Physiological Regularity and Synchrony in Individuals with Gaming Disorder

Gambling (GD) patients have emotional dysfunction and autonomic nervous dysfunction in everyday life. Studies have shown that the relaxation method by respiratory movement (be) improves cardiopulmonary synchronization, but there are many unknown gd's physiological and synchronization. In this study, the regularity of the pulse waves (PW), the chest wall movement (TWM), and the abdominal wall movement (AWM) were examined using an entryo sampling entropy (HAK). 20 GD patients and 26 healthy contrasts (HC) participated in each stage of start, play, and recovery before and after BES. As a result, both groups are significantly higher_TWMSE_HowlAnd HAK_TWM-AWMHAK before gambling from the baseline_PW-TWMAnd CAC_PW-AWMHAK PW-TWM and CAC PW-AWM during gambling were significantly higher in GDs than HC groups. Both groups are SEs compared to before_TWMAnd CAC_TWM-AWMDuring gambling, especially in the HC group. Online gambling can cause pulse waves, abnormal breathing abnormalities, and asynchronous movements on the hest wall. GD patients who perform long gambling may have lower vascular reaction synchronization compared to HC groups. wall_TWMSE_HowlHCK_TWM-AWMHCK_PW-TWMAnd HAK_PW-AWMMay be useful as a biomarker for evaluating GD risk. These biomarkers may improve the regularity and vascular reaction synchronization of TWM during gambling and alleviate the habit behavior.

Patients with keywords < Span> gambling (GD) have emotional dysfunction and autonomic nervous dysfunction in daily life. Studies have shown that the relaxation method by respiratory movement (be) improves cardiopulmonary synchronization, but there are many unknown gd's physiological and synchronization. In this study, the regularity of the pulse waves (PW), the chest wall movement (TWM), and the abdominal wall movement (AWM) were examined using an entryo sampling entropy (HAK). 20 GD patients and 26 healthy contrasts (HC) participated in each stage of start, play, and recovery before and after BES. As a result, both groups are significantly higher

1. Introduction

TWM

SE

Howl

And HAK

2. Materials and Methods

2.1. Participant

TWM-AWM

HAK before gambling from the baseline

2.2. Questionnaire

PW-TWM

2.3. Physiological Signal

And CAC

2.4. Experimental Procedure

PW-AWM

2.5. Signal Processing

HAK PW-TWM and CAC PW-AWM during gambling were significantly higher in GDs than HC groups. Both groups are SEs compared to before

TWM

And HCV

TWM-AWM

During gambling, especially in the HC group. Online gambling can cause pulse waves, abnormal breathing abnormalities, and asynchronous movements on the hest wall. GD patients who perform long gambling may have lower vascular reaction synchronization compared to HC groups. wall

TWM

SE

scream

HCK

TWM-AWM

CAC

PW-TWM_PWSE_TWMMay be useful as a biomarker for evaluating GD risk. These biomarkers may improve the regularity and vascular reaction synchronization of TWM during gambling and alleviate the habit behavior._HowlTWM_PW-TWMHCK_PW-AWMAnd HAK_TWM-AWMPW-TWM

2.6. Statistical Analysis

And CAC

PW-AWM< 0.05 was considered statistically significant. Statistical analysis was conducted using SPSS version 21.0 (SPSS, Chicago, IL, USA).

3. Results

3.1. Questionnaire

HAK PW-TWM and CAC PW-AWM during gambling were significantly higher in GDs than HC groups. Both groups are SEs compared to before_GDTWM_HCAnd HCV< 0.001) and IGDQ scores (IGDQ_GDTWM-AWM_HCDuring gambling, especially in the HC group. Online gambling can cause pulse waves, abnormal breathing abnormalities, and asynchronous movements on the hest wall. GD patients who perform long gambling may have lower vascular reaction synchronization compared to HC groups. wall< 0.001) of the two groups.

TWM

3.2. Factorial ANOVA

SE_PWSE_TWMSE_HowlHCK_PW-TWMHCK_PW-AWMAnd HAK_TWM-AWMAnalysis of heart rate fluctuations (HRV) in both time and frequency regions is commonly used to measure the degree of fluctuations in the fluctuations of GD patients. At the time of rest, the GD group showed a higher heart rate than a healthy person [6], but the tw o-square average square root range and hig h-frequency HRV were low [7, 8]. In the GD group, the hig h-frequency HRV in the game was significantly lower than when the baseline [9, 10]. Due to a decrease in cognitive control, online games have a higher lo w-frequency/ high frequency ratio in GD patients, and lo w-frequency HRVs are low. These results suggest that the autonomic nervous dysfunction in GD patients, which characterizes either parasympathetic nerve or the advantage of the sympathetic nervous system, is the autonomic nervous dysfunction in GD patients. However, these HRV reactions are linear markers and are not enough to comprehensively investigate psychological and physiological adjustments. < SPAN> If the use of online gambling cannot be properly controlled, it may cause psychological harmful results such as emotional adjustment disorder, decisio n-making bias, attention deficit, inability to control, and impulsive behavior [1] 。 As a result, gamers have abandoned other entertainment activities, are alienated by family and friends, reducing academic performance, and reduced work productivity. U. S. psychologists identified these conditions as signs of online gambling disorders [2], and the World Health Organization announced this as a gambling disorder (GD) contained in categories of impulsive control disorders. [3] The global attention to GD is gradually increasing. The British National Health Service has established a national gambling disorder center for gambling disorders and treating them [4]. In Japan, Kagawa Prefecture has established an ordinance to restrict the use time of online games for minors. [5] GD patients are immersed in the game environment for a long time, and their physiological adjustment patterns may be useful as an objective marker (including linear and no n-linear sides) for GD evaluation and prevention.

