Enhancing Tennis Performance through Visual Training: The

Ann Appl Sport Sci,

12(S1): e1279, 2024.

http://www.aassjournal.com; e-ISSN: 2322–4479; p-ISSN: 2476–4981. 10.61186/aassjournal.1279

*. Corresponding Author:

Sheiladevi Sukumaran, Ph.D.

E-mail: [email protected]

ORIGINAL ARTICLE

Enhancing Tennis Performance through Visual Training: The Efficacy

of Dynamic Vision Exercises

Zhang Die Die ,

Sheiladevi Sukumaran

Liming Vocational University, Quanzhou City, Fujian Province, China.

Faculty of Education, Language,

Psychology and Music, SEGi University, Malaysia.

Submitted October 18, 2023; Accepted in final form December 28, 2023.

ABSTRACT

Background. This research examined the impact of visual training on tennis skill levels. Tennis demands high visual

capabilities from athletes, requiring them to maintain focus throughout the entire game to secure winning points and

ensure victory. The significant impact of visual training on enhancing tennis performance has not been thoroughly

investigated. Objectives. The purpose of this study is to investigate the impact of an 8-week visual training on tennis

performance and to identify the correlation between the effects of visual training and Tennis Performance. Methods.

Participants (n=50) engaged in dynamic vision exercises using The Sensory Station Training Application and practiced

tennis hitting while wearing dynamic vision training devices. The training program aimed to enhance participants'

visual skills in real tennis scenarios. The increase of visual training is an effective method to improve tennis skill levels.

Results. After eight weeks of visual training, the experimental group's ITN average score increased by 40.80 points,

indicating a significant improvement. The findings showed that there was no significant improvement in static visual

acuity, including visual clarity (Cohen's d=0.05) and perception span (Cohen's d=0.08). However, notable

improvements were observed in dynamic visual acuity, specifically in hand-eye coordination (Cohen's d=1.26),

reaction time (Cohen's d=1.71), and GO/NO GO (Cohen's d=3.11). Conclusion. These studies provide compelling

evidence supporting the idea that visual training can enhance tennis performance.

KEYWORDS: Dynamic Vision Exercises, Tennis Skills Levels, Training, Visual Training.

INTRODUCTION

Visual training was first initiated in France by

Javal and Manuel (1). Since then, the field of

ophthalmology has seen continuous development

and diversification of visual training methods

across generations of practitioners. It is now

widely applied in various fields, including sports

education, driving skills, professional skills,

academic learning, and performing arts. Visual

training has sparked significant interest among

researchers and coaches as a widely discussed and

applied method in various sports disciplines. The

concept of sports vision may vary among different

scholars. Sports vision is a specific visual ability

that differs from other visual functions. This ability

is crucial for athletes to process and perform at

their best. Athletes must gather a considerable

amount of visual information quickly. Evidence

shows that visual skills vary between athletes and

non-athletes, and impact athletic performance (2,

3). Research on sports vision is still in its early

stages, but it is widely recognized as a critical

component of athletic performance (4, 5). In

sports, vision is vital in providing athletes with

crucial information on where, when, and what to

do. Without the ability to quickly and accurately

process visual information, even the strongest,

2 Enhancing Tennis Performance through Visual Training

fastest, and most technically skilled athlete may

not reach their full potential. Dynamic visual skill

is mainly involved in catching or interceptive

actions of ball sports, whereas strategic sports use

different visual skills (peripheral and spatial

vision) due to the sport-specific requirements (6).

Sports vision is a specific visual ability that

differs from other visual functions. Sports Vision

is defined as the brain's ability to receive and

provide feedback on the messages transmitted by

the eyes. Sports vision involves the use of the

visual senses to acquire information about the

playing field (7). The brain processes this

information and generates instructions for the body

to execute specific actions (8).

Appelbaum & Erickson (2018) defined sports

vision as the brain's ability to receive and provide

feedback on the messages transmitted by the eyes.

Sports vision involves the use of the visual senses

to acquire information about the playing field. The

brain processes this information and generates

instructions for the body to execute specific actions

(9). Sports vision training can improve balance and

increase the fixation of Inline Hockey Players (10).

