The Effect of Repetitive Headers on Acute Vestibular, Neural, Cognitive and Auditory Function in Football Players

The Effect of Repetitive Headers on Acute Vestibular, Neural, Cognitive and Auditory Function in Football Players

Jessica Andrew

September 5th,2023

The potential long-term consequences of repetitive sub-concussive head impacts, particularly from heading in football, have raised concerns about their association with neurodegenerative diseases in ex-professional football players. Recent research suggests that the accumulative nature of heading in football may lead to subtle brain changes, ultimately contributing to Chronic Traumatic Encephalopathy. This study aimed to investigate the immediate short-term effects of repeated headers in football on brain function. Seventeen football players completed a total of five high-force linear headers, one header every 2-minutes, imitating corner clearance headers, positioned 32 meters away from a ball launching machine. Four neurophysiological assessments were reported pre- and post-heading exercise: 1) vestibular evaluation for balance and sway changes, 2) neural assessment for resting brain activity changes, 3) cognitive tests measuring memory, attention and reaction time, 4) auditory assessment to assess any auditory processing changes. Paired-samples t-tests and Wilcoxon’s signed rank tests found no significant changes in pre-to-post heading exercise scores in any measurements. These findings warrant further investigation to determine whether the measures used were sensitive enough to detect subtle sub-concussive changes. Or, whether findings indicate a safe maximum number, specific to this type of header, has been established and this frequency does not pose any additional risks to footballers’ brain function. This study contributes to the ongoing research surrounding player safety in football and the immediate short-term effects of repetitive sub-concussive head impacts.