Analysis of heart rate fluctuations (HRV) in both time and frequency regions is commonly used to measure the degree of fluctuations in the fluctuations of GD patients. At the time of rest, the GD group showed a higher heart rate than a healthy person [6], but the tw o-square average square root range and hig h-frequency HRV were low [7, 8]. In the GD group, the hig h-frequency HRV in the game was significantly lower than when the baseline [9, 10]. Due to a decrease in cognitive control, online games have a higher lo w-frequency/ high frequency ratio in GD patients, and lo w-frequency HRVs are low. These results suggest that the autonomic nervous dysfunction in GD patients, which characterizes either parasympathetic nerve or the advantage of the sympathetic nervous system, is the autonomic nervous dysfunction in GD patients. However, these HRV reactions are linear markers and are not enough to comprehensively investigate psychological and physiological adjustments. If the use of online gambling is not properly controlled, psychological and psychological harm, such as emotional adjustment disorders, bias for decisio n-making, noticeable defects, inability to control, and impulsive behavior, may cause harmful results. [1] As a result, gamers have abandoned other entertainment activities, are alienated by family and friends, reducing academic performance, and reduced work productivity. U. S. psychologists identified these conditions as signs of online gambling disorders [2], and the World Health Organization announced this as a gambling disorder (GD) contained in categories of impulsive control disorders. [3] The global attention to GD is gradually increasing. The British National Health Service has established a national gambling disorder center for gambling disorders and treating them [4]. In Japan, Kagawa Prefecture has established an ordinance to restrict the use time of online games for minors. [5] GD patients are immersed in the game environment for a long time, and their physiological adjustment patterns may be useful as an objective marker (including linear and no n-linear sides) for GD evaluation and prevention._PW-TWMEntropy, a nonlinear index, indicates physiological irregularity and complexity in patients with psychiatric disorders. Compared with healthy controls (HC), patients with schizophrenia showed irregular coupling of the cardiovascular and respiratory systems [13, 14]. Patients with depressive symptoms showed higher heart rate complexity and lower cardiopulmonary coupling, suggesting central autonomic dysfunction [15]. Cardiovascular and respiratory complexity was also observed during stress, with mentally reduced cardiovascular and respiratory coupling [16], increased changes in peripheral blood volume, blood pressure, and respiratory abnormalities [17], and pulmonary neurological dysfunction. After treatment or respiratory exercise (BE), patients with psychiatric disorders showed increased regularity of peripheral blood volume [18] and enhanced cardiopulmonary synchrony [19]. Since entropy has been used to evaluate normal normality, it is worthwhile to study the entropy of cardiovascular and respiratory responses in patients with GD. Breathing affects and manifests autonomic responses. Negative emotional stimuli have been shown to promote chest wall movement (TWM) [20]. After BE, abdominal wall movement (AWM) was more complicated than TWM [21, 22]. Peripheral vasoconstriction can stabilize blood pressure under artificial ventilation control [23]. In this study, to investigate physiological regularity and synchrony in GD patients, we observed the regularity and vascular reactive coupling of pulse waves, TWM, and AWM during online gaming before and after BES. We also compared the physiological responses of the GD group and the HC group. This study proposes three hypotheses. First, physiological regularity and synchrony will be different at baseline and during gaming. Second, the GD group will show different physiological regularity and synchrony compared with the HC group. Third, physiological regularity and synchrony will be different before and after BES. Long-term maintenance of addictive behaviors may result in pulse wave, respiratory irregularities, and disconnection of vascular responses in subjects with GD. These physiological responses may serve as biomarkers for the assessment and prevention of GD. Furthermore, cognitive behavioral therapy may help improve vascular-response coupling and prevent GD._PW-TWMAnd CAC_PW-AWMThe Subject Protection and Research Ethics Committee at the National Transportation University approved the experimental plan and recruitment of participants. All procedures used in this study were implemented in accordance with the latest version of the Helsinki Declaration based on the excellent clinical practice guidelines. After explaining the experimental method to each participant, we asked the informed outlet paper to be signed._TWMThe respiratory signal was measured by installing a respiratory flap (RISMATE BAND, ADULT, AMBU, BALLERUP, Denmark) with a band for recording TWM and AWM on the chest and abdomen. The pulse wave signal is equipped with a non-invasive blood pressure monitoring device (NIBP-100D, Biopac Inc.) with an adult-sized blood cuff (23-33 cm) on the upper left arm, and medium-sized (medium-sized (23-33 cm)) on the left middle and index finger. 18-24 mm) or large dualtrim (24-28 mm) sensor was installed to measure the change in pulse. To measure respiratory muscle contract [30, 31, 32], and simultaneously collect pulse waves, use DAQCARD (USB 6255, 1 6-bit resolution, NI, Austin, TX, USA). Recorded with a sampling rate of 1000Hz and a range ± 5 bolts. These signals were transferred to PCs (Acer M2610, Intel Core i3-2120, 4GB DDR3-1066, Windows 10 Professional 64-bit, Taipei, Taiwan). < SPAN> The respiratory signal was measured by using a respiratory flap (Rismate Band, Adult, AMBU, Ballerup, Denmark), with a band for recording TWM and AWM on the chest and abdomen, respectively. The pulse wave signal is equipped with a non-invasive blood pressure monitoring device (NIBP-100D, Biopac Inc.) with an adult-sized blood cuff (23-33 cm) on the upper left arm, and medium-sized (medium-sized (23-33 cm)) on the left middle and index finger. 18-24 mm) or large dualtrim (24-28 mm) sensor was installed to measure the change in pulse. To measure respiratory muscle contraction [30, 31, 32], and at the same time collect pulse waves, use DAQCARD (USB 6255, 1 6-bit resolution, NI, Austin, TX, USA). Recorded with a sampling rate of 1000Hz and a range ± 5 bolts. These signals were transferred to PCs (Acer M2610, Intel Core i3-2120, 4GB DDR3-1066, Windows 10 Professional 64-bit, Taipei, Taiwan). The respiratory signal was measured by installing a respiratory flap (RISMATE BAND, ADULT, AMBU, BALLERUP, Denmark) with a band for recording TWM and AWM on the chest and abdomen. The pulse wave signal is equipped with a non-invasive blood pressure monitoring device (NIBP-100D, Biopac Inc.) with an adult-sized blood cuff (23-33 cm) on the upper left arm, and medium-sized (medium-sized (23-33 cm)) on the left middle and index finger. 18-24 mm) or large dualtrim (24-28 mm) sensor was installed to measure the change in pulse. To measure respiratory muscle contract [30, 31, 32], and simultaneously collect pulse waves, use DAQCARD (USB 6255, 1 6-bit resolution, NI, Austin, TX, USA). Recorded with a sampling rate of 1000Hz and a range ± 5 bolts. These signals were transferred to PCs (Acer M2610, Intel Core i3-2120, 4GB DDR3-1066, Windows 10 Professional 64-bit, Taipei, Taiwan).