Visual training has emerged as a promising

technique to improve the visual skills of tennis

players. By engaging in repetitive eye exercises

prescribed by sports optometrists, tennis players

can enhance their basic visual functions, such as

visual acuity, depth perception, and peripheral

vision. These visual skills are crucial in tennis, as

they directly impact the athlete's ability to

accurately track the ball, anticipate its movement,

and make split-second decisions on how to

respond. The study by Şenol, Deniz, et al.

compared the visual reaction times (VRT) and

auditory reaction times (ART) of individuals with

different somatotypes, including athletes and

sedentary individuals. The findings indicated that

regular training and participation in sports were

associated with reduced VRT and ART (11).

The significance of sports vision differs from

one sport to another. Tennis, a popular sport

worldwide, has athletes and enthusiasts constantly

aiming for better performance. In tennis, the ball

moves swiftly in various directions during

gameplay. Athletes must rapidly assess the

trajectory and landing spot of the ball with

accuracy. Any approach that can enhance an

athlete's visual system will ultimately improve

their ability. To improve their technical abilities

and excel in competitive sports, athletes constantly

look for ways to enhance their skill sets. Athlete's

visual strategy in the game is related to eye

dynamics, not to head movements (12). In the case

of tennis, a dynamic sport with rapidly changing

ball speeds and directions, players must be able to

make quick and accurate judgments about the

trajectory and landing position of the ball.

Enhancing visual perception is crucial as it directly

impacts an athlete's ability to execute precise

movements swiftly. Afshar, Azam, Jaleh Baqerli,

et al. conducted a study to assess the impact of

visual training on the shooting skills of female

soccer players. They utilized Raven and Gibor's

vision exercises as their research tools and

administered a two-week visual training program

to the participants. The results indicated that the

sports-specific visual exercises led to an

enhancement in the players' shooting skills.

Consequently, any technique or method that can

optimize an athlete's visual system's functioning

will undoubtedly improve accuracy and speed in

executing skilled maneuvers.

Several studies involving baseball, table tennis,

and other sports revealed that excellent dynamic

vision was important in a variety of ball sports and

fast-reacting competitive sports, particularly open-

ended, multiplayer, and confrontational sports. For

example, Huang (13) discovered that visual scene

training greatly improved rookie tennis players'

visual search abilities, cognitive functions, and

specialized sports skills. In previous research, it

has been demonstrated that video training can

enhance the throwing speed of novice baseball

players and improve their ability to predict and

assess the trajectory of baseball (14). Additionally,

the implementation of dynamic vision training is

advantageous in enhancing athlete performance.

Moreover, intervention training focused on sports

vision was conducted with softball athletes,

leading to a relative improvement in their target

capture ability and execution of softball actions

(15, 16). Previous research has extensively

investigated the potential of visual training to

enhance athlete performance. Nevertheless, there

is a notable scarcity of research within the domain

of tennis sports education concerning the influence

of visual training on athletes' technical proficiency

and competitive capabilities.

MATERIALS AND METHODS

Methodology. This research aims to

investigate the impact of visual training on tennis

sports education. Experimental research by

organizing an experimental group and a control

Enhancing Tennis Performance through Visual Training 3

group, each undergoing different training

methods, as shown in Table 3, which is the tennis

skill training schedule. Data recorded for both

groups evaluate the effects of visual training on

improving tennis players' technical proficiency,

reaction speed, and performance in matches.

Through this research, new perspectives and

methods for sports teaching, thereby providing a

scientific basis for more significant advances and

achievements for athletes at the level of skills.

The results of several research scholars (12, 17)

confirm that visual training improves the

effectiveness of tennis sports teachings and

accurately improves the skill levels of tennis.

Individuals who underwent visual training

showed a higher degree of improvement in tennis

skill levels compared to those who did not receive

any training.

