concussed subjects recovered 28% less mechanical energy as compared to healthy subjects. The difference in inverted pendulum energy recovery at 1.25 m s -1 is likely related to the fact that at this speed, concussed subjects performed 32% more external mechanical work compared to healthy subjects. However, at the fastest speed of 1.50 m s -1, concussed subjects recovered 10% less inverted pendulum energy but performed similar rates of external mechanical work. Although concussed and healthy subject had a similar fluctuations in potential energy (P=.533) and a similar phase angle between kinetic potential energy fluctuations (P=.692) across the range of speeds (Table 2), concussed subjects walked with ~45% smaller fluctuation in kinetic energy (P>.0001) (Table 3). Across the range of speeds tested, concussed and healthy gait mechanics changed similarly (P<.0001; Table 3). In both groups, both stride length and stride frequency increased by 24% and 36% respectively (P<.0001). Individuals from both groups spent more time in stance at the speed of 0.75 m s -1 and less time in stance at the fastest speed of 1.50 m s -1 (P<.001). Also, across the range of speeds tested, individuals spent more time in swing at the fastest speed of 1.50 m s -1 (P<.001). Specifically, from slowest to

19 fastest speed, stance time decreased by 42% and swing time increased by 20%. Both groups also, decreased the time spent in double limb support by 51% from the slowest to fastest speed. Related to these changes in gait kinematics, the recovery of mechanical energy decreased by 24% from the slowest to fastest speed (P<.0001). This decrease in mechanical energy recovery across the range of speeds is likely the results of a 5-fold increase in the external mechanical work performed (P<.0001). Moreover, while fluctuation in PE increased 3 fold across the range of speeds, fluctuations in KE also increased by 3-fold (P<.0001). However, the phase angle between PE and KE decreased by 6% when comparing the slowest speed to the fastest speed (P=.016). Overall, stride width and stride width variability did not change across the range of speeds (P=.112). Neurocognitive Function Concussion has a significant effect on neurocognitive function (P=.0005; Table 2). When compared to healthy subjects, concussed subjects had a decrease of 24%, 25%, and 29% in the verbal memory composite, visual memory motor composite, and reaction time composites, respectively. The concussed also have an increase of 57% in the impulse composite domain when compared to healthy subject scores. Overall, the average symptom report for healthy individuals was 2 at the time of testing; the average symptom report for concussed individuals was 33.

20 Discussion This investigation was the first to show that concussion is not associated with significantly different walking metabolics. This study was in support of previous literature describing that participants show significant differences in gait patterns when compared to healthy controls (Martini et al., 2011). I hypothesized that individuals in the acute phase of recovery would exhibit a greater metabolic cost of transport and impaired inverted pendulum mechanics as compared to healthy controls across each walking speed. I specifically predicted that 1) individuals diagnosed with a concussion via ImPACT Test (ImPACT Applications, Inc., Pittsburgh, PA) would consume metabolic energy at a faster rate and perform a greater amount of mechanical work during walking in the acute phase of recovery and 2) the difference in the rate of metabolic energy consumption between the concussed and healthy subjects would be proportional to the difference in mechanical work performed and the difference in mechanical energy recovered during walking. Contrary to our hypothesis, this study demonstrates that during the acute phase of recovery, concussed individuals consume a similar amount of metabolic energy for walking as healthy young adults across a wide range of walking speeds. Moreover, concussed individuals walk with similar gait mechanics as healthy adults at these speeds. My hypothesis was based on previous studies suggesting that walking mechanics change