Repetitive Sub-concussion, Football Heading, Neurocognitive Performance

Method
Participants
A power analysis for Analysis of Variance was conducted to determine the sample size needed for this study with an 80% power level, which identified a minimum of 40 participants to achieve a medium effect size of f=0.25, α=.001. This study did not collect a full sample and therefore is underpowered, as there are only a total of 17 participants (mean age=20.35). Participants were either academy players from Burnley Football Club or Lancaster University’s football team and were required to be male aged between 18 and 30- years with no history of concussion within the last month. This ensured variability between participants was minimal and excluding individuals with a recent history of concussion will mitigate potential confounding effects and isolate acute sub-concussive effects of heading, meaning this study will better attribute any observed effects to the specific act of heading rather than to prior injuries. Prior to volunteering, participants gave full consent and completed a modified version of the Physical Activity Readiness Questionnaire (PAR-Q), which is designed to measure participants readiness to participate in exercise or physical activity. See Appendix A for questionnaire. The purpose of the PAR-Q was to identify any potential underlying health concerns that may become an issue when participating. Additionally, participants completed a demographic questionnaire which was used to collect information about characteristics of the sample and highlighted whether participants had recently been concussed. See Appendix B for questionnaire. If any health concerns emerged during the completion of either questionnaire, participants were unable to continue with participation.
Materials
Participants were tested using a test battery comprised from four elements detailed below.
PROTXX.
Vestibular sway was measured using a wearable inertial measurement unit (IMU), called PROTXX. IMU is an electronic device designed to measures and report an individual’s orientation, velocity and gravitational forces (Powell et al., 2022). The IMU includes an accelerometer with three axis, X, Y and Z. The X-axis measures front-back acceleration, Y- axis measures vertical acceleration, and Z-axis measures left-right acceleration. For each of the three axes (x, y and z), during each 60 second test, data is recorded at a sampling rate of 100Hz and generates a total of 12,000 samples. Samples are filtered, meaning PROTXX eliminates gravitational bias and drift by using a high pass filter with a .04Hz cut-off frequency. An overall average is taken for each axis to compute one score for each of the four measures, 1) eyes open, 2) eyes closed 3) a ratio of the first two scores and 4) average power. It is also thought that the average power, calculated by adding the eyes closed and eyes open scores together, and divided by 2, can support a more objective way to clinically diagnose concussion, rather than the single tests alone (Ralston et al., 2020).
EEG Acquisition and Pre-Processing
Neural function was measured using EEG, Enobio 8 5G wireless device (Neuroelectrics, Cambridge, MA, USA). Participants wore a Neoprene headband to collect data from the frontal part of the head only, as this is where participants will later be instructed to header the ball. The Neoprene headband offers predefined positions for seven channels (F7, AF8. Fp1, Fpz, Fp2, AF8. F8) used to record EEG data and is based on the 10-10 international system (Jurcak et al., 2007). Figure 1 is a schematic of electrode location sites on the forehead. Participants wore an ear clip on their right ear with reference DRL/CMS electrodes. EEG data was initially visualised at a sampling rate of 500Hz and the line noise filter at 50Hz. Sticktrode pre-gelled self-adhesive electrodes were used and placed under the gaps of the Neoprene headband.The Necbox, is the core of the Enobio system, and is wirelessly connected to a laptop using NIC software (Neuroelectrics, Barcelona, Spain). Before any analysis, recorded EEG signals were coded and pre-processed in EEGLAB, a MATLAB toolbox (See Appendix C for EEGLAB Script) (Mathworks, Natick, MA, USA) (Delorme & Makeig, 2004). This is to ensure that data is in a suitable format and quality for analysis is reliable. Signals were downsampled to 256Hz, re-referenced to the average of all channels, and two types of filtering were applied to EEG data, high-pass (0.1Hz) and low-pass (40Hz) filtering. Independent Component Analysis was then applied to the pre-processed EEG data using a threshold of 0.8. This step was added to identify and remove any eye blinks, heart and muscle artifacts with 80% certainty (Chang et al., 2020). Components that have a score between 0.8 and 1 for artifacts are flagged for potential rejection and removed from EEG data.
Neural activity pre-and post-heading exercise were analysed using power spectral density analysis (PSD). PSD analysis is a method used to analyse frequency components present in a signal. To conduct a PSD analysis, this study used the code spectopo() function within EEGLAB. The average power of EEG frequency bands was calculated for each of the seven electrodes used in this study. The frequency bands were separated in the following way: theta (4-8Hz), alpha (8-12Hz), beta (12-30Hz) and gamma (30-40Hz) (Harris & Myers, 2023; Munia et al., 2017).
ImPACT Quick Test
ImPACT Quick Test measures different areas of cognitive function using five subtests that contribute to three overall composite scores used within this study’s analysis: Motor Speed, Memory, and Attention Tracker. The five subtests used to measure the participants cognitive abilities are:
1. Symbol Match – Reaction Time Subtest. The first subtest was a symbol match test which measured reaction time. Participants had to match a series of shapes with a specific number and the average time taken to complete all trials was recorded. (Figure 2a)