Participants. The research involved two

groups of students from the National Chinese

University College of Sports, specializing in

Tennis Education. Initially, 75 specialized

students underwent a basic vision test, and those

with short-sightedness or difficulty seeing distant

objects were excluded. Ultimately, 60 students

with naked eyesight greater than 1.0 were selected

for the research A simple random sampling

method was employed to select 60 student

subjects. The numbers 1 to 47 were assigned to

the 60 students, and each number was written on

a label. These labels were then mixed thoroughly,

and 50 labels were randomly drawn without

replacement. The students corresponding to the

numbers on these 50 labels formed the final

sample. The selected students were divided into

two groups: the control group, consisting of the

first 25 samples, and the experimental group,

consisting of the next 25 samples. Before starting

the experiment, the height and weight data of the

subjects were measured by the height and weight

meter, and the measurement verified that the BMI

of the students was in the normal range.

The premise of visual training is normal

vision. Before the experiment, an E-chart was

used to verify the subjects' normal vision.

According to Table 1, the participants'

background information comprises 25 students

from both the experimental and control groups.

The average age of the students in the

experimental group was 20.47±0.68, and the

average age in the control group was

20.54±0.45. The average height of the

experimental group was 173.75±5.59, and the

average height of the control group was

174.34±576. Body Mass Index (BMI) is a value

calculated by dividing a person's weight by the

square of their height. It primarily reflects the

overall body weight and is used as an indicator

to assess the individual's overall nutritional

status Yajnik and Yudkin (17). The average BMI

of the student in the experimental group was

18.25±1.15, and that of the control group was

17.85±1.85. Therefore, 50 students who

participated in the experimental research had

normal naked-eye vision, were in good physical

condition, and could engage in moderate

physical exercise activities. All participants in

this research volunteered to participate,

everyone signed the experimental notice and can

withdraw at any time.

Table 1. Basic Information of 50 Sample

Age

Height (CM)

Weight (KG)

BMI (W/H

)

Vision

Experimental

Group

20.47±0.68

173.75±5.59

55.39±7.18

18.25±1.15

1.0

Control

Group

20.54±0.45

174.34±5.76

54.87±9.15

17.85±1.85

1.0

Measures. Prior to starting the visual training,

a visual ability test was administered to 50

participants. During this test, the participants'

current levels of visual abilities were evaluated,

and the resulting data were recorded and stored to

gather the raw scores of their existing visual

abilities. To facilitate the visual skills exercises, the

participants engaged with the Sensory Station

Training Application. There were 9 system test

items (as depicted in Figure 1 and Table 3): The

utilization of this well-structured application

ensured a comprehensive and systematic approach

to evaluating and enhancing the participants' visual

capabilities. Firstly, visual clarity pertains to the

ability of the eyes to see objects clearly, serving as

the foundation for any visual task. Contrast

sensitivity marks the initiation of the visual process

and holds vital importance in recognizing objects

and faces. Near-far quickness evaluates the

capacity of individuals to swiftly adjust their focus,

4 Enhancing Tennis Performance through Visual Training

essential for tasks involving motion, spatial

judgment, and timely decision-making. Perception

span denotes the breadth of the visual field,

enabling the efficient gathering of diverse visual

information for quick and accurate processing.

Target capture assesses how rapidly one can

identify and focus on the most pertinent visual data

among available information. Multiple Object

Tracking allows individuals to track and navigate

a target, crucial for collision avoidance when

dealing with multiple moving objects. Reaction

time denotes the speed at which individuals

respond to visual stimuli, a critical aspect of

various activities requiring swift decision-making.

Eye-hand coordination measures the ability to

synchronize eye movement with hand movement,

determining the accuracy of executing actions after

receiving visual information and brain instructions.

In the GO/NO GO test, participants are required to

swiftly touch "Go" targets before they disappear

while avoiding "No-Go" targets, assessing quick

decision-making and rapid response skills.

To compare the differences between the two

groups of data, Cohen's d was chosen in this

research. The formula for effect size (Cohen's d) is

as follows:

Cohen's d=(M1-M2)/SD,

M1 and M2 represent the meaning of the two

sample groups, and SD was the average of the

standard deviations of the two sample groups.