3.3. The Differences among Experimental Stages

Participants were asked to avoid strenuous exercise and to refrain from consuming caffeinated beverages and foods before the experiment. The ambient temperature was kept between 23 and 27 °C. During the experiment, each participant sat in a reclining chair facing a computer screen with minimal movement. Participants completed the baseline, game 1, game 2, and recovery stages sequentially (Figure 1). In the baseline stage, participants relaxed their bodies and calmed their minds by looking at a gray background image with a black dot in the center for 6 min. In the Game 1 and Game 2 stages, participants played against a KartRider (Nexon Co. Level 4 was more difficult than Level 2. Each stage of the game lasted 7 minutes, during which participants competed against 7 robots. After each stage, participants answered the SAM questionnaire, and in the recovery stage, participants rewatched an image with a gray background and a black dot in the center for 6 minutes to relax their psychophysiological responses. After that, they performed isovolume maneuver training as BE [22, 33]. The procedure of BE is as follows. First, participants performed spontaneous breathing for 24 seconds. BE_TWMSE_HowlAnd HAK_TWM-AWMP i = 1 n S t = 1 n i m f i 2 t,_TWMIn the complexity and synchronization stage, the sample entropy (SE) was used to estimate the irregularity and complexity of one time series [35]:_Howlwhere M represents the dimension of the two time series being compared, and R represents the tolerance level of matching. B M (R) and A M (R) represent the conditional probability that two time series at M and M+1 points match, respectively. A higher SE value indicates that the signal is more irregular and complex. Cross-sample entropy (CSE) is used to estimate the synchrony or similarity between two time series u and m [35] and is written as follows:_TWM-AWMwhere b m (r) u and a m (r) u-μ indicate the conditional probability that patterns Y and μ at m and m+1 points match, respectively. A higher value of CAC indicates asynchrony or discontinuity between two physiological signals. In this study, to reduce individual differences, DC was normalized by subtracting the mean and dividing by the standard deviation. Then, the SE method was applied to evaluate the normality of the normalized DC of pulse wave, TWM and AWM signals._TWMTWM< 0.001), SE_HowlHowl< 0.001), and CSE_TWM-AWMPW-TWM_PWSE_TWMSE_HowlAnd HAK_TWM-AWMP i = 1 n S t = 1 n i m f i 2 t,_PWNo significant differences in gender (χ2 = 0, 12, p = 0, 730) and age (z = -1, 58, p = 0, 114) were observed between the GD and HC groups. There was a significant difference between the CIA (CIAS = 71, 95 ± 6, 02, CIAS = 51, 00 ± 8, 28, z = -5, 77, p = 5. 55 ± 1. 00, IGDQ = 1, 15 ± 1, 05, z = -5, 89, σ Table 1 shows the participants' SAM scores after playing online games. Before BE, the emotional vitality of the GD group in Game 1 was significantly higher than that of Game 2 (z = -2. 250, p = 0. 024), indicating that Game 1 elicited more positive emotions. In addition, the emotional activity of the GD group in Game 1 after BE was significantly lower than that of the HC group (z = -2. 123, p = 0. 034). In addition, the emotional vitality of the HC group in Game 1 (z = -2, 430, p = 0, 015) and arousal (z = -2, 072, p = 0, 038) were significantly higher after BE compared to before BE._TWMSE< 0.001), SE_HowlSE< 0.001), and CSE_TWM-AWMHAK< 0.001); game2 stage: SE_PWPW-TWM_TWMPW-AWM< 0.001), SE_HowlTWM-AWM in Game 1.< 0.001), and CSE_TWM-AWMHAK< 0.001)), but higher CSE_PW-TWMAnd CAC_PW-AWMand CAC_PW-TWMshowed significant differences between the HC and GD groups. No significant physiological differences were observed before and after BES._PW-AWMshowed a significant interaction between experimental stage and BE._PW-TWMTWM_PW-AWMhowl_PW-TWMTWM-AWM_PW-AWMTWM

