Balance control during gait in athletes and non-athletes following concussion

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Medical Engineering & Physics 30 (2008) 959–967

Balance control during gait in athletes and non-athletes following concussion Tonya M. Parker 1 , Louis R. Osternig, Paul van Donkelaar, Li-Shan Chou ∗ Department of Human Physiology, 1240 University of Oregon, 122 Esslinger Hall, Eugene, OR 97403, USA Received 1 June 2007; received in revised form 14 November 2007; accepted 14 December 2007

Abstract Current literature provides only limited information regarding performance on dynamic motor tasks following concussion. However, recent investigations have suggested that participation in contact sports may have a negative effect on cognitive function without the existence of a medically diagnosed concussion. The purpose of this study was to examine balance control during gait in concussed and uninjured athletes and non-athletes. Twenty-eight Grade 2 concussed individuals (14 athletes and 14 non-athletes) and 28 uninjured matched controls (14 athletes and 14 non-athletes) were assessed for their gait performance within 48 h, 5, 14, and 28 days post-injury under conditions of divided and undivided attention. Athletes, whether concussed or not, walked slower and swayed more and faster than non-athletes. Athletes consistently demonstrated gait imbalance even in the absence of concussion. The findings of this study support the supposition that participation in high-impact sports has a measurable and possibly detrimental effect on balance control in the absence of a medically diagnosed concussion. © 2007 Elsevier Ltd. All rights reserved. Published by Elsevier Ltd. All rights reserved. Keywords: Concussion; Gait; Sub-concussion; Uninjured controls; Dual-task; Balance control

1. Introduction Current concussion research has largely focused on cognitive neuropsychological testing as a means to assess recovery following a concussion. It has been suggested that athletic participation, particularly in contact sports, may have an adverse effect on performance in tests of cognitive function [1–3]. Downs and Abwender [1] examined the frequency of “heading” in soccer for ball control and propulsion, and found that length of a soccer career and high levels of play were related to poorer cognitive test performance. A similar finding was revealed by Rutherford et al. [3] when soccer and rugby athletes were examined. Killam et al. [2] examined cognitive function among non-concussed, recently concussed, and non-recently concussed contact and non-contact athletes and compared them to non-athletes. Their results suggested that participation in contact sports may produce cognitive impairments without diagnosed concussion. ∗

Corresponding author. Tel.: +1 541 346 3391; fax: +1 541 346 2841. E-mail address: [email protected] (L.-S. Chou). 1 Current address: Department of Movement Science, Grand Valley State University, Allendale, MI 49401, USA.

While the use of neuropsychological evaluation has recently been advocated as the “cornerstone” of proper concussion management [4], all domains that may be impacted by brain injury are not assessed by this method. One such domain that has not frequently been investigated is postconcussion recovery of dynamic motor function. Previous work has examined recovery of static balance and revealed that participants with mild traumatic brain injury (MTBI) demonstrated impaired postural stability for 1–5 days following injury [4–7]. However, Guskiewicz et al. [6] reported no relationship between concussion symptoms, performance on tests of cognitive function, and static postural stability. Johnson et al. [8] assessed post-injury symptoms and psychomotor performance of concussed athletes (mild brain injury) and matched controls over 10 days post-injury. They found the concussed subjects to exhibit significantly greater symptom scores than controls 1 day after injury, but no group differences were observed for the time to complete a psychomotor agility task. Data from Parker et al. [9] suggested that postconcussion recovery of motor function might be independent of cognitive recovery and that a longer recovery time may be needed for the resolution of more complex tasks.

1350-4533/$ – see front matter © 2007 Elsevier Ltd. All rights reserved. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.medengphy.2007.12.006

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T.M. Parker et al. / Medical Engineering & Physics 30 (2008) 959–967

Table 1 Subject demographics; group mean ± standard deviation Group

Age (years)

Height (m)

Weight (kg)

Mean time from injury to testing (h)