Table 3 illustrates the statistical analysis of

diverse visual abilities within the experimental

and control groups. The calculation of effect

sizes for each test, employing Cohen's d formula,

provided insights into the distinctions between

the data sets of both groups. The effect sizes

observed for all nine visual ability tests in the

two groups were consistently below 0.8,

indicating relatively modest differences in the

data sets for each group. Hence, the findings

showed that there was a similarity in the levels

of visual abilities between the experimental and

control groups before the commencement of

visual training.

Figure 1. Assessment Items in the present study.

Procedures. Both the experimental and

control groups engaged in an eight-week training

program focusing on basic tennis skills. The

training sessions were conducted at the Chinese

University Tennis Course and encompassed

various tennis skill exercises, including

Forehand baseline stroke (FBS), Backhand

Baseline Stroke (BBS), Forehand volleyball

(FV), Backhand volley (BV), Mid-PS, Forecourt

pressure shot (Fore PS), First serve (FS), Second

serve (SS), and other techniques. The index

method test results are displayed in Table 2.

Enhancing Tennis Performance through Visual Training 5

Table 2. Testing Index and Methods

Test index

Test method

Visual

clarity

The participants held a mobile device while standing 3 meters away from a tablet computer for the test.

On the tablet computer, a black Landolt ring appears with a random missing section at the top, bottom,

left, or right, presented in a random sequence on a white background according to predefined acuity

requirements. The participants are required to identify the direction of the missing section and swipe the

mobile device in the corresponding direction.

Contrast

sensitivity

The participants stand 3 meters away from a tablet computer while holding a mobile device. On the screen,

four black circular shapes are displayed, with one of them containing concentric circles of varying shades.

The participants are required to identify the circular shape with the concentric circles and swipe the mobile

device in the corresponding direction.

Target

capture

The participants stand 3 meters away from the large screen while holding a mobile device. Randomly, a

Landolt ring will suddenly appear in one of the four corners of the large screen. The participants are

required to judge the gap direction of the Landolt ring and swipe the mobile device in the corresponding

direction on the mobile device's screen.

Near-far

quickness

The participants stand 3 meters away from a tablet computer while holding a mobile device positioned

40cm from their eyes. During the test, Landolt rings alternately appear on the tablet computer and the

mobile device screen. After determining the direction of the gap in the ring displayed on the tablet screen,

the participants immediately swipe the mobile device in the corresponding direction and quickly identify

the gap direction in the ring on the mobile device screen. They repeat this sequence, switching focus

between the distant and near screens within the 30s.

Multiple

object

tracking

The participants are positioned 60cm away from the tablet computer. On the screen, multiple sets of balls

are displayed, each consisting of two black balls, with one of them briefly turning red and then returning

to black. Subsequently, the balls in each set start rotating randomly in both clockwise and

counterclockwise directions for several rounds before coming to a stop. The participants are required to

identify the ball in each set that initially turned red.

Perception

span

The participants stand 60cm away from the tablet computer, with their eyes aligned horizontally with the

center of the screen. During the test, a certain number of circles appear on the screen. Initially, the circles

form a pattern radiating outward from the center. Some of these circles have a central black dot that appears

in a very brief period. After the black dot disappears, the participants need to identify the circle where the

black dot appeared and click on it.

Eye-hand

coordination

The participants stand 60cm away from the large screen. Randomly, 96 circular rings are displayed in 8

columns on the screen. At the start of the test, a random point appears within one of the circular rings,

and the participants must quickly and accurately click on this point. Once the point is touched, another

point appears at a random location. The goal is to click on as many points as possible within a specified

time. The higher the number of correct clicks, the higher the test score.

GO/NO GO

The participants stand 60cm away from the large screen. On the screen, 96 circular shapes are displayed

in 8 columns, each designed to mimic eye-hand coordination. Within these circular shapes, green or red

dots appear pseudo-randomly. When a green dot appears, the participants need to quickly tap it, and when

a red dot appears, they must refrain from tapping it.

Reaction

time

The participants stand 60cm away from the tablet, with their eye level aligned with the center of the screen.