21 significantly following a concussion. However, in these previous studies, the concussed were tested at a self-selected pace. In these prior studies, the preferred walking speed was always shown to be slower in concussed subjects as compared to healthy adults (R. Catena, et al., 2007; D. Howell, Osternig, Van Donkelaar, Mayr, & Chou, 2013; D. R. Howell, Osternig, & Chou, 2013). In contrast, my study was designed to test differences in walking energetics and mechanics as a result of concussion at the same speed. My reasoning for testing subjects at the same speed is that many of the difference in walking mechanics observed as a result of concussion mimic the differences typically associated with difference in speed. Moreover to date, there have not been studies examining the differences, in the metabolic cost of transport due to concussion at the same speeds. There are several determinants of the metabolic cost of transport. In walking, the cost of performing external mechanical work is a key determinant of walking energetics and is believed to account for as much as 50% of the total metabolic cost of transport (J. M. Donelan, Kram, & Kuo, 2001a). In my study, concussed subjects performed a similar amount of external mechanical work as healthy controls at each of the speeds tested. Thus, concussed adults likely have a similar metabolic cost of walking as healthy adults as a result of performing a similar amount of mechanical work at the speeds tested. The cost of maintaining balance is another key determinant of the metabolic cost of walking. In healthy adults, maintaining balance accounts for about 10% of the overall metabolic cost of waking. Maintaining balance is dependent on keeping the CoM within the base of support, and is oftentimes referred to as postural control. Once the CoM travels outside of the bases of support, it has left the feasible stability region and muscle effort must be applied to return balance (Pai & Patton, 1997). Changes in postural

22 stability during walking are often quantified using step width and step width variability (Standard deviation). Prior studies have shown that at preferred walking speed, postural stability is impaired in concussed individuals. In the present study, concussed individuals used similar step width and step width variability as healthy controls. Previous literature has found that most individuals who receive a concussion have static balance restored within 72 hours of impact (Kevin M. Guskiewicz, 2001). In the present study, only five of the subjects were tested within 72 hours of injury. The remaining 5 individuals were tested within seven days of their injury, with the average day of testing being day 5. Thus the lack of a measurable difference in step width may be related to the time frame in which the subjects were tested. However, it should be noted that these results are similar to those of some other prior studies that have shown that only 30% of those who receive a concussion actually report changes in balance (Murray, et al., 2014). Of the ten individuals included in this sample, not all of them may have manifested their concussive symptoms in the balance domain. Thus, another reason I did not see an increase cost of walking in concussed individual may also be related to the fact that they did not exhibit any significant signs of postural instability during walking. The cost of supporting body weight and the cost of leg swing both contribute to the metabolic cost of walking. Although the cost of supporting body weight and the cost of leg swing are believed to constitute significant portion of the total cost of walking, there is no evidence in the literature that would suggest that either of these factors are different in concussed individuals. This is further supported by the results of the present study that showed no difference in stance time or swing time; two factors that greatly influence the cost of supporting body weight and cost of leg swing, respectively.

23 The amount of external work performed on a system exacts a proportional metabolic cost (Kuo, et al., 2005) and this metabolic cost is minimized at intermittent speeds (J. M. Donelan, et al., 2001b). Moreover, there is a U-curve relationship between speed, the metabolic cost of transport, and external work. In agreeing with (J. M. Donelan, et al., 2001a), the metabolic cost for both groups was minimized at the intermittent speed of 1.25m s -1. The concussed and the healthy consumed metabolic energy at similar metabolic rates. The results of this study were not supportive of our second prediction, which stated that the difference in rate of metabolic energy consumption between concussed and healthy subjects would be proportional to the difference in mechanical work performed. At the very slow speed of.75m s -1 and fastest speed of 1.50 m s -1, the concussed consumed metabolic energy at a similar rate and a used similar amount of external work as health adults. However, at 1.25m s -1, concussed consumed similar amounts of metabolic energy, but performed 24% more external work than the healthy controls. The results indicate that there was not a consistent relationship between external work rates, metabolic cost, and speed in the concussed. This lack of consistent relations between metabolic cost and work may be related to the fact that less than half of the concussed subjects were tested within the first 72 hours following their injury when concussion related difference in gait mostly seen. Future research should investigate if changes to walking metabolics are present in a population exclusive to the first 24-72 hours after receiving a concussion. In regards to neurocognitive data, researchers chose a one-way MANOVA to evaluate the effect of status on the composite domains that constituted the ImPACT test