CONC-A NORM-A

20.71 ± 1.33 20.64 ± 1.45 p = 0.528

1.86 ± .07 1.85 ± 0.07 p = 0.840

102.41 ± 23.12 100.74 ± 23.86 p = 0.850

33.21 ± 11.97

CONC-NA NORM-NA

22.43 ± 4.59 22.93 ± 4.27 p = 0.889

1.69 ± .08 1.68 ± 0.07 p = 0.543

68.93 ± 10.18 67.01 ± 9.34 p = 0.792

31.89 ± 12.14

Few data are available on the performance of dynamic motor tasks following concussion. Parker et al. [10,11] introduced a new method of assessing concussion and recovery that focused on gait as a dynamic functional motor task during conditions of divided and undivided attention. They found that gait imbalance increased when concussed subjects were asked to walk while simultaneously performing a secondary cognitive task compared to walking without mental distraction. Gait imbalance, in the divided attention condition, was marked by greater sway and sway velocity of the whole body center of mass (COM) that were maintained for up to 28 days following injury. Competitive sport activities present a venue in which head injuries are common [12]. Previous research on concussed athletes has shown that complex motor functions require a longer recovery period than cognitive tasks [10,11,13]. It has also been suggested that participation in contact sports may have a negative effect on cognitive function without the existence of a medically diagnosed concussion [3]. However, little data are available that compare concussed and non-concussed athletes and non-athletes on complex neuromotor tasks. Therefore, the primary purpose of this study was to examine gait performance as well as COM motion in concussed and uninjured athletes and non-athletes. It has been postulated that long-term participation in contact sports that expose athletes to repetitive, sub-concussive head trauma may compromise neuropsychological function [1–3,14]. This suggests that chronic, relatively low-impact, as well as, acute high-impact head traumas may result in neurological impairment. Therefore, a secondary purpose of this study was to investigate the extent to which high- and low-impact sports participants differ in the recovery of gait stability following concussion.

2. Materials and methods Fifty-six college-aged men and women served as subjects for this study. The subjects were categorized into four groups of equal number according to athletic and concussion status. The concussed groups consisted of NCAA Division I or University Club Sports athletes (CONC-A; n = 14) and non-athletes who engaged in no regular sports activities (CONC-NA; n = 14). The uninjured control groups consisted of NCAA Division I or University Club Sports athletes

(NORM-A; n = 14) and non-athletes who engaged in no regular sports activities (NORM-NA; n = 14). The control subjects were matched to concussed subjects by gender, age, height, weight, and physical activity (Table 1). All concussed subjects had sustained a Grade 2 concussion according to the American Academy of Neurology Practice Parameter [15]. Concussed participants were initially identified by medical personnel including certified athletic trainers and attending medical doctors in the university intercollegiate athletic program and the student health center, and were referred for testing as soon as possible following the injury. None of the NORM subjects self-reported a history of neurological diseases, visual impairment not correctable with lenses, musculoskeletal impairments, or persistent symptoms of vertigo, lightheadedness, unsteadiness, falling or a history of concussion within the last year. The experimental protocol was approved by the Institutional Review Board of the University. The experimental procedures were explained to all subjects prior to testing and verbal and written consents were obtained. All CONC subjects were tested within 48 h of injury (day 2) and again at 5, 14, and 28 days post-injury. The NORM participants were tested at the same time intervals. In order to avoid any shoe type differences, all subjects were tested while barefoot. The participants were instructed to walk along a 10m walkway at a comfortable self-selected walking speed. The gait protocol was the same for each testing day and consisted of level walking and was performed by each subject under two conditions: (1) with undivided attention (single-task) and (2) while simultaneously completing simple mental tasks (dualtask). These tasks consisted of spelling five-letter words in reverse, subtraction by sevens, and reciting the months of the year in reverse order. These tasks are frequently used in mental status examinations to assess attention and concentration [16]. Each type of dual-task was completed by every subject with the order of individual tasks rotated across trials. All dual-task walking trials were conducted in the same manner with verbal instructions given immediately prior to the command to begin walking. The subjects were not given instructions on which task (walking or mental) they were to focus their attention. Each testing session began with four to five trials of single-task walking followed by four to five trials of the dual-task condition. In order to assess gait variables, a set of 31 reflective markers were placed on bony landmarks of the participant (Fig. 1). A more detailed description of marker placement was

T.M. Parker et al. / Medical Engineering & Physics 30 (2008) 959–967

Fig. 1. Subject with marker set.

