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Effects of Relaxing Music on Mental Fatigue Induced by a Continuous Performance Task: Behavioral and ERPs Evidence

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The purpose of this study was to investigate whether listening to relaxing music would help reduce mental fatigue and to maintain performance after a continuous performance task. The experiment involved two fatigue evaluation phases carried out before and after a fatigue inducing phase. A 1-hour AX-continuous performance test was used to induce mental fatigue in the fatigue-inducing phase, and participants' subjective evaluation on the mental fatigue, as well as their neurobehavioral performance in a Go/NoGo task, were measured before and after the fatigue-inducing phase. A total of 36 undergraduate students (18–22 years) participated in the study and were randomly assigned to the music group and control group. The music group performed the fatigue-inducing task while listening to relaxing music, and the control group performed the same task without any music. Our results revealed that after the fatigue-inducing phase, (a) the music group demonstrated significantly less mental fatigue than control group, (b) reaction time significantly increased for the control group but not for the music group, (c) larger Go-P3 and NoGo-P3 amplitudes were observed in the music group, although larger NoGo-N2 amplitudes were detected for both groups. These results combined to suggest that listening to relaxing music alleviated the mental fatigue associated with performing an enduring cognitive-motor task.
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RESEARCH ARTICLE
Effects of Relaxing Music on Mental Fatigue
Induced by a Continuous Performance Task:
Behavioral and ERPs Evidence
Wei Guo
1
, Jie Ren
2
*, Biye Wang
1
, Qin Zhu
3
1School of Kinesiology, Shanghai University of Sport, Shanghai, China, 2China Table Tennis College,
Shanghai University of Sport, Shanghai, China, 3Division of Kinesiology and Health, University of Wyoming,
Laramie, Wyoming, United States of America
*renjie@sus.edu.cn
Abstract
The purpose of this study was to investigate whether listening to relaxing music would help
reduce mental fatigue and to maintain performance after a continuous performance task.
The experiment involved two fatigue evaluation phases carried out before and after a
fatigue inducing phase. A 1-hour AX-continuous performance test was used to induce
mental fatigue in the fatigue-inducing phase, and participantssubjective evaluation on the
mental fatigue, as well as their neurobehavioral performance in a Go/NoGo task, were mea-
sured before and after the fatigue-inducing phase. A total of 36 undergraduate students
(1822 years) participated in the study and were randomly assigned to the music group and
control group. The music group performed the fatigue-inducing task while listening to relax-
ing music, and the control group performed the same task without any music. Our results
revealed that after the fatigue-inducing phase, (a) the music group demonstrated signifi-
cantly less mental fatigue than control group, (b) reaction time significantly increased for the
control group but not for the music group, (c) larger Go-P3 and NoGo-P3 amplitudes were
observed in the music group, although larger NoGo-N2 amplitudes were detected for both
groups. These results combined to suggest that listening to relaxing music alleviated the
mental fatigue associated with performing an enduring cognitive-motor task.
Introduction
Mental fatigue is a complex concept relevant to different areas of studies including physiology,
sports medicine, psychology and therapy. In the present study, mental fatigue is defined as the
feeling that people may experience during and following prolonged periods of cognitive activity
requiring sustained mental activity [1]. Mental fatigue, which has been found to considerably
disrupt task performance, is very common in daily life. It can lead to a variety of negative con-
sequences, such as low productivity, poor study efficiency and even traffic accidents [25].
Thus, it is of great importance to explore the mechanisms underlying mental fatigue, and
develop efficient methods to alleviate mental fatigue.
PLOS ONE | DOI:10.1371/journal.pone.0136446 August 25, 2015 1/12
OPEN ACCESS
Citation: Guo W, Ren J, Wang B, Zhu Q (2015)
Effects of Relaxing Music on Mental Fatigue Induced
by a Continuous Performance Task: Behavioral and
ERPs Evidence. PLoS ONE 10(8): e0136446.
doi:10.1371/journal.pone.0136446
Editor: Alessandro Antonietti, Catholic University of
Sacro Cuore, ITALY
Received: March 3, 2015
Accepted: August 4, 2015
Published: August 25, 2015
Copyright: © 2015 Guo et al. This is an open access
article distributed under the terms of the Creative
Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information files.
Funding: This study was supported by the First-class
Disciplines of Shanghai Colleges and Universities
(Psychology). The funders had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript.
Competing Interests: The authors have declared
that no competing interests exist.
The effects of mental fatigue on cognitive-motor performance are well documented. Mental
fatigue leads to decreased attention, delayed reaction times and increased number of errors during
visual reaction tasks as a result of decreased levels of brain activation [1,610]. Subjective feelings
of mental fatigue are typically assessed by the Visual Analogue Scale, which asks participants to
rate their subjective feelings of mental fatigue from 0 (minimum) to 100 (maximum) [11].
Using the Go/NoGo paradigm, increased mental fatigue has been found to increase the
latencies of Go- and NoGo-P3 and NoGo-N2, while decreasing the amplitude of NoGo-P3 [1].
The amplitude of Go-P3, a late positive event-related potential (ERP) component, is an index
of the amount of resources devoted to identifying a target stimulus. In addition, Go-P3 latency
has been suggested as a measure of stimulus evaluation duration that is independent of
response selection and execution processes [1215].The NoGo-N2 component reflects detec-
tion of response conflict, indicated by an increased amplitude in high-conflict trials [16,17].
A number of methods have been developed that alleviate the effects of mental fatigue on cog-
nitive motor performance. First, attempts have been made to prevent mental fatigue before it
occurs. For instance, ingestion of nutrients (such as a vitamin/mineral supplement) before a sus-
tained cognitive task reduced subjective mental fatigue and improved the subsequent cognitive
performance [18,19]. Second, methods have been created to alleviate concurrent mental fatigue.
It has been reported that the presence of intermittent odours during the completion reduced
mental fatigue and improved attentional/effortful control of response selection, resulting in a bet-
ter cognitive-motor performance [20]. Furthermore, Kaplan [21] reported that exposure to natu-
ral settings and stimuli such as landscapes and animals to reduce mental fatigue. In conclusion,
interventions have been designed to either prevent or reduce mental fatigue. The focus of the
present study was testing an intervention designed to reduce concurrent mental fatigue.