(Z=-2. 616, p=0. 009), SE_TWMSE_HowlAnd HAK_TWM-AWMP i = 1 n S t = 1 n i m f i 2 t,_TWM(Z = -3. 783, p_Howl(Z = -3. 058, p = 0. 002)). In the HC group, SE< 0.001), and CSE_TWM-AWMTWM< 0.001); game2: SE_TWMTWM< 0.001), SE_HowlTWM-AWM< 0.001), and CSE_TWM-AWMTWM< 0.001)). The HC group also exhibited significantly lower SE_TWMSE_HowlAnd HAK_TWM-AWMP i = 1 n S t = 1 n i m f i 2 t,_TWM(Z=-2. 654, p=0. 008), SE TWM (Z=-4. 045, σ_HowlTWM-AWM (Z=-4. 197, σ< 0.001), and CSE_TWM-AWMHowl< 0.001); game2: SE_TWMPW-AWM< 0.001), SE_HowlTWM-AWM in Game 1.< 0.001), and CSE_TWM-AWMPW-AWM< 0.001)), but higher CSE_PW-AWMAfter BE, the GD group showed higher SE

3.4. The Regularity and Synchrony Difference after BE

TWM_TWMhowl_TWM-AWMTWM-AWM at baseline than during the Game Stage (Game1 Stage: SE

4. Discussion

TWM

(Z=-3. 441, p=0. 001), SE_TWMSE_HowlAnd HAK_TWM-AWM(Z=-3. 501, σ_PW-AWM(Z = -3. 743, σ

TWM-AWM_PW-TWMAnd CAC_PW-AWMhowl

and HAK_TWMAnd CAC_TWM-AWM(Z = -2. 857, p = 0. 004), SE_PW-TWM(Z = -3. 662, σ_PW-AWM(Z = -3. 783, p

TWM

5. Conclusions

(Z = -4. 127, σ_TWMSE_HowlAnd HAK_TWM-AWM(Stimulus: Z = -3. 264, p = 0. 001, Stimulus: Z = -2. 857, p = 0. 004)._PW-AWMTWM_PW-TWMAnd CAC_PW-AWMThis study is the first to use nonlinear methods and indices to examine pulse wave, TWM, and AWM regularity, and vascular-respiratory coupling during online gaming in GD university students. We also observed the effect of BE on these regularities and couplings, and examined the effectiveness of BE in reducing autonomic dysfunction._TWMAnd CAC_TWM-AWMAWM_TWMSE_HowlHCK_TWM-AWMHCK_PW-TWMAnd HAK_PW-AWMIn this study, the hypothesis was that GD patients showed physiological complexity and timing different from the HC group. As a result, university students with GD were compared to HC groups, indicating that the vitality of emotions in the GAME 1st stage was significantly low. Also, HC

Supplementary Materials

PW-TWM

Author Contributions

And hak

Funding

PW-AWM was significantly low. These findings are partially supported our hypothesis, indicating that mathematical stress and exposure to game play increase the number of respiratory and cardiovascular abnormalities compared to rest. [16, 37] The negative image stimulus increased the TWM vs. AWM ratio [20]. The explanation of these findings is that online games with complex hearing and visual stimulation activate the central nervous system and the autonomic nervous system. The central nervous system causes various emotional reactions and cognitive control. [39] GD young adults mainly focus on pursuing the rewards of the game [40], and when they won the game, positive emotions were triggered by anxiety and negative emotions when failed. On the other hand, the autonomic nervous system has a sympathetic nervous system and a parasympathetic nervous system. Online games can activate the sympathetic nervous system and suppress the parasympathetic nervous system, which causes the increase in physiological reactions such as heart rate, breathing, and blood pressure, especially in young GD adults. 。 In addition, cardiopulmonary interaction can suppress blood flow fluctuations and improve the performance of the heart. Compared to the base line, the synchronization of the heart breathing cycle has increased as follows.