reported previously [11,17]. An eight-camera motion analysis system (Motion Analysis Corporation, Santa Rosa, CA) was used to capture and reconstruct the three-dimensional trajectory of the surface markers. The motion analysis system was calibrated before each session (volume = 4-m long, 1.5-m wide, 2-m high). Three-dimensional marker trajectory data were collected at 60 Hz and low-pass filtered using a fourth-order Butterworth filter with the cutoff frequency set at 8 Hz. Virtual marker positions were estimated using EVaRT software (Version 4.4, Motion Analysis Corp., Santa Rosa, CA) to represent internal segment endpoints from the external markers, and the relative positions of the segmental center of mass. External markers and estimated joint centers were used to calculate the three-dimensional motion for individual body segments and locations of segmental COM. Anthropometric reference data were adapted from Dempster [18] for both age groups and genders. Whole body COM position data were calculated as the weighted sum of each body segment, with 13 segments representing the whole body (head–neck, trunk, pelvis, upper and lower arms, upper and lower legs, feet). Velocities and accelerations of the COM were estimated

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using the generalized cross-validated spline algorithm [19]. In order to compute the center of pressure (COP), ground reaction forces were collected by two force plates (Advanced Mechanical Technology, Inc., Watertown, MA) positioned in series along the gait path and sampled at a frequency of 960 Hz. Variables were examined in one gait cycle, operationally defined as from heel strike on the force plate to the next heel strike of the same limb. Data were averaged across trials for each task condition (single and dual). Four variables were examined: the COM displacement and peak velocity in the medial–lateral direction (MLdisp; MLvel); the average gait velocity (GV), and the maximum separation between the COM and COP of the supporting foot in the anterior direction (ANTmax). The relationship between the whole body COM and the base of support has been shown to be a sensitive measure gait imbalance [10,11,20,21]. The effects of group (CONC-A, CONC-NA, NORM-A, and NORM-NA) and task (single vs. dual) were examined for these variables over the testing days (2, 5, 14, and 28). Repeated measures (4 × 2 × 4) mixed design analyses of variance (ANOVAs) with Bonferroni corrections for multiple comparisons were computed to determine whether differences (p < 0.05) existed for each dependent variable between groups and within task and day (SAS Institute Inc., Cary, NC). In order to evaluate the possibility that type of competitive sport participation may have produced measurable deficits in balance control during gait, the NORM and CONC athletes were categorized into two subgroups according to the analysis of Pellman et al. [22,23]. These categories corresponded to their type of sport involvement and included “low-velocity impact” (LO-VEL) and “high-velocity impact” (HI-VEL) groups. The LO-VEL group comprised athletes that tended to experience chronic sub-concussive blows while the HIVEL group tended to experience acute higher velocity head trauma. These groups were assessed on COM displacement and peak velocity in the medial–lateral direction (MLdisp; MLvel). A repeated measures ANOVA (2 × 2) was computed to determine effects of group (HI-VEL vs. LO-VEL) and task (single vs. dual) for these variables across testing days.

3. Results The results revealed a significant interaction (p = 0.003) between task (single/dual) and testing day (2–28) for gait velocity. For all groups, the dual-task condition resulted in significantly slower GV compared to single-task on all days, and GV was significantly slower on day 2 than all other days for both tasks (Table 2). The gait velocity of athlete groups was slower than non-athlete groups in both task conditions for all testing days. During the single-task condition, the concussed and normal athletes walked significantly slower than the concussed (p = 0.032; p = 0.002) and normal non-athletes (p = 0.003; p < 0.001). With the addition of the dual-task, the

± ± ± ± 1.322 1.140 1.283 1.438

Single

0.121a 0.114a 0.152a 0.142a

Day 28

0.094 0.141 0.121 0.131

1.249 ± 0.131a 1.316 ± 0.137a 1.228 ± 0.127a 1.378 ± 0.168a

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Dual

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1.231 1.321 1.196 1.391

GV was slower for both athlete groups when compared to the normal non-athletes (p = 0.002; p = 0.001; Fig. 2). There was no effect of testing day on the medial–lateral COM displacement or peak velocity (p = 0.309; p = 0.827). However, the dual-task produced significantly greater sway than the single-task for all groups (p = 0.002; Tables 3 and 4). When the subject groups were analyzed, the athletes demonstrated a significantly greater MLdisp than the non-athletes in both task conditions (Fig. 3). Specifically during the singletask, the concussed athletes and non-concussed athletes had significantly greater sway than the concussed (p < 0.001; p < 0.001) and normal non-athletes (p = 0.004; p = 0.006). For the dual-task condition, the CONC-A group produced significantly more sway than either non-athlete group (CONC-NA, p = 0.002; NORM-NA, p = 0.001) while the NORM-A subjects showed a significantly greater sway than those in the CONC-NA group (p = 0.001). Similarly, the ML COM peak sway velocity was significantly greater in the dual-task compared to the single-task condition (p = 0.001; Table 4). MLvel was also found to have a group effect (p = 0.002), as both athlete groups had signif-

± ± ± ± 1.316 1.415 1.266 1.422

Single

0.135a 0.146a 0.148a 0.127a ± ± ± ± 1.218 1.282 1.189 1.356

Dual

0.107 0.118 0.150 0.108 ± ± ± ± 1.296 1.396 1.271 1.415

Single Single

a

b

Single > dual. Day 2 < days 5, 14, and 28.