People tend to listen to music while working, studying or driving in daily life. It is believed
that music may help alleviate mental fatigue and improve work efficiency. A number of studies
have found that music affects people's cognitive processes [2224]. For instance, Arikan et al.
[22] reported that hearing music that was well-known by participants increased the allocation
of attentional resources during memory updating processes in an auditory oddball task. This
should also be reflected by a larger P3 amplitude. Also, it has been shown that listening to
relaxing music is an effective way to recover from exercise-induced physical fatigue [25,26].
Jing et al. [26] found that compared to those who had 15-minute rest without music after com-
pleting an exhausting cycle ergometer test, participants who listened to relaxing music for 15
minutes had a greater decrease in heart rate, urinary protein, and ratings of perceived exertion
(RPE). However, the effect of listening to the relaxing music on the mental fatigue induced by
the enduring cognitive motor task remained unknown. The present study was designed to
examine this issue, along with the associated neurobehavioral mechanisms.
The Go/NoGo paradigm was used to examine the availability of participantsattentional
resources and conflict monitoring and inhibition process (as indexed by N2 and P3) following
completion of the continuous performance task, with and without the presence of relaxing
music. This will provide information in regards to the underlying neurobehavioral mechanisms.
It was hypothesized that listening to relaxing music would result in a reduced subjective feeling
of mental fatigue and reduce the negative effects of fatigue on cognitive-motor performance.
Materials and Method
Participants
36 undergraduate students (18 females and 18 males) between 18 and 22 years of age
(M = 20.3) participated in the experiment. They were all right-handed, had normal or cor-
rected-to-normal vision and normal audition. None of them was over-weight or obese (body
Relaxing Music Alleviates Mental Fatigue
PLOS ONE | DOI:10.1371/journal.pone.0136446 August 25, 2015 2/12
mass index (BMI) of all participants was less than 25). None had a history of current or past
neurological or psychiatric illnesses and none was taking any medication known to affect the
central nervous system. Table 1 shows the main characteristics of the participants.18 males and
18 females were randomly assigned to the control group and the music group. Both groups per-
formed the same tasks (fatigue-inducing and fatigue-evaluating tasks), however, the control
group performed the 60-min fatigue inducing task in a quiet condition, and the music group
performed the same task while listening to relaxing music. Written informed consent was
obtained from all participants prior to the study. Participants didnt know the real purpose of
the study and were paid for their participation. The Ethical Committee of Shanghai University
of Sport approved the manner of consent and the study.
Procedures
Participants were instructed to abstain from alcohol 24 h before the experiment and from caf-
feine-containing substances 12 h before the experiment. Each participant was seated in a dimly lit,
electrically shielded room with response keyboard in his/her right hand. The experiment consisted
of 3 continuous phases. The first phase was filled with a 15min long Go/NoGo task as fatigue-
evaluating task. Participants could have a rest every 5min in order to prevent fatigue. After which,
participants were required to fill out the VAS. Phase 2 was filled with the fatigue-inducing task,
during which participants performed 60 min AX-continuous performance task without rest.
Then participants performed the VAS again and finished phase 3 with another 15min long
fatigue-evaluating task, which was the same as the first phase. The participants were instructed to
respond as quickly as possible, maintaining a high level of accuracy. Both the control and music
group performed the fatigue-evaluating task with the concurrent electroencephalography (EEG)
data recorded, which was not performed during the fatigue-inducing phase. While performing
the fatigue-inducing task, participants in the music group listened to the relaxing music, those in
the control group did not. The relaxing music was chosen from functional music developed by
the China Institute of Sport Science. These pieces of music helped Chinese athletes alleviate men-
tal fatigue during the preparing for the 2008 Beijing Olympic Games. All participants listened to
the same 12 pieces of instrumental folk music (no lyrics) music during the fatigue-inducing phase.
The chosen pieces were played to the participants at a tempo of 6080 beats per minute. The
music was presented via a power amplifier connected to a computer, with a volume of 40dB.
Fatigue-evaluating task. A Go/NoGo paradigm was used to measure effect of mental
fatigue. A computer screen (19inch) was positioned approximately 1m in front of the partici-
pants. The fixation point was a cross (1×1° of visual angle) displayed in the center of the screen
for 1500ms. Four squared configurations subtending 4×4° were presented for 100ms on a dark
background, and were displayed randomly with equal probability (p = 0.25), and a stimulus
onset time of 800ms. Two configurations were defined as targets and two non-targets (Fig 1).
The participants were instructed to press a button as quickly as possible with their right hand
when the target appeared on the screen (Go stimuli; p = 0.5), and withhold responding when a
non-target appeared (NoGo stimuli; p = 0.5). The task consisted of 4 blocks of 400 trials.
Table 1. Main characteristics of the participants.
total music group control group
Age(yr) 20.33 ±1.26 20.31 ±1.25 20.35 ±1.31
Height(m) 1.68 ±0.09 1.66 ±0.08 1.69 ±0.10
Weight(kg) 60.43 ±10.75 59.72 ±10.31 61.00 ±11.32
BMI(kg/m
2
) 21.24 ±2.14 21.34 ±2.60 21.16 ±1.75
doi:10.1371/journal.pone.0136446.t001
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Fatigue-inducing task. Mental fatigue was induced by asking participants to work on the
AX-continuous performance task for 60 min. In this task, letters that consisted of cue stimuli
(target letter A and non-target letter B) and probe stimuli (target letter X and non-target letter
Y) were presented sequentially on a computer screen. Participants sat in front of a numeric
keyboard and were instructed to give a target response (press button1on a numeric keyboard)
to a probe letter Xafter a cue letter A. In all other cases, they had to respond with a non-tar-
get response (button3on the same keyboard). The frequency of A-X trails was 70% and A-Y,
B-X, B-Y trails were 10% respectively.
Subjective evaluation of Mental Fatigue (VAS). The participants were asked to subjec-
tively rate their alert/concentrated, anxious, energetic, confident, irritable, jittery/nervous,
sleepy, talkative levels on a visual analogue scale (VAS) from 0 (minimum) to 100 (maximum).