At the start of the test, two circular shapes appear on the screen. Using their index fingers on both hands,

they lightly touch the center of each circle. Once their fingers are correctly aligned with the centers, the

circular shapes change color to green. Subsequently, the two circular shapes randomly turn red, and the

corresponding index fingers must be swiftly lifted and then pressed down again. The faster this action is

performed, the higher the score.

Table 3. Visual Ability Level of Participants

Experimental

Group

Control

Group

Cohen's d

Visual clarity

17.18±1.32

18.22±1.54

-0.68

Contrast sensitivity

30.07±1.16

29.78±1.02

0.29

Near-far quickness

19.33±3.14

20.46±2.98

-0.37

Perception span

58.94±4.87

59.59±6.12

0.11

Target capture

20.94±1.28

21.19±0.76

0.22

Multiple object tracking

70.82±2.25

69.83±3.87

0.31

Reaction time

14.18±3.61

15.22±2.65

0.29

Eye-hand coordination

50.80±4.87

49.81±4.75

0.21

GO/NO GO

29.28±4.91

30.87±5.27

0.32

6 Enhancing Tennis Performance through Visual Training

The tennis basic skills exercises were carried

out three times a week, with each session lasting

for 90 minutes. To ensure the participant's safety

and well-being, warming-up and relaxation

activities were incorporated at the beginning and

end of each training session to prevent

unnecessary physical injuries. The detailed

training schedule is provided in Table 4.

Table 4 outlines the schedule of skills

exercises to be carried out by all participants in

the research The exercises have been designed to

incorporate a diverse range of techniques,

providing athletes with comprehensive practice

opportunities for each skill. Notably, the

experimental group was required to wear dynamic

vision glasses (Model 2MJ03SE-868, also known

as the Primary Dong Dynamic Vision Trainer).

The purpose of using these glasses was twofold:

first, to heighten the difficulty level for the

experimental group in receiving visual

information, and second, to reduce the frequency

of interruptions in the dynamic visual trainer

blocking the picture surface. As a result, the path

to the ball becomes more inconsistent,

necessitating the experimental group of students

to focus their attention entirely on gathering

visual information. Subsequently, they must

transmit this information to the brain and execute

the corresponding action while practicing their

tennis skills.

Table 4. Schedule of Skills Exercises

Week

Day

Training

Week 1

Monday 2 pm-3:30 pm

FBS+BBS, FS

Wednesday 4 pm-5:30 pm

Mid-PS+ Fore PS, SS

Friday 4 pm-5:30 pm

FV+BV, SS, Footwork training

Week 2

Monday 2 pm-3:30 pm

Mid-PS+ Fore PS, FS

Wednesday 4 pm-5:30 pm

FV+BV, SS

Friday 4 pm-5:30 pm

FBS+BBS, FS, Footwork training

Week 3

Monday 2 pm-3:30 pm

FBS+BBS, FS

Wednesday 4 pm-5:30 pm

Mid-PS+ Fore PS, SS

Friday 4 pm-5:30 pm

FV+BV, SS

Week 4

Monday 2 pm-3:30 pm

Mid-PS+ Fore PS, FS

Wednesday 4 pm-5:30 pm

FV+BV, SS

Friday 4 pm-5:30 pm

FBS+BBS, FS

Week 5

Monday 2 pm-3:30 pm

FBS+BBS, FS, Footwork training

Wednesday 4 pm-5:30 pm

Mid-PS+ Fore PS, SS

Friday 4 pm-5:30 pm

FV+BV, SS

Week 6

Monday 2 pm-3:30 pm

Mid-PS+ Fore PS, FS, Footwork training

Wednesday 4 pm-5:30 pm

FV+BV, SS

Friday 4 pm-5:30 pm

FBS+BBS, FS

Week 7

Monday 2 pm-3:30 pm

FBS+BBS, FS

Wednesday 4 pm-5:30 pm

Mid-PS+ Fore PS, SS

Friday 4 pm-5:30 pm

FV+BV, SS

Week 8

Monday 2 pm-3:30 pm

Mid-PS+ Fore PS, FS

Wednesday 4 pm-5:30 pm

FV+BV, SS, Footwork training

Friday 4 pm-5:30 pm

FBS+BBS, FS

As illustrated in Figure 2, a Feeder (F) was

stationed in the field, handing the ball to the

opposing Player (P) and conducting skills

exercises according to the predetermined

schedule. The primary objective of this exercise

was to ensure that all participants engaged in

tennis skills exercises with an equal amount of

practice and intensity.

