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Sport recovery system is an integral aspect to help athletes adapt faster to training. This is an important process of physical preparation by reducing fatigue where the athletes can ready for the next competition or training. However, most of an athlete doing training without having the fully recovery after the training and can affect their performance. The cold bath water immersion is the one of common technique to recover from the fatigue. In this study, Neurosky mindwave is use to extract the brain wave of an athlete to know the response of an athlete when perform the cold water immersion. The responses of an athlete include meditation which is in alpha wave that state in relax condition and beta wave that is in fatigue condition in sport. The raw brain wave signal that extract using Neurosky mindwave is analysed using Matlab in terms of time domain. After that, Fast Fourier Transform (FFT) will use to analysed in terms of frequency domain. This project used alpha and beta band to collect the data. The analysis have made based on the peak value in frequency domain to know the best time for cold water immersion and best cold bath temperature.
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International Journal of Engineering & Technology, 7 (4.30) (2018) 438-442
International Journal of Engineering & Technology
Website: www.sciencepubco.com/index.php/IJET
Research paper
Ice Bath Therapy on Athletes Recovery Response Using
EEG
Hakimi, M.H.1, Salleh, S.M.*1, Ainul, H.M.Y.1, Ngali, M.Z.1, Ismail, A.E.1, Rahman, M.N.A.1, Mahmud,
W.M.A.W 1
1*Mechanical Failure Prevention and Reliability (MPROVE), Department of Eng. Mechanics,
Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia
*Corresponding author E-mail:saliha@uthm.edu.my
Abstract
Sport recovery system is an integral aspect to help athletes adapt faster to training. This is an important process of physical preparation
by reducing fatigue where the athletes can ready for the next competition or training. However, most of an athlete doing training without
having the fully recovery after the training and can affect their performance. The cold bath water immersion is the one of common tech-
nique to recover from the fatigue. In this study, Neurosky mindwave is use to extract the brain wave of an athlete to know the response of
an athlete when perform the cold water immersion. The responses of an athlete include meditation which is in alpha wave that state in
relax condition and beta wave that is in fatigue condition in sport. The raw brain wave signal that extract using Neurosky mindwave is
analysed using Matlab in terms of time domain. After that, Fast Fourier Transform (FFT) will use to analysed in terms of frequency do-
main. This project used alpha and beta band to collect the data. The analysis have made based on the peak value in frequency domain to
know the best time for cold water immersion and best cold bath temperature.
Keywords: Brain Wave; Cold Ice Bath Theraphy; EEG; Fatigue; NeuroSky Mindwave,
1. Introduction
In sport, the athletes usually focusing into training and competi-
tion. The training that their focusing based on their schedule re-
duce the capacity in athletes performance. The regular training
based on the schedule can cause muscle damage and it is the im-
portant factor that limiting the performance of the athletes [1]. It
causes fatigue to an athlete and make them not able to perform
well in their competition and follow the regime of training sched-
ule.
Fatigue can be defined as a reduction capacity of the muscle re-
duction in the maximal force generating [2]. Physical fatigue can
cause the temporary inability of muscle to perform optimally. The
effect of fatigue on human are widely studied because of the sen-
sorimotor function may decreased the functional joint stability,
many muscle properties change during fatigue including the extra-
cellular and intracellular ions. Besides that, action potential and
many intracellular metabolites are affected. A range of mecha-
nisms have been identified that contribute to the decline perfor-
mance [3]. The performance of muscle is decrease when used in
near maximum capacity.
Combination of reduced force production, slowed relaxation and
decreased velocity of shortening will change the performance that
lead to extreme reductions in performance particularly for rapidly
repeated movements.The quality recovery is important to make
sure the athletes in good shape and can perform well in training
and competition. The quality recovery will indicate the good result
in terms of restoring the physiological of an athlete. It will recover
the fatigue, muscle damage and increase the performance for an
athlete that can make the athletes always in good shape for their
training
and competition [4]. Cold water immersion is the one of the re-
covery system for an athlete and it helps the recovery of the hu-
man body when react to water immersion. It will change in the
heart, blood flow and muscle function [5].