Previous studies have shown that the VAS was valid for subjective evaluation of mental fatigue
[11,27]. Participants were asked to perform ratings before and after the fatigue-inducing phase
in order to assess the change in subjective feelings after performing the task trials.
Data recording and analysis
Reaction time and error rate were measured as behavioral variables via e-prime (Psychology
Software Tools, Pittsburgh, PA, USA). With the 1020 system, the electroencephalogram
(EEG) signals were recorded from 64 electrodes attached to an electrocap (Brain Products,
BrainAmp MR Plus), and all electrodes were referenced to linked ears. A ground electrode
located between Fpz and Fz. The electro-oculogram (EOG) was recorded bipolarly from two
electrodes placed at the outer canthi of the right eye and below the left eye. Electrode imped-
ance was kept below 5 kO. Signals were digitized at a rate of 1000 Hz.
ERPs were collected with the Brain Products recorder software and were analyzed off-line
by its analyzer. The ERP signals were averaged off-line for the correct responses only. Trails
contaminated with artifacts greater than ±120μV were rejected before averaging and the aver-
aged ERPs were smoothed through a low-pass digital filter at 30 Hz. The epoch for ERP analy-
sis was 1000 ms (200 ms before and 800 ms after the stimulus onset). For ERP analysis, 3
electrodes of Fz, Cz and Pz were selected. The ERP components were specifically described by
N2 (range 200350 ms) and P3 (range 350600 ms) in both Go and NoGo trails during the
fatigue-evaluating task.
Statistical analysis
Statistical analyses of subjective data, behavioral data and ERP data were performed using a
mixed-design ANOVA. The between-subjects variable was condition (music and control), and
Fig 1. Stimuli used in Go (the two pictures on the right) and NoGo (the two pictures on the left) task.
doi:10.1371/journal.pone.0136446.g001
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the within-subject variable was the testing phase (before and after fatigue-inducing task).
Degrees of freedom were corrected whenever necessary using the Greenhouse-Geisser epsilon
correction factor. The significant level was set at p <0.05.
Results
Fatigue Scale
The VAS scores on anxious (F
(1,34)
= 19.13, p <0.01, η
p2
= 0.36), irritable (F
(1,34)
= 8.21,
p<0.01, η
p2
= 0.20), sleepy (F
(1,34)
= 21.81, p <0.01, η
p2
= 0.39) significantly increased; and the
scores on alert/concentrated (F
(1,34)
= 50.69, p <0.01, η
p2
= 0.60), energetic (F
(1,34)
= 73.47,
p<0.01, η
p2
= 0.68), confident (F
(1,34)
= 42.43, p <0.01, η
p2
= 0.56) significantly decreased
after the fatigue-inducing mental task session. There was also a significant interaction between
testing phase and condition for alert/concentrated (F
(1,34)
= 14.69, p <0.01, η
p2
= 0.30), anxious
(F
(1,34)
= 9.09, p <0.01, η
p2
= 0.21), energetic (F
(1,34)
= 12.52, p <0.01, η
p2
= 0.27), confident
(F
(1,34)
= 10.04, p <0.01, η
p2
= 0.23) and irritable (F
(1,34)
= 6.29, p <0.05, η
p2
= 0.16). Further
interaction contrasts for different testing time showed that before the fatigue-inducing phase
all the subjective levels were not significantly different between the control and music groups.
However, after the fatigue-inducing phase, the music groups scores on alert/concentrated
(F
(1,34)
= 12.08, p <0.01), energetic (F
(1,34)
= 8.79, p <0.01), confident (F
(1,34)
= 11.35, p <0.01)
were significantly higher than those of control group, and the control groups scores on anxious
(F
(1.34)
= 5.63, p <0.05) and irritable (F
(1,34)
= 5.81, p <0.05) were significantly higher (see
Table 2 and S1 Table for supplement). These results suggested that our fatigue-inducing task
did result in mental fatigue on both groups, but it affected control group more than music
group.
Behavioral performance
Reaction times of Go trials significantly increased after the fatigue-inducing task (F
(1,34)
= 3.98,
p = 0.05, η
p2
= 0.11). There was a significant interaction between condition and test phase
(F
(1,34)
= 10.85, p <0.01, η
p2
= 0.24). An interaction contrast indicated that reaction time signif-
icantly increased for the control group (500ms to 520ms), but remained the same for the music
group (502ms to 498ms). The accuracy of the task did not differ at all (see Fig 2 and S2 Table
for supplement).
Table 2. Scores of the fatigue scale.
Before task After task
Control group Music group Control group Music group
alert/concentrated 73.8 ±12.89 72.22 ±16.29 35.00 ±22.82 60.55 ±21.27**
anxious 26.11 ±16.14 27.78 ±18.96 53.33 ±30.29 32.78 ±20.81*
energetic 72.22 ±14.37 67.78 ±16.29 29.44 ±18.93 50.00 ±22.49**
feel condent 72.22 ±15.17 73.33 ±15.72 41.67 ±18.86 62.78 ±18.73**
irritable 22.22 ±23.90 20.56 ±14.74 38.89 ±24.71 21.67 ±17.57*
jittery/nervous 23.89 ±22.00 25.00 ±18.86 31.67 ±23.57 26.11 ±19.44
sleepy 41.67 ±25.26 43.33 ±26.57 72.78 ±22.70 57.22 ±20.52
talkative 32.78 ±24.21 25.00 ±16.89 27.22 ±21.64 22.78 ±13.20
** p<0.01
*p<0.05
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P3 component
Fig 3 shows the grand-average ERPs at the Fz, Cz and Pz sites for NoGo trails. The NoGo-P3
amplitudes at Cz and Pz sites significantly decreased after the fatigue-inducing phase (F
(1,34)
=
9.64, p <0.01, η
p2
= 0.22; F
(1,34)
= 4.63, p = 0.04, η
p2
= 0.12, respectively). The interactions
between testing phase and condition were significant at the Cz and Pz sites (F
(1,34)
= 8.95, p
<0.01, η
p2
= 0.21; F
(1,34)
= 4.91, p = 0.03, η
p2
= 0.13, respectively). An interaction contrast at
the Cz and Pz sites indicated that the NoGo-P3 amplitudes were significantly different on test-
ing phase for the control group (F
(1,34)
= 6.04, p = 0.02, F
(1,34)
= 4.33, p = 0.05, Cz 6.65 mV,
1.87 mV; Pz 5.53 mV, 3.46 mV), but they were not significant for the music group. Although
the NoGo-P3 latencies at the Fz, Cz and Pz sites all increased after the fatigue-inducing task,
there was no significant difference between the groups.