1.101 1.321 1.196 1.391 CONC-A CONC-NA NORM-A NORM-NA

1.227 1.270 1.217 1.381

± ± ± ±

0.150 1.127 0.134 0.107

Dual

± ± ± ±

0.174a,b 0.114a,b 0.152a,b 0.142a,b

Day 5 Day 2 Group

Table 2 Mean ± standard deviation for COM gait velocity (m/s) for groups in single- and dual-task conditions for each day

Day 14

0.091 0.119 0.140 0.113

Dual

± ± ± ±

Fig. 2. Group means and standard errors for COM gait velocity in singleand dual-task conditions averaged across testing days. *Significantly greater than CONC-A and NORM-A.

Fig. 3. Group means and standard errors for medial–lateral COM displacement in single- and dual-task conditions averaged across testing days. **Significantly greater than CONC-NA and NORM-NA; ‡ Significantly greater than CONC-NA.

Table 3 Mean ± standard deviation for COM medial–lateral displacement (m) for groups in single- and dual-task conditions for each day Group

Day 2

Day 5

Single

a

0.044 0.033 0.041 0.034

± ± ± ±

0.014 0.007 0.007 0.007

0.044 0.042 0.043 0.040

Single ± ± ± ±

0.011 0.014a 0.008a 0.010a

0.042 0.031 0.041 0.036

Dual ± ± ± ±

0.010 0.008 0.008 0.009

0.046 0.033 0.044 0.035

Day 28

Single ± ± ± ±

0.011 0.009 0.011 0.010

0.041 0.032 0.041 0.033

Dual ± ± ± ±

0.008 0.007 0.011 0.010

0.048 0.034 0.043 0.040

Single ± ± 0.010a ± 0.008a ± 0.012a 0.011a

0.039 0.032 0.041 0.035

Dual ± ± ± ±

0.008 0.006 0.012 0.008

0.046 0.037 0.040 0.039

± ± ± ±

0.009a 0.011a 0.011a 0.014a

± ± ± ±

0.033a 0.026a 0.035a 0.043a

Single < dual.

Table 4 Mean ± standard deviation for COM medial–lateral velocity (m/s) for groups in single- and dual-task conditions for each day Group

Day 2

Day 5

Single CONC-A CONC-NA NORM-A NORM-NA a

0.146 0.123 0.146 0.122

Dual ± ± ± ±

0.044 0.026 0.030 0.014

0.146 0.134 0.157 0.142

Day 14

Single ± ± ± ±

0.037 0.030a 0.025a 0.032a

0.150 0.116 0.148 0.135

Dual ± ± ± ±

0.039 0.028 0.032 0.035

0.168 0.124 0.163 0.139

Day 28

Single ± ± ± ±

0.034a 0.032a 0.029a 0.035a

0.147 0.123 0.144 0.130

Dual ± ± ± ±

0.031 0.024 0.034 0.026

0.160 0.130 0.154 0.139

Single ± ± ± ±

0.029a 0.028a 0.031a 0.035a

0.145 0.123 0.148 0.133

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CONC-A CONC-NA NORM-A NORM-NA

Dual

Day 14

Dual ± ± ± ±

0.034 0.022 0.036 0.029

0.162 0.133 0.154 0.141

Single < dual.

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0.231 0.239 0.230 0.253 ± ± ± ± 0.239 0.252 0.240 0.259 0.239 0.246 0.230 0.245

c

a

b

Single > dual. Day 2 < days 5, 14, and 28. Day 5 < day 28.