24 based on previous research. There were several limitations to this study. First, this study was limited to a relatively small sample size. The numbers of participants in each group was not balanced, nor were the genders balanced. Previous research has found that females may respond to symptom manifestation differently than males. Future researchers may want to test these sexes separately during their physiological rehabilitation process. Secondly, this study was limited to including individuals who received a concussion up to seven days after the injury occurred. This was done to aide in subject recruitment. Future studies should test for significant changes in balance in the first 24-72 hours of concussion, 14 days post-concussion, and 28 days post-concussion in attempts to evaluate the acute and relatively long-time changes that occur due to concussion. Third, this study did not control for lifelong history of concussion. Overall, the results of this study will help victims, medical professionals, and sports organizations have a better understanding of another way this subtype of brain injury effects all members of the community. The results of this study added to the research community in several ways including our understandings of 1) how concussion affects gait mechanics across a range of walking speeds and 2) how concussion affects walking energetics. The research, medical, and sport-for-profit communities are striving to understand how to best manage the wide range of symptoms that define what is known as a concussion today. Although this study found no significant differences in metabolic cost at the speeds of.75m s -1, 1.25m s -1, and 1.50m s -1, the concussed experienced altered kinematics that affect how they interpreted and responded to their environment.

25 Table 1. Subject characteristics (Mean ±SEM) with statistics for concussed and healthy walkers. Asterisk indicates the only significant group difference (p<.05). Healthy(n=14; 9M, 5 F) Concussed (n=10; 5M, 5 F) Age, years 22.0 ± 2.7 21.4 ± 3.1 Height, m 1.7 ±.1 1.7 ±.1 Body mass, kg 76.1 ± 17.2 76.6 ± 9.8 Days Tested Since Concussion Standing metabolic rate, W/kg 1.3 ± 0.2 3.7 ±.6* 1.3 ± 0.1 0.75 m s -1, gross metabolic power, W kg -1 3.0 ± 0.4 3.0 ±.3* 1.25 m s-1, gross metabolic power, W kg -1 3.8 ± 0.4 3.9 ± 0.3* 1.50 m s-1, gross metabolic power, W kg -1 4.6 ± 0.4 4.6 ± 0.2*

26 Table 2. Spatio-temporal strides variables (Mean ± SEM) with statistics for concussed and healthy subjects. Asterisk indicates significant group difference (p<.05). Speed 0.75 m s -1 Healthy (n=14) Concussed (n=10) Stance Time, % of stride 66.9 ±.5 66.8 ±.7 Swing Time, % of stride 33.2 ±.5 33.2 ±.7 Stride Frequency, Hz 0.7 ± 0.0 0.8 ± 0.0 Stride Length, Leg Length 1.0 ± 0.0 1.0 ± 0.0 Stride Width, meters.1 ±.0.1 ±.0 Speed 1.25 m s -1 Stance Time, % of stride 63.7 ± 17.0 64.2 ±.8 Swing Time, % of stride 36.3 ± 9.8 35.8 ±.8 Stride Frequency, Hz 0.9 ± 0.3 0.9 ± 0.0 Stride Length, Leg Length 1.4 ± 0.3 1.3 ± 0.0 Stride Width, meters.1 ±.0.1 ±.0 Speed 1.50 m s -1 Stance Time, % of stride 62.7 ± 16.7 66.7 ±.7 Swing Time, % of stride 37.3 ± 10.0.2 ±.7 Stride Frequency, Hz 1.0 ± 0.3 1.0 ± 0.0 Stride Length, Leg Length 1.5 ± 0.4 1.5 ± 0.0 Stride Width, meters.1 ±.0.1 ±.0

27 Table 3. Inverted Pendulum Mechanics variables (Mean ± SEM) with statistics for concussed and healthy subjects. Asterisk indicates significant group difference (p<.05). Speed 0.75 m s -1 Healthy (n=14) Concussed (n=10) Delta KE, J 1.9 ± 0.2 1.8 ± 0.4 Delta PE, J 5.7 ± 0.5 6.3 ± 0.9 Pendulum Recovery, % J 66.9 ± 3.1 68.9 ± 3.0 External Work, J/kg 2.6 ± 0.4 2.6 ± 0.5 Phase Angle 275 ± 3.0 284 ± 4.0 Speed 1.25 m s -1 Delta KE, J 5.8 ± 1.6 3.9 ± 0.6* Delta PE, J 15.4 ± 2.3 17.4 ± 2.1 Pendulum Recovery, % J 64.1 ± 19.7 52.5 ± 3.8 External Work, J/kg 8.3 ± 1.1 10.5 ± 1.6 Speed 1.50 m s -1 Phase Angle 265 ± 67 260 ± 4.0 Delta KE, J 7.4 ± 1.9 4.6 ± 0.7* Delta PE, J 20.7 ± 3.1 20.4 ± 3.0 Pendulum Recovery, % J 54.2 ± 17.6 49.5 ± 3.4 External Work, J kg -1 13.3 ± 1.7 13.4 ± 2.7 Phase Angle 266 ± 66 258 ± 5