The experimental team, in addition to wearing

dynamic vision glasses during tennis ball

practice, also engaged in auxiliary visual skills

exercises utilizing the ZF-Test Attention Capacity

Test. Following the specialized tennis training,

participants moved to the indoor classroom at the

tennis court for attention span training, with each

session lasting 90 seconds per person and was

conducted in two consecutive sessions.

The ZF-test was utilized as a focus range

measurement method and device in this research.

It involved placing multiple LED light keys on a

test panel, arranged in a composition matrix (as

shown in Figure 3). Testers initiated the test by

pressing the start button to initiate the timing.

During the test, when an LED light on the test

board was illuminated, another LED light

immediately lit up simultaneously. If a tester

Enhancing Tennis Performance through Visual Training 7

failed to press the illuminated light within the

predetermined interval time, this instance was not

recorded in the score, and the light switched to

another LED light. This process continued until

the timing was completed. Finally, the test score

was displayed and recorded for subsequent

analysis.

The purpose of this exercise was to enhance

the stability, concentration, and flexibility of

visual attention. Testers were required to

concentrate their attention on specific targets and

quickly switch their focus to other targets, to

improve their perception and responsiveness to

the surrounding environment.

Figure 2. Position of Feeder and Player.

Figure 3. ZF-Test Panel Plot.

Analysis. To assess the students' specialized

tennis skills, this research utilized the International

Tennis Number (ITN) as a measurement tool and

incorporated the collected data into the overall

analysis. The normality distribution was confirmed

by inspecting Skewness, Kurtosis, Kolmogorov-

Smirnov statistics, and Shapiro-Wilk statistics.

The International Tennis Number (ITN) was used

as a measurement instrument in this research to

assess the students' specialized tennis skills, and

the obtained data was incorporated into the overall

analysis. Skewness, Kurtosis, Kolmogorov-

Smirnov, and Shapiro-Wilk statistics were used to

confirm the normality of the distribution. The

visual ability and ITN scores have Kolmogorov-

Smirnov values greater than 0.05. The Z-score for

skewness was calculated as 0.078/0.141=0.55, and

the Z-score for Kurtosis was 0.262/0.281=0.93.

8 Enhancing Tennis Performance through Visual Training

The skewness and kurtosis values were close to

zero, and the Z-scores were within 1.96 standard

deviations of the mean. This showed that the data

gathered in this research for visual ability scores

and ITN scores has a normal distribution.

RESULTS

International Tennis Number (ITN). The

purpose of this research was to explore the impact

of visual training on tennis sports education. To

achieve this, the International Tennis Number

(ITN) was used to quantify the level of tennis

skills among the participants, and the student skill

scores of both the experimental and control

groups were statistically summarized.

Table 5 shows that both groups underwent

statistical data analysis before and after the

experiment. The control group had an average ITN

score of 99.28 before training, with a total score of

2482.00 and a range of 21. After training, the

control group had an average ITN score of 106.76,

with a total score of 2669.00 and a range of 29. The

paired-sample t-test for the control group showed

a value of -7.067 with a significance level of 0.000.

For the experimental group, the average ITN score

before training was 98.48, with a total score of

2462.00 and a range of 21. After training, the

average ITN score increased to 139.28, with a total

score of 3482.00 and a range of 42. The paired

sample t-test for the experimental group showed a

value of -28.199 with a significance level of 0. 000.

After eight weeks of visual training, the

experimental group's average score increased by

40.80 points, significantly improved.

