Improving college students sub-threshold depression by music neurofeedback_Journal of Biomedical Engineering

Authors：

 LI Xin ^1,2 , DING Xinyue ^1,2 , CUI Wei ³ , SONG Xinwang ^1,2 , SHI Chunyan ^1,2 , LI Xiangdong ⁴

1. Institute of Biomedical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, P.R.China;
2. Measurement Technology and Instrumentation Key Lab of Hebei Province, Qinhuangdao, Hebei 066004, P.R.China;
3. HanDan Central Hospital, Handan, Hebei 056000, P.R.China;
4. HUISIANPU Medical Instruments Co., Ltd., Qinhuangdao, Hebei 066000, P.R.China;

Corresponding author：

LI Xin, Email: yddylixin@ysu.edu.cn

Keywords：

sub-threshold depression; music neurofeedback stimulation; relative power; sample entropy; complexity

DOI：

10.7507/1001-5515.201904012

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Sub-threshold depression refers to a psychological sub-health state that fails to meet the diagnostic criteria for depression. Appropriate intervention can improve the state and reduce the risks of disease development. In this paper, we focus on music neurofeedback stimulation improving emotional state of sub-threshold depression college students.Twenty-four college students with sub-threshold depression participated in the experiment, 16 of whom were members of the experimental group. Decompression music based on spectrum classification was applied to 16 experimental group participants for 10 min/d music neural feedback stimulation with a period of 14 days, and no stimulation was applied to 8 control group participants. Three feature parameters of electroencephalogram (EEG) relative power, sample entropy and complexity were extracted for analysis. The results showed that the relative power of α、β and θ rhythm increased, while δ rhythm decreased after the stimulation of musical nerofeedback in the experimental group. The sample entropy and complexity were significantly increased after the stimulation, and the differences of these parameters pre and post stimulation were statistically significant (P < 0.05), while the differences of all feature parameters in the control group were not statistically significant. In the experimental group, the scores of self-rating depression scale(SDS) decreased after the stimulation of musical nerofeedback, indicating that the depression was improved. The result of this study showed that music neurofeedback stimulation can improve sub-threshold depression and may provides an effective new way for college students to self-regulation of emotion.

Citation： LI Xin, DING Xinyue, CUI Wei, SONG Xinwang, SHI Chunyan, LI Xiangdong. Improving college students sub-threshold depression by music neurofeedback. Journal of Biomedical Engineering, 2020, 37(1): 54-60. doi: 10.7507/1001-5515.201904012 Copy

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12.	Mumtaz W, Malik A S, Yasin M A M, et al. Review on EEG and ERP predictive biomarkers for major depressive disorder. Biomedical Signal Processing and Control, 2015, 22: 85-98.
13.	Begić D, Popović-Knapić V, Grubišin J, et al. Quantitative electroencephalography in schizophrenia and depression. Psychiatr Danub, 2011, 23(4): 355-362.
14.	Knott V, Mahoney C, Kennedy S, et al. EEG power, frequency, asymmetry and coherence in male depression. Psychiatry Res, 2001, 106(2): 123-140.
15.	Hosseini S A, Naghibi-Sistani M B. Emotion recognition method using entropy analysis of EEG signals. International Journal of Image Graphics & Signal Processing, 2011, 3(5): 30-36.
16.	van Drongelen W, Nayak S, Frim D M, et al. Seizure anticipation in pediatric epilepsy: use of Kolmogorov entropy. Pediatr Neurol, 2003, 29(3): 207-213.
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19.	Azarnoosh M, Motie Nasrabadi A, Mohammadi M R, et al. Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: symbolic dynamics. Chaos Solitons Fractals, 2011, 44(12): 1054-1062.
20.	Conrad C, Niess H, Jauch K W, et al. Overture for growth hormone: requiem for interleukin-6?. Crit Care Med, 2007, 35(12): 2709-2713.
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22.	Fachner J, Gold C, Erkkilä J. Music therapy modulates fronto-temporal activity in rest-EEG in depressed clients. Brain Topogr, 2013, 26(2): 338-354.
23.	钟盈花, 龚玲, 闻毅. 正性音乐刺激联合舍曲林治疗对首发抑郁症大学生焦虑抑郁情绪及生活质量的影响. 南昌大学学报: 医学版, 2017, 57(5): 45-49.
24.	Bressan R A, Crippa J A. The role of dopamine in reward and pleasure behaviour--review of data from preclinical research. Acta Psychiatr Scand Suppl, 2005, 111(427): 14-21.
25.	Takayama Y, Miura E, Miura K, et al. Condition of depressive symptoms among Japanese dental students. Odontology, 2011, 99(2): 179-187.
26.	李园园. 冠心病经皮冠状动脉介入术后合并抑郁情绪的临床调查. 延安: 延安大学, 2016.
27.	张娟娟, 刘小榕, 陈美芬. 积极心理学团体心理辅导对轻度抑郁大学新生的干预研究. 课程教育研究, 2016, 26: 13.
28.	毛峡, 朱刚. 1/f 波动数据的产生及其舒适感分析. 北京航空航天大学学报, 2002, 28(3): 253-256.
29.	刘慧, 和卫星, 陈晓平. 生物时间序列的近似熵和样本熵方法比较. 仪器仪表学报, 2004, 25(S1): 806-807, 812.
30.	Sun minghou, Zhao Qinglin, Hu Bin, et al. The research of depression based on power spectrum// International Conference on Brain Informatics and Health (BIH), 2015, 9250: 401-409.
31.	Yum M K, Jung K Y, Kang H C, et al. Effect of a ketogenic diet on EEG: analysis of sample entropy. Seizure, 2008, 17(6): 561-566.
32.	Zhu Xueling, Wang Xiang, Xiao Jing, et al. Altered white matter integrity in first-episode, treatment-naive young adults with major depressive disorder: a tract-based spatial statistics study. Brain Res, 2011, 1369: 223-229.
33.	何梦璇. 丹栀逍遥散治疗轻中度抑郁症的疗效观察及机制研究. 名医, 2019(02): 260.