28 Table 4. Results for Neurocognitive Performance Composite Scores and Symptom Score (Mean ± SEM) via ImPACT. Asterisk indicates the only significant group difference (p<.05). Healthy (n=14; 9M, 5F) Concussed (n=10; 5M, 5F) Verbal Memory 93.1 ± 2.20 75.0 ± 4.2* Visual Memory 77.1 ± 3.0 75.0 ± 3.8 Visual Motor 44.4 ± 6.3 35.6 ± 2.3* Reaction Time 0.5 ± 0.1 0.7 ± 0.1 Impulse Control 6.3 ± 1.2 4.0 ± 1.3 Symptom Score 1.9 ± 1.0 32.9 ± 8.1*

29 Figure 1. Mean (SE) gross metabolic cost of transport as a function of speed in healthy walkers ( ) and concussed walkers ( ). Asterisks (*) indicate significant differences between healthy walkers and concussed walkers (P<.05).

30 Figure 2. Mean (SE) gross inverted pendulum energy recovery as a function of walking speed in healthy walkers ( ) and concussed walkers ( ). Symbols shown on vertical axis represent standing metabolic rate of both groups. Asterisks (*) indicate significant differences between healthy and concussed walkers (P<.05).

31 Figure 3. Mean (SE) gross metabolic external work as a function of speed in healthy walkers ( ) and concussed walkers ( ). Asterisks (*) indicate significant differences between healthy walkers and concussed walkers (P<.05).

32 Figure 4. Mean (SE) gross metabolic power as a function of speed in healthy walkers ( ) and concussed walkers ( ). Asterisks (*) indicate significant differences between healthy walkers and concussed walkers (P<.05).

33 References Baldwin, S. A., Fugaccia, I., Brown, D. R., Brown, L. V., & Scheff, S. W. (1996). Bloodbrain barrier breach following cortical contusion in the rat. Journal of Neurosurgury, 85(3), 476-481. doi: 10.3171/jns.1996.85.3.0476 Barkhoudarian, G., Hovda, D. A., & Giza, C. C. (2011). The molecular pathophysiology of concussive brain injury. Clinical Sports Medicine, 30(1), 33-48, vii-iii. doi: 10.1016/j.csm.2010.09.001S0278-5919(10)00075-X [pii] Bell, D. R., Guskiewicz, K. M., Clark, M. A., & Padua, D. A. (2011). Systematic Review of the Balance Error Scoring System. Sports Health: A Multidisciplinary Approach, 3(3), 287-295. doi: 10.1177/1941738111403122 Brockway, J. M. (1987). Derivation of formulae used to calculate energy expenditure in man. Human Nutritional Clinical Nutrition, 41(6), 463-471. Catena, R., Donkelaar, P., & Chou, L.-S. (2007). Cognitive task effects on gait stability following concussion. Experimental Brain Research, 176(1), 23-31. doi: 10.1007/s00221-006-0596-2 Catena, R. D., van Donkelaar, P., & Chou, L. S. (2009). Different gait tasks distinguish immediate vs. long-term effects of concussion on balance control. Journal of Neuroengenering Rehabilitation, 6, 25. doi: 1743-0003-6-25 [pii]10.1186/1743-0003-6-25 Cavagna, G. A., & Franzetti, P. (1986). The determinants of the step frequency in walking in humans. Journal of Physiology, 373, 235-242. Cavagna, G. A., Willems, P. A., Legramandi, M. A., & Heglund, N. C. (2002). Pendular energy transduction within the step in human walking. Journal Experimental Biology, 205(Pt 21), 3413-3422. Chen, S. H. A., Kareken, D. A., Fastenau, P. S., Trexler, L. E., & Hutchins, G. D. (2003). A study of persistent post-concussion symptoms in mild head trauma using positron emission tomography. Journal of Neurology, Neurosurgery & Psychiatry, 74(3), 326-332. doi: 10.1136/jnnp.74.3.326 Chou, L.-S., Kaufman, K. R., Walker-Rabatin, A. E., Brey, R. H., & Basford, J. R. (2004). Dynamic instability during obstacle crossing following traumatic brain injury. Gait & Posture, 20(3), 245-254. doi: http://dx.doi.org/10.1016/j.gaitpost.2003.09.007 Donelan, J. M., Kram, R., & Kuo, A. D. (2001a). Mechanical and metabolic determinants of the preferred step width in human walking. Proceedings of the Royal Society of London [Biolological Sciences], 268(1480), 1985-1992.