Fig 4 shows the grand-average ERPs at Fz, Cz and Pz for Go trials as a function of condition
and time-on-task. The Go-P3 amplitudes at Fz and Cz sites significantly decreased after the
fatigue-inducing task (F
(1,34)
= 4.70, p = 0.04, η
p2
= 0.12; F
(1,34)
= 4.81, p = 0.04, η
p2
= 0.12);
The interaction between testing phase and condition at Cz sites was significant (F
(1,34)
= 4.44,
p = 0.04, η
p2
= 0.12); An interaction contrast at the Cz site indicated that the Go-P3 amplitude
of the control group was smaller than that of the music group (4.52 mV, 6.16 mV) after the
fatigue-inducing task. No main effect of condition was found. The Go-P3 latencies at the Fz,
Cz, Pz sites all increased after the fatigue-inducing phase, but the main effect and interaction
were not significant (See S3 Table for description of ERP data).
Fig 2. Average RTs for Go trials as a function of condition and testing time.
doi:10.1371/journal.pone.0136446.g002
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Fig 3. Grand-average ERPs at the Fz, Cz and Pz sites for NoGo trials as a function of condition and testing time.
doi:10.1371/journal.pone.0136446.g003
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N2 component
For the NoGo-N2 amplitudes, the main effect of testing phase was significant at the Cz site
(F
(1,34)
= 4.35, p = 0.05, η
p2
= 0.11).There were no other main effects or interactions found. It
revealed that although NoGo-N2 amplitudes increased at the Cz site after the fatigue-inducing
phase, there were no significant differences between the groups (Fig 3).
As for the Go-N2 amplitudes at Fz, Cz and Pz, the main effects of testing phase and condi-
tion, as well as their interaction were not significant (Fig 4).
Discussion
In the present study, both the music group and control group exhibited signs of mental fatigue
(distracted, anxious, irritable, sleepy and unconfident) after the 60-min of fatigue-inducing
task. This is in accord with previous findings [28] and suggests that our task manipulation was
successful in inducing mental fatigue. Importantly, based on the scores of Visual Analogue
Scale, the control group reported suffering from more mental fatigue than the music group.
This phenomenon was also demonstrated by behavioral data. After the fatigue-inducing
phase, the reaction time of the control group increased on the Go/NoGo task, while the music
group remained the same. The accuracy of the two groups did not change in the Go/NoGo
task, which could be due to the flooring effect, where participants had maintained a fairly high
accuracy in the task. The behavioral results implied that when people perform cognitively chal-
lenging tasks, listening to relaxing music could mitigate performance deterioration (e.g., a
slower response) caused by mental fatigue.
The observed performance deterioration might be related to a reduction in attentional re-
sources allocated to the task due to mental fatigue. Kok [29] suggested that the attentional avail-
ability of resources is the most important factor in determining the performance in the cognitive
task. Lack of attentional resources will lead to the poorer performance. In our study, the Go-P3
amplitude significantly decreased after the fatigue-inducing task for the control group, suggesting
that participants had increasing difficulty allocating resources for stimulus detection as the task
unfolded. In Katos study, they found that mental fatigue had no effect on the Go-P3 amplitude
[1], which was inconsistent with ours. We assumed that different proportion of the Go and
NoGo trials used for study would account for this difference. In their study, the stimulus proba-
bility of Go trials (80%) was greater than that of NoGo trials (20%). As mental fatigue may cause
the decreased availability of cognitive resources [8,20], in order to maintain a speedy response,
the most reasonable decision is to allocate the limited resources to the Go stimuli instead of the
NoGo stimuli. Therefore, participants may have limited capacity to allocate attentional resources
to the NoGo stimulus alone due to mental fatigue. The stimulus probability of Go trails and
NoGo trials in our study was 50% to 50%, thus, participants detected the two stimuli with equal
probability, and they had to allocate equal amount of attentional resources to both Go and NoGo
stimuli. Interestingly, the Go-P3 amplitude decreased less in the music condition compared to
the control condition after the fatigue-inducing task, suggesting that the attentional availability of
resources did not decline much in the music condition. Hence, participants who performed the
fatigue-inducing task in the music condition suffered less mental fatigue.
N2 is an important ERP component in NoGo trails. Many studies have been performed
to clarify the cognitive process reflected by NoGo-N2, some of which suggested that NoGo
N2 reflected conflict monitoring[30,31], and others thought it reflected response inhibition
Fig 4. Grand-average ERPs at the Fz, Cz and Pz sites for Go trials as a function of condition and
testing time.
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[3234]. More and more evidence suggested that N2 might reflect the conflict monitoring pro-
cess. Bruin et al. [35] examined the effects of response priming on N2 evoked by target stimuli
in a Go/NoGo task. They found that N2 was not modulated by response priming, and con-
cluded that it was not associated with response inhibition. Instead they proposed the frontal P3
to be inhibition-specific. This positive wave peaked between 300 and 600 ms after stimulus pre-
sentation and was enhanced on NoGo trials relative to Go trials on the frontal electrode chan-
nels. In the present study, we found that the decrement of NoGo-P3 amplitudes after the
fatigue-inducing task were smaller in the music condition than in their absence. These findings
suggest that listening to the relaxing music plays an important role in mitigating the deteriora-
tion of cognition performance and inhibition resulted from mental fatigue. For the NoGo-N2
trials, there was only a main effect of testing phase at Cz site with no group difference. We
assumed that music only modulated response inhibition without effect on the conflict monitor-
ing process. The relationship between mental fatigue and response inhibition remains unclear.