0.202 0.205 0.208 0.226 0.217 0.215 0.217 0.239

± ± ± ±

0.041 0.039 0.030 0.033

Dual

± ± 0.038a,b ± 0.028a,b ± 0.036a,b

Single Single

± ± ± ±

0.033 0.036 0.035 0.035

0.221 0.228 0.213 0.241

± ± 0.039a,c ± 0.038a,c ± 0.034a,c

0.237 0.249 0.230 0.255

± ± ± ±

0.021 0.029 0.027 0.031

0.222 0.235 0.221 0.252

± ± 0.029a ± 0.036a ± 0.040a

Single Dual Single Dual

0.041a,c

Day 14 Day 5 Day 2

0.053a,b

CONC-A CONC-NA NORM-A NORM-NA

Fig. 5. Group means and standard error for anterior separation distance of the COM and COP for single- and dual-task conditions averaged across testing days. *Significantly greater than CONC-A and NORM-A.

Group

icantly faster sway velocity than the concussed non-athlete group during both task conditions (Fig. 4). The anterior separation distance between the COM and COP was found to have task (p = 0.001), day (p < .001), and group (p = 0.026) main effects. For these comparisons, the dual-task produced significantly smaller ANTmax than the single-task for the first three testing sessions (Table 5). Within all groups, the subjects had significantly less separation on day 2 compared to all other testing days for both the single and dual tasks. The non-athletes were found to have a greater separation COM–COP distance compared to the athlete groups for both task conditions (single: p = 0.036; dual: p = 0.028; Fig. 5). Analyses of the low-velocity and high-velocity athletes on the medial–lateral variables revealed a significant difference between the groups (p = 0.025; Fig. 6) with the LO-VEL athletes showing greater sway than those in the HI-VEL group.

Table 5 Mean ± standard deviation for anterior separation distance between the COM and COP (m) for groups in single- and dual-task conditions for each day

Fig. 4. Group means and standard errors for medial–lateral COM velocity in single- and dual-task conditions averaged across testing days. **Significantly greater than CONC-NA.

0.032a

Day 28

0.023 0.040 0.032 0.031

Dual

± ± ± ±

0.036 0.037 0.036 0.043

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Fig. 6. Group means and standard errors for the LO-VEL and HI-VEL groups for medial–lateral COM displacement for single- and dual-task conditions averaged across testing days. † Significantly greater than HI-VEL.

4. Discussion For the sagittal plane variables, the athletes displayed a slower gait velocity and shorter separation distance between the COM and COP than the non-athletes. In prior studies [20,21], patients with traumatic brain injury with lasting complaints of gait imbalance were found to walk with a significantly reduced anterior COM velocity and displacement. A similar pattern of decreased gait velocity, increased sway, and sway velocity was found in concussed individuals, and these differences were have been shown to be distinguishable from 2 to 28 days post-injury, especially in the presence of a secondary mental task [10,11]. The previous findings taken together with the current results suggest that individuals with concussion or contact sports athletes may maintain their balance through reduced sagittal plane movement in an effort to control for increased coronal plane sway. Few data are available on the post-concussion recovery of complex motor tasks in an athletic population although athlete performance on cognitive neuropsychological tests following concussion has been investigated. In the present study, both the frontal plane (MLdisp; MLvel) and sagittal plane (GV; ANTmax) data tended to cluster according to athlete or non-athlete group (Figs. 2–5). The athletes whether concussed or not, displayed significantly greater sway excursion and faster sway velocity than the nonathletes. In contrast, the athletes walked significantly slower than the non-athletes and allowed less center of mass to center of pressure separation before the next step. These differences were more pronounced during the dual-task compared to the single-task condition and were evident from 2 to 28 days (Tables 2–5). It is possible that the dual-task condition interfered with sensory feedback necessary to control lateral sway. Donelan et al. [24] studied treadmill gait of humans fitted with and without an external lateral stabilization device and observed reductions in foot placement variability with external stabilization. They suggested that