Donelan, J. M., Kram, R., & Kuo, A. D. (2001b). Mechanical and metabolic determinants of the preferred step width in human walking. Proc Biol Sci, 268(1480), 1985-1992. doi: 10.1098/rspb.2001.1761 Donelan, J. M., Kram, R., & Kuo, A. D. (2002a). Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking. Journal Experimental Biology, 205(Pt 23), 3717-3727. Donelan, J. M., Kram, R., & Kuo, A. D. (2002b). Simultaneous positive and negative external mechanical work in human walking. Journal of Biomechanics, 35(1), 117-124. doi: S0021929001001695 [pii] Donelan, J. M., Shipman, D. W., Kram, R., & Kuo, A. D. A. D. (2004). Mechanical and metabolic requirements for active lateral stabilization in human walking. Journal of Biomechanics, 37(6), 827-835. Fait, P., McFadyen, B. J., Swaine, B., & Cantin, J. F. (2009). Alterations to locomotor navigation in a complex environment at 7 and 30 days following a concussion in an elite athlete. Brain Injury, 23(4), 362-369. doi: 909310678 [pii] 10.1080/02699050902788485 Gavett, B. E., Stern, R. A., Cantu, R. C., Nowinski, C. J., & McKee, A. C. (2010). Mild traumatic brain injury: a risk factor for neurodegeneration. Alzheimers Research Theapy, 2(3), 18. doi: 10.1186/alzrt42alzrt42 [pii] Geurts, A. C., Ribbers, G. M., Knoop, J. A., & van Limbeek, J. (1996). Identification of static and dynamic postural instability following traumatic brain injury. Archives of Physiology and Medicine Rehabilitation, 77(7), 639-644. doi: S0003-9993(96)90001-5 [pii] Giza, C. C., & Hovda, D. A. (2001). The Neurometabolic Cascade of Concussion. Journal of Athletic Training, 36(3), 228-235. Guskiewicz, K. M. (2001). Postural Stability Assessment Following Concussion: One Piece of the Puzzle. Clinical Journal of Sport Medicine, 11(3), 182-189. Guskiewicz, K. M. (2003). Assessment of postural stability following sport-related concussion. Current Sports Medicine Reports, 2(1), 24-30. Guskiewicz, K. M., McCrea, M., Marshall, S. W., Cantu, R. C., Randolph, C., Barr, W.,... Kelly, J. P. (2003). Cumulative effects associated with recurrent concussion in collegiate football players: the NCAA Concussion Study. Journal of the American Medical Association, 290(19), 2549-2555. doi: 10.1001/jama.290.19.2549290/19/2549 [pii] Howell, D., Osternig, L., Van Donkelaar, P., Mayr, U., & Chou, L.-S. (2013). Effects of concussion on attention and executive function in adolescents. Medicine and Science in Sports and Exercise, 45(6), 1030-1037. Howell, D. R., Osternig, L. R., & Chou, L.-S. (2013). Dual-Task Effect on Gait Balance Control in Adolescents With Concussion. Archives of Physical Medicine and Rehabilitation, 94(8), 1513-1520. doi: http://dx.doi.org/10.1016/j.apmr.2013.04.015 Johnston, I. A. (1984). Muscles and movement: muscles, reflexes, and locomotion. Science, 226(4680), 1308. doi: 226/4680/1308 [pii]10.1126/science.226.4680.1308 34