Falkenstein et al. [36] investigated the inhibition-related ERP components, and they found that
there was no effect of time on task on NoGo-P3 component, therefore, they suggested that the
inhibitory processes were fairly robust against mental fatigue. In Katos study [1], the NoGo-P3
amplitude decreased with time on task, suggesting that mental fatigue affected controlled pro-
cessing for response inhibition. At this point, our findings were consistent with Katos. The
NoGo-P3 amplitudes at Cz and Pz sites significantly decreased after the fatigue-inducing task,
indicating the response inhibition was impaired. These findings combined to suggest that lis-
tening to the relaxing music mitigated the decrement of response inhibition during mental
fatigue.
A previous study found that the presence of intermittent odours during the continuous per-
formance task helped to reduce mental fatigue and maintain performance [20]. The present
study showed the similar effect using relaxing music. Listening to the relaxing music during a
cognitive task may make people feel less mentally fatigued and maintain high productivity. The
effects of relaxing music on alleviating mental fatigue may better explain why people tend to
listen to music while working, studying or driving in daily life. Nevertheless, there are some
limitations of the study. Firstly, the fatigue-inducing task AX-CPT is a relatively simple task,
and so future research should attempt to replicate results using a more difficult task to induce
mental fatigue. Secondly, the relaxing music might act as a distracting stimulus, blocking men-
tal fatigue instead of exerting a relaxing effect. A group listening to a non-musical sound may
be added as a better control in the future experiment.
Conclusion
The current study suggests a potential intervention for reduction in mental fatigue while per-
forming an enduring cognitive-motor task. By listening to relaxing music during a fatigue-
inducing task, both mental fatigue and deterioration in motor performance were reduced. The
analysis of ERP signals further suggested that the music group suffered less impairment of
attentional control of response selection and inhibition than the control group. In sum, these
findings demonstrate that listening to relaxing music can alleviate the mental fatigue encoun-
tered in performing an enduring cognitive-motor task at both behavioral and cognitive levels.
Supporting Information
S1 Table. Fatigue scale data.
(XLSX)
Relaxing Music Alleviates Mental Fatigue
PLOS ONE | DOI:10.1371/journal.pone.0136446 August 25, 2015 10 / 12
S2 Table. Behavioral data.
(XLSX)
S3 Table. ERP data.
(XLSX)
Author Contributions
Conceived and designed the experiments: WG BW JR. Performed the experiments: WG BW.
Analyzed the data: WG BW. Contributed reagents/materials/analysis tools: JR QZ. Wrote the
paper: WG BW QZ. Called for all the participants: JR. Polished the manuscript: QZ.
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Relaxing Music Alleviates Mental Fatigue
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Relaxing Music Alleviates Mental Fatigue
PLOS ONE | DOI:10.1371/journal.pone.0136446 August 25, 2015 12 / 12
... If true, this would provide a clear neurophysiological pathway through which caffeine can reduce MF and provide an easy-to-implement MF countermeasure within multiple contexts (e.g., work and sport) [11,12,19]. Moreover, non-nutritional interventions, for example the use of music, have also been found to counteract the negative impact of MF [20]. It has been proposed that music may act through increasing important neurotransmitter levels and, as such, attenuating feelings of pain and physical exertion experienced during physical performance [21,22]. ...
... All 33 included studies, of which ten are between-subject and 23 within-subject design studies, were screened for risk of bias (see Figs. 2,3). This assessment determined that 25 studies [12,14,20,26,27,[37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56] had a high risk of bias, three studies [57][58][59] had some concerns of bias and five studies [11,13,[60][61][62] had a low risk of bias. ...
... Ten studies used a behavioural countermeasure (see Sect. 2 for a definition) [20, 26, 27, 40, 45-47, 54, 55, 59]. Of these, five studies used a physical sensation-based intervention (e.g., physical activity and massage) [40,45,47,54,59], four other studies utilized an auditory intervention (e.g., listening to music) [20,26,40,45], and two studies [27,46] assessed the effect of a nap on MF. As well as utilising a nap, Hayashi et al. [27] incorporated a moment of rest in the middle of the task as an extra countermeasure in their study. ...
Article
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Introduction Mental fatigue (MF) is a psychobiological state that impairs cognitive as well as physical performance in different settings. Recently, numerous studies have sought ways to counteract these negative effects of MF. An overview of the explored countermeasures for MF is, however, lacking. Objectives The objective of this review is to provide an overview of the different MF countermeasures currently explored in literature. Countermeasures were classified by the timing of application (before, during or after the moment of MF) and type of intervention (behavioural, physiological and psychological). Methods The databases of PubMed (MEDLINE), Web of Science and PsycINFO were searched until March 7, 2022. Studies were eligible when MF was induced using a task with a duration of at least 30 min, when they assessed MF markers in at least two out of the three areas wherein MF markers have been defined (i.e., behavioural, subjective and/or [neuro]physiological) and used a placebo or control group for the countermeasure. Results A total of 33 studies investigated one or more countermeasures against MF. Of these, eight studies assessed a behavioural countermeasure, 22 a physiological one, one a psychological countermeasure and two a combination of a behavioural and psychological countermeasure. The general finding was that a vast majority of the countermeasures induced a positive effect on behavioural (e.g., task or sport performance) and/or subjective MF markers (e.g., visual analogue scale for MF or alertness). No definitive conclusion could be drawn regarding the effect of the employed countermeasures on (neuro)physiological markers of MF as only 19 of the included studies investigated these measures, and within these a large heterogeneity in the evaluated (neuro)physiological markers was present. Discussion Within the physiological countermeasures it seems that the use of odours during a MF task or caffeine before the MF task are the most promising interventions in combating MF. Promising behavioural (e.g., listening to music) and psychological (e.g., extrinsic motivation) countermeasures of MF have also been reported. The most assumed mechanism through which these countermeasures operate is the dopaminergic system. However, this mechanism remains speculative as (neuro)physiological markers of MF have been scarcely evaluated to date. Conclusion The present systematic review reveals that a wide range of countermeasures have been found to successfully counteract MF on a subjective, (neuro)physiological and/or behavioural level. Of these, caffeine, odours, music and extrinsic motivation are the most evidenced for countering MF. To provide in-detail practical guidelines for the real-life application of MF countermeasures, more research must be performed into the underlying mechanisms and into the optimal dosage and time of application/intake.