Table 5. ITN of 25 samples

Figure 4 displays a line chart illustrating the

changes in tennis skill levels before and after

visual learning for both the experimental group

and the control group, each consisting of 50

samples.

The Sensory Station Training Application.

The research quantified the participants' tennis

skill levels using the International Tennis Number

(ITN). Subsequently, the skill scores of students

in both the experimental and control groups were

Control

Group

Pro-test

ITN

Post-test

ITN

Effect

Size

Experimental

Group

Pro-test

ITN

Post-test

ITN

Effect

Size

104

139

111

120

129

104

135

105

112

135

100

111

166

103

130

106

101

-5

106

139

101

107

104

141

135

A10

106

B10

147

A11

104

115

B11

148

A12

100

103

B12

141

A13

101

B13

131

A14

112

B14

134

A15

111

110

-1

B15

137

A16

108

B16

102

142

A17

B17

110

146

A18

B18

126

A19

108

114

B19

124

A20

102

111

B20

135

A21

106

123

B21

146

A22

101

B22

135

A23

103

121

B23

135

A24

100

108

B24

108

152

A25

103

B25

103

154

Mean

99.28

106.76

Mean

98.48

139.28

Total

2482.00

2669.00

Total

2462.00

3482.00

Range

Enhancing Tennis Performance through Visual Training 9

subjected to thorough statistical analysis and

summarization.

Table 6 presented the Cohen's d values for

different visual abilities, with Visual clarity,

Contrast sensitivity, Perception span, and

multiple object tracking showed relatively small

Cohen's d values, while the remaining four

indicators exhibit relatively large Cohen's d

values. The assessment of visual abilities

encompassed both dynamic visual acuity and

static visual acuity. The findings from the training

conducted using The Sensory Station Training

Application revealed that there was no significant

improvement in static visual acuity, including

visual clarity (Cohen's d=0.05) and perception

span (Cohen's d=0.08). However, notable

improvements were observed in dynamic visual

acuity, specifically in hand-eye coordination

(Cohen's d=1.26), reaction time (Cohen's d=1.71)

and GO/NO GO (Cohen's d=3.11).

Figure 4. Changes in Tennis Skill Levels.

Table 6. Visual Ability Level of Pre-Post

Experimental

Group Pre-Test

Experimental

Group Post-Test

Cohen's d

Visual clarity

17.18±1.32

17.12±1.92

0.05

Contrast sensitivity

30.07±1.16

30.13±2.06

-0.035

Near-far quickness

19.33±3.14

25.67±3.60

2.03

Perception span

58.94±4.87

59.32±5.05

0.08

Target capture

20.94±1.28

21.16±1.70

0.13

Multiple object tracking

70.82±2.25

72.20±2.85

0.48

Reaction time

14.18±3.61

20.80±4.26

1.71

Eye-hand coordination

50.80±4.87

57.12±5.08

1.26

GO/NO GO

29.28±4.91

44.68±5.15

3.11

10 Enhancing Tennis Performance through Visual Training

DISCUSSION

The objective of this research was to examine

the influence of visual training on tennis physical

education and its potential to enhance tennis skill

levels. Moreover, the researchers sought to

introduce a straightforward and practical visual

training method into university sports courses.

During the 8-week study, the experimental group

students underwent visual ability training,

resulting in notable improvements in their visual

abilities. Additionally, the enhanced tennis skill

levels observed in this group provided further

evidence of the effectiveness of utilizing the

dynamic visual training device.

The visual abilities, including static and dynamic

visual acuity showed different levels of

improvement after the training. In this research

confirmed that when visual training was applied

with high-ball speed and high-focus tasks, athletes

demonstrated significant improvements in tracking

ball trajectories and making precise ball predictions.

Before research, several scholars have obtained

consistent research results in various sports. Visual

training has been shown to significantly enhance

athletic performance in a range of sports, such as

badminton, baseball, table tennis, and football.

Before this research, several studies have been

conducted to investigate the effects of visual

training on athletic performance across these sports.