Fatigue detection is an on-going research topic among both psy-
chologists and engineers. Both of them are able sensors and bio
signal processing technologies to be developed for detecting the
human stress. There are few types of bio signal processing tech-
nologies use for human stress detection such as Electrocardiog-
raphy (ECG), Electromyography (EMG), Electroencephalo-
graphy (EEG), Blood Pressure (BP), Blood Volume Pulses (BVP)
and Galvanic Skin Resistance (GSR) [6].
The reaction of an athletes towards recovery process can be identi-
fied by using EEG. EEG has been long used to know the reaction
of human body based on the relationship among human and be-
haviour because of it delivers a direct real-time measure of neural
activity. EEG are inexpensive and easy to apply because is record-
ed using electrode places at specific locations such as frontal,
temporal, parietal and occipital in scalp [7].
Electroencephalography (EEG) signal is the most common of
nature signals. The signal exists in the brains of human beings and
animals. Table 1 shows the activities of EEG in for different sig-
nal of wave.
Table 1: The frequency and amplitude at different signal
Signal
Amplitude,
(μV)
Delta,δ
20-200
Theta, θ
Around 20
439
International Journal of Engineering & Technology
Alpha, α
8-15
20-200
Beta, β
15-40
5-10
It records the brain wave pattern from the signal produces. From
ionic current, the EEG will measure the inconstantly voltage es-
tablish from internal neurons of the brain. In clinical condition,
EEG show the chronicle of the mind's unconstrained electrical
movement over a period, as recorded from numerous anodes put
on the scalp [8].
Muscular pain usually comes after unaccustomed or eccentric
exercise and is usually defined as delayed onset muscle soreness
(DOMS). DOMS cause reduced range of motion and decrease in
capability of muscle to produce force. It also causes pain that is
exacerbated by movement. The typical symptoms of DOMS are
muscle tenderness, stiffness, strength loss, swelling and pain. The
peak of muscle soreness can be felt around 24 to 72 hours and the
resolution of symptoms can long to 5 to 7 days [9].
Fig. 1: Physiological effect of cold water immersion [13]
Over the past decade, cold water immersion (CWI) is a technique
and the most popular strategies to prevent and manage DOMS and
use in post-exercise recovery. CWI becomes popular because of it
can perform in different situations and low-cost techniques [10].
Based on endurance exercise, studies have shown that cold water
immersion reduces the blood flow to the limbs and muscle. Endo-
thelin is peptides that constrict blood vessels and raise blood pres-
sure has been implicated in vascular responses to cold exposure.
Therefore, muscle and limb blood flow regulated after cold water
immersion applied. The temperature of muscle after endurance
exercise also reduces after cold water immersion apply [11]. The
metabolic activity and muscle blood flow reported decrease when
applying cold water immersion [12]. Cold water immersion has
also been proposed to reduce inflammation from exercise [11].
Figure 2.9 shows the physiological effect of cold water immersion
[13].
2. Experimental Set Up
Experiment is started with before the workout, EEG signal wave
for meditation is taken using Neurosky mindwave for 5 minutes.
After that, athlete start the workout routine and after finish the
workout routine, EEG signal wave for meditation is taken again
for another 5 minutes for reading after workout. Then, athlete will
perform the cold bath water immersion for 15 minutes. There have
three experiments for each athlete. Each athlete will repeat three
different temperature which is 13°C, 14°C and 15°C. The reading
for data will take at 11 minutes, 12 minutes, 13 minutes, 14
minutes and 15 minutes.
In this study, there are few types of equipment used to conduct the
experiment. The equipment is divided into tools, hardware and
software which use to extract the data. The tools that used for cold
water immersion therapy for an athlete are bath tub, chiller Hailea
HS-90A, water pump and rubber pipe. MATLAB is the software
used to retrieve data from hardware used which is NeuroSky
Mindwave.