... Supplementary vital signs that can assist in fatigue detection include respiratory rate and blood oxygen saturation, which a large variety of commercial sensors can measure [20]. Subjective measurements of fatigue have also been found to be useful in research [21], [22], [23]. These psychological self-report measures are dependent on the conditions being investigated. ...
... Simple reaction time measurements such as those utilised by the Psychomotor Vigilance Task (PVT) provide a repeatable metric used to evaluate decline in attention capacity [17], [26]. The accuracy of responses provided in tasks such as the AX-Continuous Performance Test (AX-CPT) and the Stroop Task also provide insight into the task's execution quality [27], [28], [23]. Along with objective and subjective measurements, these performance metrics should provide a reliable method to detect fatigue. ...
Article
The need for proper fatigue detection and mitigation is made clear in research, with failure to detect fatigue resulting in significant societal health repercussions. Currently, there are limited hardware systems dedicated to the monitoring of fatigue-related biometrics. The devices that do attempt to provide this information are often impractical due to their size, required expertise and cost constraints. Access to these technologies by a broader population is therefore limited. Wearable health devices could provide a more practical solution. A data capture system was designed and implemented that records PPG and in-ear EEG information. The device was created to be inexpensive and portable. The in-ear EEG results obtained showed the detection of a statistically significant difference in alpha attenuation levels, which are closely associated with the state of alertness or drowsiness. While the acquired heart rate and blood oxygen saturation measurements showed a close correlation with an FDA approved pulse oximeter. Although the number of trials conducted was limited, the results show promising performance. This project is a stepping stone in the pursuit of an affordable fatigue monitoring solution that can mitigate the human-cost incurred on account of fatigue.
... Studies have shown that the EEG signal is decomposed into 4 bands: delta (δ) (0.5-4 Hz), theta (θ) (4-8 Hz), alpha (α) (8)(9)(10)(11)(12)(13)(14), and beta (β) (14-30 Hz) bands, and these can be measured to detect the current mental state [38]. When the subjects were fatigued, the decreased arousal level elevated the delta power [39]. Early stages of fatigue can be indicated by an increase in theta activity [40]. ...
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Due to the large volume of monitoring data in mines, concentrating on and reviewing the data for a long period of time will easily cause fatigue. To study the influence of different visual codes of early-warning interfaces on the response of individuals who are fatigued, the changes in the subjective fatigue and corresponding frequency waves are compared before and after a fatigue-inducing task, as well as using event-related potential to study the behavioral data and EEG signals of subjects who participated in an oddball task on an early-warning interface. The results showed that all 14 subjects became fatigued after the fatigue-inducing task, and the amplitude of P200 when text is used in a fatigued state was the largest, with the longest latency. The subjects showed a slower reaction time and a reduced accuracy rate, thus indicating that in designing a warning interface, when text rather than color is used as a visual code, the operating load will be larger, mental load is increased, and attention resources are consumed. The experimental results provide the basis for the design and evaluation of early-warning interfaces of mine management systems.
... Overexercise may induce fatigue (Ahmad et al., 2018), while moderate exercise may increase arousal levels (Byun et al., 2014) and improve cognitive performance (Oberste et al., 2019) and physical performance (Fradkin et al., 2010). Attending cultural events, such as listening to music (Guo et al., 2015;Qi et al., 2021), may help to relieve fatigue, which is an essential factor in traffic accidents (Soares et al., 2020) and is related to high-risk behaviors (Gastaldi et al., 2014). Excessive fatigue damages drivers' thinking and memory and may make drivers forget operating procedures, such as forgetting to use the turn signal when turning (George, 2004). ...
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Objective: Previous studies have investigated the relationship between lifestyle and driving behaviors in countries such as Iran and Greece. However, lifestyles vary in different cultures, and the impact of lifestyle on driving behavior in China remains unclear. This study explores the question of how lifestyle influences driving behavior in Chinese culture by developing a lifestyle scale customized for Chinese drivers. Methods: A total of 290 Chinese drivers completed anonymous scales, including sociodemographic variables, a lifestyle questionnaire, and a driving behavior questionnaire. Exploratory and pathway analyses were conducted. Results: The findings demonstrated that (1) the newly developed lifestyle scale, including the dimensions of sports activity (α = 0.792), sleep quality (α = 0.761), cultural events (α = 0.875) and social engagement (α = 0.682), had satisfactory reliability; (2) sports activity had a negative impact on aggressive violations (β =-0.141) and lapses (β =-0.135); (3) sleep quality positively predicted positive driving behavior (β = 0.133) and negatively predicted aggressive violations (β =-0.226), ordinary violations (β =-0.233), errors (β =-0.180) and lapses (β =-0.237); (4) attendance at cultural events negatively predicted positive driving behavior (β =-0.119) and positively predicted errors (β = 0.101) and lapses (β = 0.141); and (5) social engagement positively predicted positive driving behavior (β = 0.135) and aggressive violations (β = 0.143) while negatively predicting errors (β =-0.110). Conclusion: Overall, Chinese drivers’ driving behavior is correlated with their lifestyle. The results emphasize the importance of living a healthy lifestyle and promote the development of better road safety management measures.
... The fatigue relief effect of active cognitive tasks with a motor component is better than that of passive cognitive tasks without any motor components [39], but driving is a behavior that requires attention, thus adding motor components to cognitive tasks (such as stretching or straightening the legs to relax them) is a very dangerous proposition. Listening to music during driving is the choice of many drivers at present, and many studies have shown that music has a fatigue-alleviating effect [29][30][31]. However, this method is too monotonous under long-term driving, and the fatigue relief effect of single music stimulation will gradually weaken, resulting in a reduced ability of the driver to maintain interest, thereby entering the fatigue state. ...