Kuo, A. D., Donelan, J. M., & Ruina, A. (2005). Energetic Consequences of Walking Like an Inverted Pendulum: Step-to-Step Transitions. Exercise and Sport Sciences Reviews, 33(2), 88-97. Martini, D. N., Sabin, M. J., DePesa, S. A., Leal, E. W., Negrete, T. N., Sosnoff, J. J., & Broglio, S. P. (2011). The Chronic Effects of Concussion on Gait. Archives of Physical Medicine and Rehabilitation, 92(4), 585-589. doi: http://dx.doi.org/10.1016/j.apmr.2010.11.029 McCrory, P., Meeuwisse, W., Johnston, K., Dvorak, J., Aubry, M., Molloy, M., & Cantu, R. (2009). Consensus statement on concussion in sport - the Third International Conference on Concussion in Sport held in Zurich, November 2008. Physiology and Sports Medicine, 37(2), 141-159. doi: 10.3810/psm.2009.06.1721 McCrory, P., Meeuwisse, W. H., Aubry, M., Cantu, B., Dvořák, J., Echemendia, R. J.,... Turner, M. (2013). Consensus statement on concussion in sport: the 4th International Conference on Concussion in Sport held in Zurich, November 2012. British Journal of Sports Medicine, 47(5), 250-258. doi: 10.1136/bjsports-2013-092313 McKee, A. C., Cantu, R. C., Nowinski, C. J., Hedley-Whyte, E. T., Gavett, B. E., Budson, A. E.,... Stern, R. A. (2009). Chronic traumatic encephalopathy in athletes: progressive tauopathy after repetitive head injury. Journal of Neuropathology and Experimental Neurology, 68(7), 709-735. doi: 10.1097/NEN.0b013e3181a9d503 McKee, A. C., Gavett, B. E., Stern, R. A., Nowinski, C. J., Cantu, R. C., Kowall, N. W.,... Budson, A. E. (2010). TDP-43 proteinopathy and motor neuron disease in chronic traumatic encephalopathy. Journal of Neuropathology and Experimental Neurology, 69(9), 918-929. doi: 10.1097/NEN.0b013e3181ee7d85 Minetti, A. E., Capelli, C., Zamparo, P., di Prampero, P. E., & Saibene, F. (1995). Effects of stride frequency on mechanical power and energy expenditure of walking. Medicine Science Sports Exercise, 27(8), 1194-1202. Moser, R. S., Iverson, G. L., Echemendia, R. J., Lovell, M. R., Schatz, P., Webbe, F. M.,... Barth, J. T. (2007). Neuropsychological evaluation in the diagnosis and management of sports-related concussion. Archives of Clinical Neuropsychology, 22(8), 909-916. doi: http://dx.doi.org/10.1016/j.acn.2007.09.004 Murray, N. G., Ambati, V. N. P., Contreras, M. M., Salvatore, A. P., & Reed-Jones, R. J. (2014). Assessment of oculomotor control and balance post-concussion: A preliminary study for a novel approach to concussion management. Brain Injury, 28(4), 496-503. doi: doi:10.3109/02699052.2014.887144 Omalu, B. I., DeKosky, S. T., Hamilton, R. L., Minster, R. L., Kamboh, M. I., Shakir, A. M., & Wecht, C. H. (2006). Chronic traumatic encephalopathy in a national football league player: part II. Neurosurgery, 59(5), 1086-1092; discussion 1092-1083. doi: 10.1227/01.NEU.0000245601.69451.2700006123-200611000-00014 [pii] Omalu, B. I., DeKosky, S. T., Minster, R. L., Kamboh, M. I., Hamilton, R. L., & Wecht, C. H. (2005). Chronic traumatic encephalopathy in a National Football League player. Neurosurgery, 57(1), 128-134; discussion 128-134. Ortega, J. D., & Farley, C. T. (2007). Individual limb work does not explain the greater metabolic cost of walking in elderly adults (Vol. 102). 35