For instance, Feng (18) examined its impact on

badminton players, while Liu et al. (19) and Millard

(20) focused on baseball players, and Coetzee and

de Waal (21) focused on netball players. Similarly,

Shinkai et al. (10) researched table tennis, and Yang

et al. (22) investigated its applications in football.

Skeet Shooting Athletes have better hand-eye

coordination and visual memory than non-athletes

(23). Collectively, these studies provide compelling

evidence supporting the notion that visual training

can yield significant improvements in athletic

performance in a diverse range of sports. Although

research results demonstrate that visual training can

enhance fundamental tennis skills, the specific skills

and techniques with the most significant

improvement remain unclear.

The continuous advancements in the ability of

visual training devices have raised intriguing

questions about their potential impact on athletes'

physiological structure and subsequent sports

performance. As this critical question remains

unanswered, it was strongly recommended further

research in this field to delve deeper into these

aspects. By investigating the effects of visual training

on athletes' performance, the research adds to the

growing interest in understanding the training method

can contribute to improved sports proficiency.

CONCLUSION

The findings of this study will not only provide

valuable insight and recommendations for athletes

and coaches but will also contribute to the

advancement of tennis education and the

improvement of athletes' competitiveness in the

sport. Furthermore, as technology continues to

evolve and visual training devices become

increasingly popular, the study highlights the

importance of delving deeper into their potential

impact on the physiological aspects of athletes.

Addressing this gap in the research field will help to

better understand the mechanisms by which visual

training enhances sports performance, ultimately

opening up new possibilities for optimizing sports

training and performance in the future.

From a theoretical perspective, this research

can be grounded in the framework of perceptual

motor skills and neural adaptations. Visual

training is thought to improve athletes' perceptual

skills, including the perception of movement

trajectory, speed, and position, which is crucial

for making quick decisions in fast-paced sports

such as tennis. Additionally, neuroadaptive

theory suggests that consistent training and

practice can improve the way the brain processes

specific motor tasks, leading to improved athletic

performance. By examining how visual training

affects perceptual-motor skills and neural

adaptations, a fuller understanding of its impact

on athletes' competitive abilities can be gained.

In conclusion, this study will not only provide

practical advice for athletes and coaches but also

provide theoretical support for the development

of tennis education. In addition, by thoroughly

investigating the physiological effects of visual

training, we can reveal its potential mechanisms

for optimizing sports training and performance

and provide new directions for future sports

science research and sports training.

APPLICABLE REMARKS

 The primary aim of this study was to examine

the impact of visual training on tennis physical

education and skill enhancement, focusing on

the introduction of a practical visual training

method into university sports courses.

 The experimental group of students who

underwent visual ability training during 8 weeks

Enhancing Tennis Performance through Visual Training 11

demonstrated substantial improvements in their

visual abilities, including static and dynamic

visual acuity.

 The study's results provided evidence that

utilizing a dynamic visual training device was

effective in enhancing tennis skill levels,

particularly when high ball speed and high-

focus tasks were employed.

 This research contextualized its findings by

referring to prior studies in various sports like

badminton, baseball, table tennis, and football, all

of which supported the idea that visual training

can significantly improve athletic performance.

 The study also acknowledged the need for

further investigation to determine which

specific skills and techniques benefited the

most from this training.

ACKNOWLEDGMENTS

In preparing this academic manuscript, we

wish to clarify that we have not received financial

backing from any external organization, and there

exists no affiliations or associations that could

potentially influence the content or findings of

this paper.

AUTHORS’ CONTRIBUTIONS

Study concept and design: Zhang Die Die,

Sheiladevi Sukumaran. Acquisition of data:

Sheiladevi Sukumaran. Analysis and interpretation

of data: Zhang Die Die. Drafting the manuscript:

Zhang Die Die, Sheiladevi Sukumaran. Critical

revision of the manuscript for important intellectual

content: Sheiladevi Sukumaran. Statistical analysis:

Sheiladevi Sukumaran. Administrative, technical, and

material support: Zhang Die Die. Study supervision:

Sheiladevi Sukumaran.

CONFLICT OF INTEREST

The authors declare that there are no conflicts

of interest that could have inappropriately.

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