Institutional Review Board Statement

In this study, the hypothesis was that GD patients showed physiological complexity and timing different from the HC group. As a result, university students with GD were compared to HC groups, indicating that the vitality of emotions in the GAME 1st stage was significantly low. Also, HC

Data Availability Statement

PW-TWM

Acknowledgments

And hak

Conflicts of Interest

PW-AWM

References

1. The university students who developed GD had significantly higher cardiorespiratory asynchrony compared with the HC group, especially before BE. These findings partially supported our hypothesis. Consistent with the literature, Chang et al. suggested that university students with GD had higher cardiorespiratory asynchrony compared with the HC group [43]. This asynchrony may be due to autonomic dysfunction, and young students with GD may have increased sympathetic activity or suppressed parasympathetic activity [8, 44], leading to irregular cardiorespiratory coordination [43]. Patients with GD often showed emotional dysfunction and were at higher risk of depressive and anxiety symptoms [45, 46]. Patients with psychiatric disorders may have cardiovascular disorders and pulmonary nerve dysfunction, increasing the complexity of cardiac and respiratory interactions [13, 14, 15, 46]. Therefore, we conclude that university students with GD show emotional and autonomic dysfunction and reduced synchronization of vascular-TWM and vascular-AWM. Entropy as a nonlinear index may be useful in questionnaires in assessing GD risk.
2. We hypothesized that normal values ​​would be different before and after BES. In the HC and GD groups, SE
3. TWM
4. and CAC
5. TWM-AWM
6. In the Game1 scene after BE, the HC group showed statistically significant changes. Both groups showed significantly higher HAK
7. PW-TWM
8. or CAC
9. PW-AWM
10. These findings partially support our hypothesis. However, in contrast to previous studies, long-term BE (e. g., ≥15 days) in psychiatric patients significantly increases cardiorespiratory synchrony [19] and decreases heart rate [47]. BE, especially 6 cycles per minute, affects the cerebral cortex, relaxes the body, and enhances vagal activity [48]. Vagal activation enhances parasympathetic activity, increases heart rate variability, brain-heart interaction, and cardiorespiratory coupling [49]. The inconsistency in our findings may be due to individual differences in response to short-term BE, suggesting that long-term BE may be necessary [50, 51]. Also, the small sample size may have influenced the statistical significance, especially in the GD group. Although short-term BE did not significantly improve cardiorespiratory coupling, young students with GD showed a significant increase in total power and low HRV after 10 min of BE [52]. Research suggests that BE can assist cognitive behavioral therapy [53] and meditation [54] to relieve play cravings and manage impulse control. Therefore, we conclude that the intervention time and sample size of BE are important factors for observing play cravings and impulse control.
11. Experimental data was acquired and analyzed under strict IRB approval, but this study has several limits. First, the number of samples was limited, so it was not possible to evaluate the additional gender and the gender gender and the difference between the su b-groups receiving clinical treatment. Second, the psychiatrist has not interviewed the participants. GD risk is only evaluated by CIAS and IGDQ, and these subjective results can cause screening bias. Third, the 1000Hz sampling rate is too expensive and can cause an over sampling effect. Rather, a low sampling rate such as 200Hz should be used. Fourth, most studies are divided into mental illness patients into clinical treatment groups and BE groups [19], or BE and no n-BE groups [47]. This problem should be recruited for more participants and further classify GD patients into a group without lon g-term BE and a group. Fifth, online games may cause a variety of physiological reactions. It is necessary to investigate the impact of other popular games. Sixth, most participants may not have been able to observe the actual psychological and physiological reactions of the GD group because they were unfamiliar with the games of cartriders. The selected game should be close to the game that players usually play. Finally, we have not investigated whether the su b-sampling rate affects the calculation of SE and HAC. [55] Govindan and colleagues have corrected SE algorithms to include the SE algorithms to include a continuous time delay, and improved the evaluation of physiological complexity. In the future, we plan to verify the results of this research using different SE algorithms.
12. In this study, we examined the pulse wave regularity before and after BE, TWM, AWM, blood vessels-breathing coupling for university students in GD in online games. As a result, S. E
13. TWM
14. SE
15. AWM
16. And HAK
17. TWM-AWM
18. Was significantly higher than the base line value, but CSE
19. PW-AWM
20. Was lower than the base line value. Before be BE, the GD group is CSE
21. PW-TWM
22. And CSE
23. PW-AWM
24. Was significantly expensive. Compared to BE before, SE in both HC and GD groups
25. TWM
26. And HAK
27. TWM-AWM
28. In the GAME1 stage, the HC team decreased significantly. These findings suggest that online gambling enhances blood vessels-breathing coupling, but also increases the irregularity of TWM and AWM and asynchronous movements on the hest wall. Due to autonomic nervous dysfunction, college students with GD have shown that blood vessels-breathing coupling during online play compared to HC groups. wall
29. TWM
30. SE
31. scream
32. HC
33. TWM-AWM
34. CAC
35. PW-TWM
36. And HAK
37. PW-AWM
38. Is an objective index that evaluates GD risk. These can be used to improve the synchronization of TWM's regularity and vascular reactivity during gambling, enhance autonomic nervous functions, and reduce poisoning symptoms. However, such a positive effect by be was observed only in the HC group, suggesting that the same effect could be obtained by more training and larger samples in the GD group. 。 In future research, we plan to examine various game types and various SE algorithms in order to more comprehensively understand the physiological adjustment in GD patients.
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41. This study was subsidized by the National Science and Technology Council of Taiwan (MOST 109-2221-E-A49-001-MY3, NSTC 112-2221-E-040- 009). Part of this study was conducted by the initial funding of Nakayama Medical University.
42. The experiment was approved by the CHIAO TUNG NATIONAL UNIVERSITY Research Ethics Committee for the Protection of Human Subjects (NCTU-REC-108-114F).
43. The data announced in this study is available if there is a request from the corresponding author. The data is not open to the public because of the privacy of the subject.
44. Thanks to C.-W. H., L.-Y. C., T.-C. L., W.-Y. C., Y.-H. L.
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Schulz, s; Haueisen, j; Characte r-lecture network for healthy first close relatives in patients with mental division. Neuroscience advances, 2020, 14, 617. [Google School] [CrossRef]._PW-TWMZhao, l .; Entropy-Based and CardioRespiratory Coupling Analysis in Discriminating Different. Sior. [Google Scholar] [CrossRef] [Pubmed]._PW-AWMUdhayakumar, r .; rahman, s.;.;. ;; Macefield, v. g.; Dawood, T. Merer, N; N; N; Karmakar, C. Multimodal PPG measurement of stres s-inducing sympathetic nerve activity. [Google School] [CrossRef]._TWM-AWMToschi-dias, E.? Tobaldini, E.; Solbiati, m.; Costantino, g.; Sanlorenzo, r.; Doria, s.; IRTELLI, f; MENCACCI, C; Improve the heart autonomic nervous control. J. Affect. Disorder. 2017, 214, 74-80. [Google School] [CrossRef]._HowlHuang, R.-H.? HSIAO, T.-C. Internal Entropy: A new adaptive method for measuring the instantaneous complexity of time series. LelationResult internal entropy: A new adaptive method for measuring the instantaneous complexity of time series. [Google School] [CrossRef]._PWHUANG, R.-H; hsiao, T.-C. (1) Evaluation of the impact of a volume manuebatest that uses an unique entropy to evaluate the instantaneous complexity of the thoracic motion pattern. Entropy 2024, 26, 27. [Google School] [CrossRef]._TWMStatista. Distribution of video game users in the United States until June 2024 (by age group). Available Online: https: // www. Statista. Com/FORECASTS/1277856/video-users-age-Market-usa (Accessed August 27, 2024).