Article
Full-text available
Driving fatigue refers to a phenomenon in which a driver’s physiological and psychological functions become unbalanced after a long period of continuous driving, and their driving skills decline objectively. The hidden dangers of driving fatigue to traffic safety should not be underestimated. In this work, we propose a judgment excitation mode (JEM), which adds secondary cognitive tasks to driving behavior through dual-channel human–computer interaction, so as to delay the occurrence of driving fatigue. We used multifractal detrended fluctuation analysis (MF-DFA) to study the dynamic properties of subjects’ EEG, and analyzed the effect of JEM on fatigue retardation by Hurst exponent value and multifractal spectrum width value. The results show that the multifractal properties of the two driving modes (normal driving mode and JEM) are significantly different. The JEM we propose can effectively delay the occurrence of driving fatigue, and has good prospects for future practical applications.
... As a non-invasive form of fatigue intervention, sound interventions include music interventions and binaural beats interventions. Sound is a regular vibration with an emotional arousal effect [27,28], which has been shown to enhance alertness [29,30], reduce stress [31], treat post-traumatic stress disorder [32,33], reduce mental fatigue [34], and is an effective method used against driving drowsiness and fatigue [35,36]. Music affects the arousal level and emotional state of listeners. ...
Article
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Introduction: It is clear that mental fatigue can have many negative impacts on individuals, such as impairing cognitive function or affecting performance. The aim of this study was to investigate the role of sound interventions in combating mental fatigue. Method: The subjects were assessed on various scales, a psychomotor vigilance task (PVT) task, and a 3 min resting-state electroencephalogram (EEG), followed by a 20 min mental fatigue-inducing task (Time Load Dual Back, TloadDback), during which subjects in different condition groups listened to either 15 Hz binaural beats, 40 Hz binaural beats, relaxing music, or a 240 Hz pure tone. After the mental fatigue-inducing task, subjects were again assessed on various scales, a PVT task, and a 3 min resting-state EEG. Results: After the fatigue-inducing task, there was no significant difference between the four groups on the scales or the PVT task performance. In TloadDback, the accuracy rate of the 40 Hz binaural beats group and the relaxing music group decreased in the middle stage of the task, while the 15 Hz binaural beats group and the 240 Hz pure tone group remained unchanged in all stages of the task. The EEG results showed that after fatigue inducement, the average path length of the 15 Hz binaural beats group decreased, and local efficiency showed an increasing tendency, indicating enhanced brain network connectivity. Meanwhile, the 240 Hz pure tone group showed enhanced functional connectivity, suggesting a state of mental fatigue in the group. Conclusions: The results of this study show that listening to 15 Hz binaural beats is a proven intervention for mental fatigue that can contribute to maintaining working memory function, enhancing brain topological structure, and alleviating the decline in brain function that occurs in a mentally fatigued state. As such, these results are of great scientific and practical value.
... Practically, these results suggest that professionals should consider using MF levels to guide adjustments in exercise session intensity and control negative affect associated with exercise to avoid its negative influence on future exercise adherence. Second, by identifying MF levels, specific strategies can be created to alleviate MF (e.g., listening to music; Guo et al., 2015;Lam et al., 2021) perhaps increasing pleasure and positive implicit attitudes toward aerobic exercise. Future studies will be needed to expand these findings, since the variables we investigated (i.e., MF, implicit attitude, and affective response) still need to be tested in real-world environments. ...
Article
We investigated the effects of mental fatigue (MF) on affective responses during an aerobic exercise session at moderate intensity. We submitted 12 insufficiently active adults (50% women; M age = 24.9 years, SD = 3.0; M BMI = 24.3 kg/m ² ; SD = 2.6) to two 30-minute pre-exercise conditions: an MF condition (Stroop Color-Word task) and a control condition (watching a documentary) prior to their performance of 20 minutes of aerobic treadmill exercise at 40–59% of heart rate reserve. The minimum washout interval between conditions was two days. Perceived MF and motivation to perform physical exercise were assessed before and after conditions with a visual analog scale of 100 mm. We assessed participants’ affective and exertion responses with the Feeling Scale, Rating of Perceived Exertion (RPE) and heart rate during every two minutes of physical exercise. Implicit attitudes toward physical exercise were assessed by the Implicit Association Test before the MF and control conditions and after the physical exercise session. The participants in the MF condition reported lower pleasure ( M difference = −1.57, 95% CI = −2.64 to −0.50, d = 0.93, p = .008) and higher exertion (RPE) ( M difference = 1.16, 95% CI = 0.04 to 2.27, d = 0.66, p = .043) compared to those in the control condition. Participants who experienced MF also reported a more negative implicit attitude toward physical exercise than in the control condition ( β = −0.47, 95% CI= −0.73 to −0.21, d = 1.41, p < .001). While these findings should be cross-validated in subsequent research with a larger and more diverse participant sample, there appears to be value in minimizing pre-exercise mental fatigue to avoid negative MF effects on the exercisers’ affective experience.
... Fatigue is defined as exhaustion, fatigue or tiredness that reveals physical and mental activities (4)(5)(6). Longterm physical and mental tasks resulted in fatigue, a lack of energy, inhibited emotions, unwillingness, and poor cognitive function (7,8). Mental fatigue is characterized by the inability to sustain cognitive function as a result of decreasing brain activity and mental exhaustion (6) and often leads to reduction of attention/concentrationresponse (9), reaction times (10) decision-making ability (11) and response accuracy (12). ...
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Background: Successful performance in soccer is associated with multiple factors such as physical, technical and perceptual-cognitive performance. In contrast to physical fatigue, nowadays one of the most popular affecting factors is mental fatigue, especially in soccer. Objectives: This systematic review aims to clarify the impact of mental fatigue intervention on psychophysiological responses and cognitive performance in soccer. Methods: A literature review was conducted by using the keywords of “mental fatigue and soccer” and “cognitive fatigue and soccer” in the content of confined space, psychophysiological and cognitive performance in soccer within the databases of Pubmed, Scopus, Web of Science (WOS) and Sport Discuss from the 1st of January 2010 to the 31st of January 2022. Systematic searches of six databases resulted in consist of 7 studies. The study was characterized based on PICO (Population, Intervention, Comparison and Outcome) criteria. Results: The current results showed that mental fatigue had a negative impact on psychophysiological responses, impaired cognitive performance, and decreased utilization of technical skills. Conclusions: According to this systematic review, mental fatigue reduces performance via impairing psychophysiological responses, cognitive performance, and technical skills in soccer.