2.1. Hardware and software stage
The hardware involves experimental components, Neurosky
Mindwave device and the software uses MATLAB R2015. Figure
3.6 shows the components set up for experiment. The water pump
is located inside the bath tub and below the water level. The water
pump is connected with rubber pipe and the other end rubber pipe
will connect with inlet at Chiller Hailea HS-90A. Another rubber
pipe with connect with the outlet of Chiller Hailea HS-90A and
the other end is put inside the bath tub. For this experiment, make
sure that no water leakage from the rubber pipe connections. Be-
fore starting the chiller, the pump must be run and make sure that
there is water in the bath tub. After that, set the required tempera-
ture.
Fig. 2: Components set up
Meanwhile, the Neurosky Mindwave device will take the electri-
cal wave that produces by the brain. EEG signal have a specific
signal frequency that can be divided into two condition that are
waves or rhythmic patterns. The frequency response measured in
Hertz (Hz) or cycles per seconds generates different type of brain
wave pattern that is delta, theta, alpha, beta and gamma. This
study aims to study the response of athlete after applying the cold
water immersion.
Based on the Cheron et al., 2016,[14] know that the person will
feel fatigue after perform sport and it will generates Beta (β) wave
which is in 15-30 Hz and the person when relax and resting state
is alpha (α) wave which in 8-15 Hz. The electrical wave that form
from the response of a person brain of Neurosky mindwave will
extract in total waves. It need to classify which type of the fre-
quency wave occurs. From that, the wave pattern can see whether
delta, theta, alpha, beta and gamma. The result will show whether
the athlete is recover or not after performing the recovery system
which is cold water immersion and the result obtained will be
tabulated on.
2.1.1. MATLAB Software
MATLAB software will be used to interpret the data that been
extract by NeuroSky Mindwave. MATLAB is developed by
International Journal of Engineering & Technology
440
MathWorks and it is a multi-paradigm programming language
numerical analysis. This software is written the different language
of program such as C, C++, Java, and Python to interfacing the
program, plotting of data and function, implementation of algo-
rithm and creation of user interfaces.
The technology of thinkgear inside NeuroSky enables it to inter-
face with the wearers brainwaves and responsible for directing
headset data from the serial port to an open network socket. The
thinkgear connector runs a background process on the computer
and process all the data. It also provides the data to software and
applications in digital form using thinkgear module that contains
the onboard chip.
MATLAB software allows the sign is taken from NeuroSky
Mindwave to be displayed and analysed using this software. The
communication protocol between MATLAB and Mindwave EEG
device is illustrated in Figure 3.7. First, ThinkGear.dll file need to
uploaded into Matlab. Connection between Mindwave and Matlab
is established with using com port. After that, use the
TG_ReadPackets function with ID parameter and number of
packet to read to read a Packet of data from the connection. Then
use TG_GetValue function to get the updated value of the raw
EEG signal. Afterwards, can read the value of raw EEG signal.
After finish, close the connection and unload ThinkGear.dll.
Fig. 0: Communication protocol of MATLAB and Mindwave
2.2. Fourier analysis
The extraction data of EEG signal comprises the sum of brain-
wave response or pattern signals. Raw data signal need to change
to time domain. This total brainwave signal are extracted in time
domain.The time domain signal represented by waveform where
the analysis is mainly based on the voltage time plot. The varia-
ble is always measured against time in time domain analysis. Its
operation is not very useful or effective in signal processing. In
this case, Fast Fourier Transform will be used to observe unhidden
means of the signals.
Fast Fourier Transform is one of the technique that can be used to
convert the signal from time domain to frequency domain. In
Matlab, the coding NFFT and FFT algorithm has implemented.
The signals in time domain comprises different signals of time
which can be observed clearly as the peak in frequency domain.
Thus, brainwave patterns at certain frequency range can be clearly
analysed using the highest peak in frequency compared in time
domain.
2.3. EEG data extraction to frequency domain
The NeuroSky mindwave headset was used to allow the data col-
lection when the headset connects with ThinkGear software.