King, D. Herd, M. C. E.; Delfabbro, P. H. Tolerance to Internet gambling disorder: A need to increase gambling time or something else? J. Behav. Add. 2017, 6, 525-533. [Google Scholar] [CrossRef]._PWKim, H.; Ha, J.; Chang, W.-D.; Park, W; Kim, L.; Im, C.-H. Detecting gambling cravings in adolescents with Internet gambling disorder using multimodal biosignals. Sensors 2018 , 18 , 102. [Google Scholar] [CrossRef] [PubMed]. Sola-Soler, J.; Cuadros, A. Giraldo, B. F. Cardiopulmonary phase synchronization is increased during certain mental stimuli in healthy subjects. Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, HI, USA, July 18-21, 2018. [Google Scholar] [CrossRef]. Chang, J. S.; Kim, E. Y; Jung, D; Jeong, S. H; Kim, Y.; Roh, M.-S; Ahn, Y. M; Hahm, B.-J. Modified cardiorespiratory coupling in young male adults with excessive online gaming. Biol. Psychol. [Google Scholar] [CrossRef]. Coyne, S. M.; Dyer, W. J.; Densley, R.; Money, N. M.; Day, R.; Physiological markers of pathological video game use in adolescents. J. Adolesc. Health 2015, 56, 307-313. [Google Scholar] [CrossRef] [PubMed]. Yen, J.-Y; Yes, Y.-C.; Wang, P.-W.; Liu, T.-L.; Chen, Y.-Y; Ko, C.-H. Emotional regulation in young adults with Internet gambling disorder. Int. J. Environ. Res. Public Health 2018, 15, 30. [Google Scholar] [CrossRef]. Schulz, S; Haueisen, J; Bär, K.-J.; Voss, A. Altered causal coupling pathways within the central-autonomic network in patients with schizophrenia. Entropy 2019, 21, 733. [Google Scholar] [CrossRef]. Chen, Y.-F; Huang, H.-Y.; Chien, C.-H.; Cheng, J.-F. The effectiveness of diaphragmatic breathing relaxation training on stress reduction. Perspective. Psychiatr. Care 2017, 53, 329-336. [Google Scholar] [CrossRef]._TWMZaccaro, A.; Piarulli, A.; Laurino, M.; Garbella, E; Menicucci, D.;; Neri, B.; Gemignani, A. How breath control can change your life: a systematic review of psychophysiological correlates of slow breathing. In. Buteo. Neurosci. 2018, 12, 353. [Google Scholar] [CrossRef] [PubMed]._HowlMartínez-hernández, v. J.; Dorantes-méndez, g. Analysis of the interaction between cardiovascular and cerebral systems for cognitive stress stimulation. XLVI Mexican Congress on Biomedical Engineering, Villahermosa Tabasco, Mexico, 2-4 NoveMBER 2023. [Google School] [CrossRef]._PW-TWMYoung, K. S; Fusion of theoretical model and treatment approach in the context of Internet gambling disorders: Personal perspective. Forward. Psychol. [Google School] [CrossRef]._PW-AWMGovindan, R. B .; Wilson, J. D .; ESWARAN, H.; Lowery, C. L. L.; PHYS. ATAT. Mech. Appl. 2007, 367, 158-164. [Google Scholar] [CrossRef]._TWM-AWMFigure 1. Experimental procedure.< 0.05 compared BB with the other three stages before BE for the GD group; b p < 0.05 compared BB with the other three stages before BE for the HC group; c p < 0.05 compared BA with the other three stages after BE for the GD group; d p < 0.05 compared BA with the other three stages after BE for HC group; e p < 0.05 compared GD with HC groups; f p < 0.05 compared before BE with after BE.