... Il semblerait également qu'écouter de la musique relaxante après un effort physique aiderait à récupérer plus rapidement [85]. Aussi, dans le cadre de la fatigue cognitive, la musique relaxante améliorerait les performances et diminuerait la fatigue [69]. Enfin, l'étude de Potteiger et al. [132] montrerait que il n'y aurait pas de différence significative en terme de fatigue entre plusieurs types de musique mais que dans tous les cas la musique permettrait de diminuer la fatigue ressentie. ...
Thesis
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Récemment, sont apparus de nouveaux casques grand public de réalité virtuelle (RV) aux capacités comparables à ceux utilisés en laboratoire. L'usage de ces technologies est devenu plus courant et les sessions d'utilisation sont devenues plus longues (jeux vidéo, expression artistique, travail à distance, sport, rééducation...). Durant ces temps d'interaction, les utilisateurs ont leurs bras dans les airs parfois sans repos possible. Aussi, ce type d'interaction dans l'air, qualifié de ``mid-air'', est connu pour provoquer de la fatigue au niveau des bras que l'on nomme ``effet Bras de Gorille'' en interaction humain-machine (IHM). Comprendre ce phénomène pour la conception des applications en RV devient un élément essentiel afin d'assurer un confort d'utilisation et aussi d'éviter des blessures.D'abord, nous discuterons les travaux antérieurs traitant le sujet des interactions mid-air puis de la fatigue musculaire avant de présenter des études portant sur ces deux sujets. Puis, au travers de plusieurs expériences, nous avons cherché à étendre notre compréhension de cette fatigue lors de divers exercices en RV. En particulier, nous nous sommes intéressés à différentes synchronisations des mains, au rythme et au rapport contrôle-affichage (CDR), en nous appuyant sur les contextes d'applications pouvant occasionner de longues sessions d'utilisations comme le jeu vidéo et l'expression artistique.Premièrement, nous avons étudié les différences entre interactions uni et bi-manuelles en terme de fatigue au cours de différentes tâches répétitives de sélection de cibles. Il est apparu que la synchronicité de main devait être choisie au regard de la tâche à effectuer pour optimiser le rapport entre fatigue et efficacité. De plus, il semblerait préférable de laisser à l’utilisateur la possibilité d’utiliser ses mains comme il le souhaite afin qu'il auto-régule sa fatigue. En outre, il se pourrait que les changements de postures des utilisateurs soient des indicateurs de la fatigue. Enfin, nous avons pu vérifier que certaines directions de mouvements étaient plus fatigantes, en particulier celle verticale et certaines diagonales. Secondement, suite notamment à l'analyse des retours des participants, nous avons exploré l'impact d'un rythme imposé aux gestes sur la fatigue des bras et l'expérience de l'utilisateur (UX), lors d'un exercice de suivi de cibles. Ce rythme, en particulier s’il est irrégulier et lent, semblerait pouvoir réduire la sensation de fatigue et améliorer l’expérience de l’utilisateur. De plus, si le rythme est souligné par un son simple, le participant pourrait percevoir la tâche comme étant plus fatigante mais également plus engageante qu'en l'absence de son. Enfin, nous avons voulu observer les effets de variations du CDR sur la fatigue et l'UX. Cette expérience a pris place dans un instrument de musique virtuel immersif (IVMI) afin de motiver les gestes mid-air des participants. Ils ont dû explorer un cube musical alors que leurs gestes étaient visuellement amplifiés ou réduits, plus ou moins fortement. Quand le CDR est modérément modifié, il pourrait avoir un impact bénéfique sur l'UX lors de l’interaction avec un IVMI. Aussi, étonnamment, nous n'avons observé aucun impact significatif sur la fatigue alors que, pour une grande variation du CDR, les utilisateurs parcouraient moins de distance avec leur main et que cette distance était corrélée à la fatigue. Étudier le CDR sur des temps d'interaction plus longs nous permettra peut-être d'observer un impact sur la fatigue.En conclusion, nous avons pu retirer des implications intéressantes sur les choix de conceptions les plus judicieux à effectuer lorsque l'on veut proposer des applications peu fatigantes en RV. Nous avons également proposé des idées de futurs travaux qu'il serait intéressant d'étudier, comme l'utilisation de la manipulation redirigée entre des zones de CDR différenciées ou l'étude des changements de postures comme indicateur de la fatigue.
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In recent years, brain functional connectivity (FC) plays an important role in the field of cognitive state monitoring and has attracted the attention of many researchers. In this study, we explored the effects of rest on the brain by designing a two-session experiment with 20 healthy participants. In session one, subjects were required to do four consecutive experiments (No-rest session), whereas, in session two, subjects were required to do a mid-task break by adding a rest run in the middle of consecutive tasks (Rest session). To reveal the changes in brain FC over long timescales, a dynamic brain network with three frequency bands (theta, alpha, and beta band) was established. Compared to the pre-task rest runs, a significant decrease in temporal global efficiency was observed in theta and alpha bands in post-task rest (theta: pre-task rest > post-task rest, F1,19 = 4.501, p = 0.047, η² = 0.010; alpha: pre-task rest > post-task rest, F1,19 = 4.686, p = 0.043, η² = 0.027) whereas there was a significant increase in temporal local efficiency in the theta band (pre-task rest < post-task rest, F1,19 = 7.646, p = 0.012, η² = 0.043). Such results manifested that the temporal local efficiency had a positive correlation with the duration of the task. In addition, we use a two-way repeated-measures ANOVA for the temporal closeness centrality of each channel. In general, significant differences (including block effect, session effect and interaction effect) are found in three frequency bands, and these channels are mainly distributed in frontal and occipital regions. Overall, this work is an expansion of EEG-based static brain network fatigue analysis and the results manifest that the temporal local efficiency of the brain increases in the process of fatigue to overcome the decline of the overall efficiency of the brain.
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