2. Symbol Match – Memory Subtest. This symbol match test also measured memory and asked participants to recall the number-symbol pairs and remember which symbol was matched up with which number. The resulting score is the percentage of correctly recalled number-symbol pairs across the trials. (Figure 2b)
3. Three Letter Memory – Speed Subtest. The participant is initially given three consonants. Participants are then given a computer-randomised 5x5 number grid and asked to count backwards from 25. The result is how long it takes the participant to count backwards from 25 to 1. This subtest provides a measure of speed, but also serves as an interference task for the next subtest. (Figure 2c)
4. Three Letter Memory – Memory Subtest. This subtest measures the participants memory and recall. It provided a measure of memory and tested how well the participants could recall the three consonants after completing the computer-randomised 5x5 number grid interference task. (Figure 2d)
5. Attention Tracker – Reaction Time and Attention Subtest. This subtest is comprised of three separate tasks and involves a circle that moves in the shape of a square, figure 8 and a sporadic/random pattern across the screen. The participant is asked to tap the circle when it changes from red to green at various points during its movement. This subtest provides results for reaction time and how fast the participant can react to the colour change and how well the participant can keep their attention sustained on the moving circle. (Figure 2e)
Digits in Noise Test (DiN)
The final testing measure used within this study was an online DiN test to measure participant’s auditory function. The DiN task is written in Javascript and hosted as a web- application on a Google Cloud Platform. Participants remained seated for this measure and listened to a British female voice who said three digits in a random order that are embedded into speech-shaped background noise (Smits et al., 2004). Stimuli was presented diotically in a quiet environment through supplied wired overhead SteelSeries 5Hv2 headphones. Signal- to-noise ratio (SNR) is a measure used to quantify strength of a desired signal relative to background noise level. A flexible approach called an adaptive 1-up, 1-down psychophysical method was employed. When a participant recalled the three digits correctly, SNR decreased, and when participants recalled the digits incorrectly, SNR increased. The DiN test began with a SNR of 0dB. As the test progressed, the changes in difficulty, known as step sizes, decreased from 5 to 2 dB after 3 reversals. Then after 3 more reversals, step sizes reduced even more to 0.5dB. A reversal refers to a change in direction, therefore the difficulty level is adjusted in the opposite direction. The test concluded after a total of 10 reversals and the final five SNR were recorded and an average was created, to calculate the participant’s speech in noise threshold. This threshold represents the level of background noise at which participants correctly identify the digits spoken to them. Football Heading
Within this study, participants received headers by a ball launching machine (Ball Launcher Pro Trainer, Ball Launcher). Participants completed five high-force linear headers at 35 yards from the ball launching machine at a ball speed of 50mph, the speed of the ball is regarded as below the average corner kick for collegiate-level players, which helps reduce the likelihood of injury and discomfort to players (Elbin et al., 2015; Tierney et al., 2021). This exercise is designed to mimic heading during football matches, specifically a clearance header from a corner (Figure 3). This ball launcher allowed for each of the headers to be consistent when measuring the effects of heading in football. The football used in this study was size 5, inflated to the FA standards of 8.6-15.6 PSI (The Football Association, 2023).
Procedure
A chronological schematic representation of the experimental procedure has been provided below (Figure 4).
Players at Burnley Football Club were contacted via their club’s representative and Lancaster University players were emailed directly. Upon arrival, participants were informed that the study will take around one hour to complete and asked to read the participant information sheet to ensure they fully understood the requirements before completing the consent, PAR-Q and demographic form. Participants height and weight was taken on the day, meaning that the demographic questionnaire will be filled in accurately. These forms were screened by the researcher(s) to ensure eligibility. Once completed, participants were first tested using PROTXX sensor. Participants were asked whether they experience any skin irritation or sensitivities due to prolonged adhesive contact, for example when using plasters. If there were no known adhesive-related reactions, PROTXX sensor was attached to the right mastoid using a disposable medical adhesive patch (figure 5). However, if participants did have adhesive-related reactions, PROTXX sensor was placed into a headband, and positioned in the same location (figure 6).
Participants were instructed to stand still, in an upright relaxed position with feet hips width apart and arms by their side whilst maintaining a straight, fixed gaze, three meters away from a specific target. Participants were instructed not to talk, chew gum, turn their head, fidget or move while the test is in progress. A smartphone app (protxxclinic; Version 1.0 build 13), connects to PROTXX via Bluetooth to run the tests and collect data. Participants completed two 60 second trials; eyes open and eyes closed. The app is used to start the test and participants are made aware of an audible countdown. One researcher stood by the participant to ensure no apprehension of falling during the eyes closed trial. The app sounded a tone signifying the test was 10-seconds away from finishing. Participants were instructed not to move until tests are completed and researchers had informed them, they can relax. If any anomalous participant movement was observed during the testing, said test data was excluded from analysis.