King, D. Herd, M. C. E.; Delfabbro, P. H. Tolerance to Internet gambling disorder: A need to increase gambling time or something else? J. Behav. Add. 2017, 6, 525-533. [Google Scholar] [CrossRef]._PWKim, H.; Ha, J.; Chang, W.-D.; Park, W; Kim, L.; Im, C.-H. Detecting gambling cravings in adolescents with Internet gambling disorder using multimodal biosignals. Sensors 2018 , 18 , 102. [Google Scholar] [CrossRef] [PubMed]. Sola-Soler, J.; Cuadros, A. Giraldo, B. F. Cardiopulmonary phase synchronization is increased during certain mental stimuli in healthy subjects. Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, HI, USA, July 18-21, 2018. [Google Scholar] [CrossRef]. Chang, J. S.; Kim, E. Y; Jung, D; Jeong, S. H; Kim, Y.; Roh, M.-S; Ahn, Y. M; Hahm, B.-J. Modified cardiorespiratory coupling in young male adults with excessive online gaming. Biol. Psychol. [Google Scholar] [CrossRef]. Coyne, S. M.; Dyer, W. J.; Densley, R.; Money, N. M.; Day, R.; Physiological markers of pathological video game use in adolescents. J. Adolesc. Health 2015, 56, 307-313. [Google Scholar] [CrossRef] [PubMed]. Yen, J.-Y; Yes, Y.-C.; Wang, P.-W.; Liu, T.-L.; Chen, Y.-Y; Ko, C.-H. Emotional regulation in young adults with Internet gambling disorder. Int. J. Environ. Res. Public Health 2018, 15, 30. [Google Scholar] [CrossRef]. Schulz, S; Haueisen, J; Bär, K.-J.; Voss, A. Altered causal coupling pathways within the central-autonomic network in patients with schizophrenia. Entropy 2019, 21, 733. [Google Scholar] [CrossRef]. Chen, Y.-F; Huang, H.-Y.; Chien, C.-H.; Cheng, J.-F. The effectiveness of diaphragmatic breathing relaxation training on stress reduction. Perspective. Psychiatr. Care 2017, 53, 329-336. [Google Scholar] [CrossRef]._TWMZaccaro, A.; Piarulli, A.; Laurino, M.; Garbella, E; Menicucci, D.;; Neri, B.; Gemignani, A. How breath control can change your life: a systematic review of psychophysiological correlates of slow breathing. In. Buteo. Neurosci. 2018, 12, 353. [Google Scholar] [CrossRef] [PubMed]._HowlMartínez-hernández, v. J.; Dorantes-méndez, g. Analysis of the interaction between cardiovascular and cerebral systems for cognitive stress stimulation. XLVI Mexican Congress on Biomedical Engineering, Villahermosa Tabasco, Mexico, 2-4 NoveMBER 2023. [Google School] [CrossRef]._PW-TWMYoung, K. S; Fusion of theoretical model and treatment approach in the context of Internet gambling disorders: Personal perspective. Forward. Psychol. [Google School] [CrossRef]._PW-AWMGovindan, R. B .; Wilson, J. D .; ESWARAN, H.; Lowery, C. L. L.; PHYS. ATAT. Mech. Appl. 2007, 367, 158-164. [Google Scholar] [CrossRef]._TWM-AWMFigure 1. Experimental procedure.< 0.05 compared BB with the other three stages before BE for the GD group; b p < 0.05 compared BB with the other three stages before BE for the HC group; c p < 0.05 compared BA with the other three stages after BE for the GD group; d p < 0.05 compared BA with the other three stages after BE for HC group; e p < 0.05 compared GD with HC groups; f p < 0.05 compared before BE with after BE.