Based on Figure 1 shows the raw data that had been collected
using Neurosky mindwave. After that, Matlab software used to
classified and extracted the data from NeuroSky Mindwave head-
set. The data then will be filtered again into different time domain
range at different frequency as shown in Figure 2. Time domain
are difficult to analyse and need to transform into frequency do-
main. The Fast Fourier Transform (FFT) will be used for the fea-
tures extraction to convert the raw data EEG in time domain to
frequency domain. The FFT method is important because the raw
data signal need to split into the different frequency bands which
alpha band and beta band as shown in Figure 3.
Fig 4: Raw data extraction using NeuroSky Mindwave
Fig 5: Filtered data in time domain
Fig. 6: Filtered data in frequency domain using FFT
441
International Journal of Engineering & Technology
3. Results and Discussions
3.1. Before and after workout
The reading before workout experiment was conducted before
the athletes performed the workout routine. The reading of brain
wave was taken for the 5 minutes before the athletes start the
workout. After that, the athlete will start the workout followed
the routine and after finish all the workout routine. The brain
wave was taken again for the reading after workout for another
5 minutes.
Table 2 summarizes for all athletes (professional, intermediate and
beginner) results for different immersion cool bath temperature of
13, 14 and 15°C. The purpose of the observation is to distinguish
brain wave signal before and after workout among the athletes. It
is to know the response of an athlete before and after workout.
Table 2: Summary of graph before and after workout
Temp (°C)
Beta (β)
Before
Workout
(µV)
After Workout
(µV)
Percentage
(%)
Athlete
1
13
7.259
8.33
12.85
14
3.447
4.466
22.82
15
6.077
6.892
11.83
Athlete
2
13
5.136
5.712
10.08
14
3.738
4.105
8.94
15
4.597
6.210
25.97
Athlete
3
13
5.087
5.552
8.38
14
6.075
7.740
21.51
15
5.030
5.664
11.19
These show all athletes experienced increasing of beta wave after
workout exercise when compared with before workout. From the
result, the reading of EEG shows that response in beta wave is
increased after perform the routine of workout. It show that the
athlete feel fatigue after perform the workout.
3.2. Cold water immersion
Table 3 shows that the result of the highest alpha based on differ-
ent time and temperature. From the analysis that have been con-
ducted using the Matlab to find the best temperature and time for
an athlete. The analysis was conducted with find the highest alpha
wave that means of relaxed. Based on the analysis using Matlab,
find that there have 3 different time with different temperature that
form the highest alpha value based on different athletes as shown
in Table 3.
From that, the analysis conducted again to find the best alpha
value based on the athletes and it shows the result for athletes 1
for perform the cold water immersion is between 13 minutes to 15
minutes. However, the best cold water immersion is at cold bath
temperature 14°C with cold water immersion 14 to 15 minutes for
the athlete 1.
For athletes 2, the best alpha value for perform the cold water
immersion is between 12 minutes to 14 minutes. It different be-
tween athlete 2 in terms of cold water immersion time but the
reason for the different time for the water immersion is it because
different people react differently based on their body and the ac-
tivity. The best time for athlete 2 also at the temperature 14°C and
for the cold water immersion is 13 to 14 minutes.
Then, for athletes 3 the best temperature to perform cold water
immersion is at 14°C with 13 to 14 minutes cold water immersion
same with athlete 2. However, the result shows at the cold bath
temperature 15°C, the best alpha value is at 11 minutes to 12
minutes cold water immersion. Based on the experiment, the read-
ing shows the different from expected. It may because of the con-
dition when conducted the experiment which is that time is raining
so the athlete recover early than the expectation because response
with the environment condition.
Table 3: The highest alpha wave in cold water immersion
Athlete
Cold bath
Temperature (°C)
Time
(minutes)
α, µVolt
1
14
14-15
7.423
2
14
13-14
8.917
3
14
13-14
9.596
3.3. After workout and cold water immersion
The reading after workout experiment was conducted after the
athletes performed the workout routine. The reading of brain wave
was taken for the 5 minutes after the athletes finish the workout.