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walking is passively unstable in the lateral direction and requires active feedback control. Bauby and Kuo [25] compared lateral and fore-aft foot placement variability during gait of normal subjects under eyes-open and eyes-closed conditions. They found significantly greater lateral than fore-aft foot placement variability during gait that was exacerbated when the eyes were closed. It was suggested that lateral balance is sensitive to intrinsic perturbations and must be stabilized with visual-vestibular feedback and significant active control. Previous studies have shown that task complexity and task assessment technique may influence the interpretation of concussion effects on athletes. Using a virtual field reality environment, Slobounov et al. [26] studied the effect visual field motion on COP in eight athletes before and after suffering mild traumatic brain injuries. They reported that for standard balance tests the area of COP returned to pre-injury level within 10 days post-injury, while the more challenging visual field motion tasks induced postural dysfunction, which lasted up to 30 days post-injury. Cavanaugh et al. [27] compared equilibrium scores and approximate entropy (ApEn) values on COP data collected from athletes with and without initial postural instability after concussion. The ApEn score was used to detect subtle changes in COP oscillations. They reported that the effects of concussion on postural control, when measured in terms of ApEn, appeared to persist for longer than 3–4 days post-injury, even among athletes who demonstrated normal postural stability within 48 h of injury based on composite equilibrium scores. In studies of active soccer players it was found that the number of incidences of heading the ball in a season was related to poorer results on neuropsychological tests when compared to athletes who participated in non-contact sports [3,14]. It was documented that rugby participants performed better on a battery of neuropsychological tests than soccer players despite suffering a fivefold greater incidence of head injuries [3]. In a study comparing soccer players and swimmers, Downs and Abwender [1] determined that performance on neuropsychological tests was not correlated with previous histories of concussion. They suggested that years of participation and repeated sub-concussive head trauma may place individuals at risk for neuropsychological compromise. Killam et al. [2] examined non-concussed, recently concussed and non-recently concussed athletes against non-athlete/nonconcussed controls. It was found that recently concussed and non-concussed athletes performed poorer on tests of memory than non-athlete controls. While the number of participants in each group was relatively small, it was concluded that participation in contact sports produced sub-clinical cognitive impairments due to repeated, sub-concussive, head trauma. All athletes in the present study were involved in contact sports including football, rugby, and lacrosse. These sports have proven to have a high incidence of concussions [12]. It is possible that diagnosed concussions as well as repeated exposure to sub-concussive blows in the non-

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concussed and concussed athlete groups decreased the ability of these individuals to control their sway during gait. Subconcussive trauma has been implicated in the etiology of dementia pugilistica (DP), or “punch drunk” in boxers [28]. The hallmark of DP is a “Parkinsonian” pattern of progressive cognitive and physical decline [28]. It has been hypothesized that, over time, the brain may be vulnerable to repeated, cumulative mild sub-concussive effects without a specific brain injury severe enough to produce symptoms of concussion [2,29]. Recent research has examined the role of sub-concussive blows as a chronic phenomenon implicated in the documented decline in neuropsychological performance seen in soccer and football players [3,30]. The LO-VEL subgroup consisted of those athletes playing positions that are subject to repeated sub-concussive blows and included American football offensive and defensive linemen, and rugby players who participate in the scrum. In American football, the offensive and defensive linemen have a relatively lower risk of concussion than the HI-VEL players such as the quarterbacks and wide receivers [22,23]. The linemen and the rugby scrum players tend to move with slower velocities over shorter distances than HI-VEL athletes and therefore impact each other with lower acceleration. Because of this, LO-VEL players are less likely than HI-VEL players to experience impacts that produce medically diagnosed concussions. These athletes operate in close contact with their own teammates, as well as with opposing team athletes, and the number of these sub-concussive impacts for this group can be quite high. Therefore, in a similar pattern as boxers, the negative effects of many sub-concussive blows may be cumulative. The HI-VEL subgroup included athletes who were less likely to suffer repeated sub-concussive head trauma but more likely to suffer high-velocity head injuries in the open field. This group consisted of quarterbacks, wide receivers, tight ends, and the lacrosse players. The significant differences found in medial–lateral sway variables suggest that repeated sub-concussive blows due to certain types of athletic participation may produce a measurable consequence for controlling the whole body COM during gait. It is possible that athletes have a greater allowable sway and sway velocity as a result of the high level of physical conditioning and these differences may not affect their athletic performance. However, the data from this study and that of others [11] suggest that motor stability, particularly balance control when attention is divided, can be impaired for up to 1 month following what is sometimes considered to be a mild (Grade II) concussion. Hence, neuropsychological assessments alone may not be adequate to detect lingering insufficiencies in motor function that could influence sports performance and vulnerability to further injury. It is recommended that evaluation of concussion recovery include assessments of complex motor tasks which test the demands required of an athlete returning to play. It is also recommended that further study be carried out on the cumulative effects of sub-concussive head trauma occurring from sports participation.

Acknowledgements This study was supported by the Centers for Disease Control and Prevention (R49/CCR021735 and CCR023203), which did not have a role in the design, collection, analysis or publication of the data. The authors gratefully acknowledge the assistance of Robert Catena in data collection.

Conflict of interest None.

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