Figure 2. Signal processing framework. AWM, abdominal wall movement. CEEMD, complementary set of empirical decomposition functions. TWM, chest wall movement. HAK, cross sample entropy. SE sample entropy. CAC Figure 2. Signal processing framework. AWM, abdominal wall movement. CEEMD, complementary set of empirical decomposition functions. TWM, chest wall movement. HAK, cross sample entropy. SE sample entropy. CAC

CAC between pulse waves and TWM. CAC		HC	GD
PW-AWM
CAC CAC between pulse waves and AWM	TWM-AWM	CAC between TWM and AWM. wall	Howl
AWM SE. wall	SE of pulse waves. wall	TWM
TWM SE.	TWM-AWM	) (b) SE (SE) of chest wall athletic signal	TWM
AWM SE. wall	Howl	) (d) Cross sample entropy (CSE) (CSE) of pulse waves and chest wall athletic signals
PW-TWM
CAC CAC between pulse waves and AWM	TWM-AWM	) (F) CSE (CSE (CSE	TWM-AWM
AWM SE. wall	Figure 3. B rod graph showing the average and synchronous and synchronization average and standard deviation in the gambling disorder (GD) group and the health contrast (HC) group: (a) Sample entropy (SE) pulse wave signal (SE) pulse wave signal (SE)	) (b) SE (SE) of chest wall athletic signal
TWM SE.	TWM-AWM	AWM	) (d) Cross sample entropy (CSE) (CSE) of pulse waves and chest wall athletic signals
AWM SE. wall	) (e) CSE (CSE) between pulse wave signals and abdominal wall movement signals	PW-AWM

) (F) CSE (CSE (CSE< 0.05 significant difference in valence between game1 and game2 for the GD group; b p < 0.05 significant difference in valence between game1 and game2 for the HC group; c p < 0.05 significant difference in valence between the GD and HC groups; d p < 0.05 significant difference in valence between before and after BEs for the HC group; e p < 0.05 significant difference in arousal between before and after BEs for the HC group.

TWM-AWM TWM-AWM

Table 1. SAM score (average ± standard deviation).	Table 1. SAM score (average ± standard deviation).			BE			Emotion			Before be before being			Game 1			vitality
	6, 04 ± 1, 80 D	F	p	6, 04 ± 1, 80 D	F	p	6, 04 ± 1, 80 D	F	p	6, 04 ± 1, 80 D	F	p	6, 04 ± 1, 80 D	F	p	6, 04 ± 1, 80 D	F	p
SEPW	Strength	5, 77 ± 1, 99	4, 55 ± 2, 16 α	excitement	6, 46 ± 1, 58	7, 05 ± 1, 96		After be	game	Strength	6, 69 ± 1, 72 B, C, D	5, 70 ± 1, 63 γ	Degree of excitement	6, 62 ± 1, 47 E	6, 55 ± 1, 99		Game 2	Strength
SETWM	5, 15 ± 1, 93	Degree of excitement		Degree of excitement	6, 40 ± 1, 93	Be, breathing exercise. GD, gambling disorder; HC, healthy contrast.		After be	Table 2. Distributing analysis of physiological complexity and synchronization.	Parameter	stage	group	Stage x be	Stage x group	BE x Group	p 2	p 2	p 2
SEHowl	The P 2	H p 2		0, 080	5. 46	0, 001 α	0, 009	1, 88	0, 172	0, 01	0, 921	0, 010	0, 080	0, 561	0, 003			0, 23
0, 878PW-TWM	0, 811	TWM	0, 311	0, 009	0, 003	1. 08	0, 299	0, 01		0, 942	0, 049	5. 23	0, 942	0, 049	1. 46	0, 224	0, 001	0, 48
0, 878PW-AWM	0, 618	84, 78	4, 55 ± 2, 16 α	0, 080	0, 003	0, 004	1, 57	0, 211		0, 020	2. 69	0, 046	0, 002	0, 24	0, 867	0, 978	Χακ	PW-TWM
0, 878TWM-AWM	0, 016	0, 004		0, 07	0, 789	0, 860		After be	0, 070	0, 01	0, 704	0, 070	0, 47	0, 702	0, 087	p 2	0, 188	Χακ

PW-AWM_PW-TWM5, 68_PW-AWM0, 002_TWM-AWM0, 787_Howl28, 78_PW0, 011_TWM0, 947< 0.008 after Bonferroni correction (0.05/6); b p < 0.05 after Bonferroni correction; c p < 0.006 after Bonferroni correction (0.05/8).

0, 048

0, 50

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0, 679

0, 031

1. 00

0, 319

CAC

TWM-AWM

0, 569