After that, the athlete will performed cold ice bath therapy for the
15 minutes. In this result, only the best time are chooses to know
the response of an athletes in the beta wave.
The result is summarised for all athletes (professional, intermedi-
ate and beginner) at 14°C cold bath water immersion which is the
best cold bath temperature. The purpose of the observation is to
distinguish brain wave signal after and during performed cold bath
among the athletes. It is to know the response of an athlete after
and during perform cold bath water immersion.
Based on Table 4, it shows that the athletes are feel fatigue after
perform the workout. The highest peak value shows in beta fre-
quency is after workout for the athlete 1,2 and 3. It can conclude
that the athletes are tired or fatigue after the routine of workout
and when performed the cold water immersion, the fatigue are
reduced as shown the beta wave is higher at after workout than
when performed the cold bath.
Table 4: Summary of graph after workout and cold bath
Athlete
Temp
(°C)
Beta (β)
After Workout
(µV)
Before Workout
(µV)
Stress Relieve
(%)
1
14
4.884
4.536
7.13
2
14
6.510
4.144
36.34
3
14
5.713
5.053
11.55
4. Conclusion
This project applied Neurosky Mindwave to know the recovery
response of an athletes when perform ice bath therapy which is
one of the recovery technique after the exercise. The Neurosky
Mindwave is used to extract the brain wave in raw data and
Matlab software is used to evaluate the raw data signal that pro-
duced by athletes. The data is evaluated in time domain and fre-
quency domain, the wave bands that evaluated in this project is
alpha wave and beta wave.
The study was conducted to know the response of athlete before
the exercise and after the exercise. Besides that, it also determines
the best temperature when performed the cold bath and the best
time for cold water immersion. For the response of the athlete, the
peak value in alpha wave is higher before exercise. This shows
that the person is in relaxed condition. After the exercise, the re-
sponse of data show the beta wave indicates the athlete is in fa-
tigue condition. For the best temperature to performance cold bath
based on this experiment is 14°C and the best time is between 13
minutes to 15 minutes.
Acknowledgements
The authors gratefully acknowledge the financial support from
Research and Innovation Fund of Research Management Centre
(RMC) Universiti Tun Hussein Onn Malaysia (UTHM).
International Journal of Engineering & Technology
442
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Background Cold Water Immersion (CWI) is commonly used to manage delayed onset muscle soreness (DOMS) resulting from exercise. Scientific evidence for an optimal dose of CWI is lacking and athletes continue to use a range of a treatment protocols and water temperatures. Objectives To compare the effectiveness of four different water immersion protocols and a passive control intervention in the management of DOMS. Design Randomised controlled trial with blinded outcome assessment. Setting University Research Laboratory Participants 50 healthy participants with laboratory induced DOMS randomised to one of five groups: Short contrast immersion (1 min 38°C/1 min 10°C x 3), Short intermittent CWI (1 min x 3 at 10°C); 10 minute CWI in 10°C; 10 minute CWI in 6°C; or control (seated rest). Main outcome measures muscle soreness, active range of motion, pain on stretch, muscle strength and serum creatine kinase. Results 10 minutes of CWI in 6°C was associated with the lowest levels of muscle soreness and pain on stretch however values were not statistically different to any of the other groups. There were no statistically significant differences between groups for any other outcomes. Conclusion Altering the treatment duration, water temperature or dosage of post exercise water immersion had minimal effect on outcomes relating to DOMS.
Article
Fatigue may be defined as a reduction in the maximal force-generating capacity of a muscle. It may result from peripheral processes distal to the neuromuscular junction and from central processes controlling the discharge rate of motoneurons. When assessed with a sensitive test using twitch interpolation, most 'maximal' voluntary contractions approach but do not attain optimal muscle output. During fatigue, reflex inputs from intramuscular receptors may contribute to a decline in motor unit discharge rate--a decline which optimises force production during maximal efforts. Further studies should investigate how the central nervous system controls the discharge rate of motor units during fatigue produced by different forms of exercise.