The second testing measure completed was EEG. Participants were seated for this measure and prior to setting up EEG, they were asked to wipe their foreheads with an alcohol wipe to reduce the impedance. Participants wore a Neoprene headband across their forehead with seven pre-gelled adhesive electrodes placed on bare skin located at each channel site and the reference channels were linked to their right ear (figure 7).
Electrode placement was completed, then connected via Bluetooth to a desktop app. The researcher(s) instructed participants to blink rapidly several times to create distinct electrical patterns on EEG recordings. This procedure is known as artifact-inducing task and is used to verify the quality of EEG readings (Grosselin et al., 2019). Participants were asked to sit in a comfortable position with eyes closed and 5-minutes of resting state EEG activity was recorded. A quiet environment was used, with minimal foot traffic, to reduce background noise and lessened potential of any auditory artifacts.
The third testing measure completed was ImPACT Quick Test. Participants remained seated for this measure and completed the assessment tool on an iPad in a quiet environment to remove distractions. The iPad was placed on a table in front of the participant who was instructed not to hold the iPad in their hands (Figure 8). The test was taken in one sitting and took participants between 5-7 minutes to complete.
The final testing measure participants completed was DiN. This measure required participants to remain seated in the quiet environment and wear provided overhead- headphones, that were plugged into the iPad (Figure 9). Before the test began, some music played through the headphones and participants were asked to find a volume level that was comfortable for them and were instructed to not change once selected. Participants were informed that this measure will vary in difficulty, and to guess the digits if they were unable to identify them. There was an opportunity to have a practice trial at this measure, so participants were familiar with the task and response procedure before the measure began. Participants would input three digits that they heard or guessed on the iPad’s keypad displayed. Again, this test was to be completed in one sitting and took no more than 3- minutes to complete.
After all baseline assessments were complete, participants moved on to the heading exercise, which was conducted in an indoor open space. The primary objective of this exercise was to execute five consecutive linear high-force headers within a timeframe of 10- minutes, giving participants 2-minutes rest between each header. Before commencing the heading exercise, participants received a briefing to prepare them. They were informed about their designated position, situated 35 yards away from the ball launching machine, replicating the distance of a typical corner kick in real-game scenarios. The ball would be launched at a velocity of 50mph from a ball launching machine, ensuring consistency. To optimise their heading technique, participants were encouraged to aim for frontal contact and direct the ball back in a linear trajectory towards the ball launching machine and were allowed to take a single step and execute a jump into the header (to replicate real-life situations). Additionally, a secondary researcher positioned further back from the participant was responsible for retrieving any missed headers, thereby sparing participants unnecessary energy expenditure. To familiarise participants with the dynamics and to help maximise their performance during this heading task, participants were acclimatised to the ball’s trajectory, observing several ball launches from the side-line and standing in their designed position before initiating any heading attempts. This also ensured that participants were comfortable with the ball speed.
Participants immediately completed the test battery again to obtain their post-heading scores, which were compared to evaluate the effect of headers on various test battery components. To close the study, participants were given a debrief sheet, and given a further opportunity to ask questions or raise concerns.
Statistical Analysis
Data pre- and post-heading were evaluated using paired-samples t-tests. The specific data used to input into the analyses was the independent variable, the point at which participants completed the test battery, pre-post heading exercise. The dependent variables
consisted of data collected from the different measures: PROTXX; using individual eyes open and closed condition sway power scores, in addition to ratio and average power of these conditions, EEG; PSD for the four frequency bands, (alpha, beta, theta and gamma) were averaged across each seven electrodes for each participant, ImPACT; overall composite scores for each cognitive domain (motor speed, memory and attention) and DIN; SNR thresholds. The paired-samples t-test is specifically designed to compare the means or averages of two related groups. These analyses test for immediate short-term effects that may occur after RSHI. Data was tested for normality using Shapiro-Wilks’ test (Shapiro & Wilk, 1965). This step is crucial to verify whether the data meets parametric assumption of a normal distribution before proceeding with further analyses. Analyses were performed using statistical software R Studio. See Appendix D for R Studio Script.

Lancaster University

Excel.csv("Linear Heading Study Data.xlsx")
r_file.R("Dissertation_Masters.R")

Andrew2023

Niko Liu ,Anusha Sandeep, David Racovita

'Open'

N/A

English

Data

LA20PF

Dr Helen Nuttall

Masters

Neuropsychology

17 participants

T-Test
Other