1. Drevets W C, Price J L, Furey M L. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct, 2008, 213(1/2): 93-118.
2. Holden C. Global survey examines impact of depression. Science, 2000, 288(7): 39-40.
3. Reddy M S. Depression: the disorder and the burden. India J Psychol Med, 2010, 32(1): 1-2.
4. 胡月, 黄海, 张雨晴, 等. 大学生手机依赖与认知失败的关系: 负性情绪的中介作用. 中国临床心理学杂志, 2017, 25(6): 1088-1092.
5. 胡广富, 程献, 颜春辉, 等. 大学生手机成瘾对抑郁的影响: 情绪调节自我效能感的中介作用. 宁波大学学报: 教育科学版, 2019, 41(01): 13-19.
6. Ibrahim A K, Kelly S J, Adams C E, et al. A systematic review of studies of depression prevalence in university students. Journal of Psychiatric Research, 2013, 47(3): 391-400.
7. 刘微波. 首发抑郁症患者情绪调控网络内功能连接的静息态功能磁共振研究. 杭州: 浙江大学, 2014.
8. Nestler E J, Carlezon W A Jr. The mesolimbic dopamine reward circuit in depression. Biol Psychiatry, 2006, 59(12): 1151-1159.
9. 齐倩蕊. 抑郁症患者大脑结构差异及脑网络动力学研究. 大连: 大连海事大学, 2018.
10. 卢钟娇, 贾志云, 黄晓琦, 等. 抑郁症自杀行为的神经生物学研究进展. 生物医学工程学杂志, 2011, 28(4): 834-838.
11. 魏玲, 李颖洁, 唐莺莹, 等. 抑郁症情绪加工过程中的脑功能连通性分析. 生物医学工程学杂志, 2010, 27(5): 961-967.
12. Mumtaz W, Malik A S, Yasin M A M, et al. Review on EEG and ERP predictive biomarkers for major depressive disorder. Biomedical Signal Processing and Control, 2015, 22: 85-98.
13. Begić D, Popović-Knapić V, Grubišin J, et al. Quantitative electroencephalography in schizophrenia and depression. Psychiatr Danub, 2011, 23(4): 355-362.
14. Knott V, Mahoney C, Kennedy S, et al. EEG power, frequency, asymmetry and coherence in male depression. Psychiatry Res, 2001, 106(2): 123-140.
15. Hosseini S A, Naghibi-Sistani M B. Emotion recognition method using entropy analysis of EEG signals. International Journal of Image Graphics & Signal Processing, 2011, 3(5): 30-36.
16. van Drongelen W, Nayak S, Frim D M, et al. Seizure anticipation in pediatric epilepsy: use of Kolmogorov entropy. Pediatr Neurol, 2003, 29(3): 207-213.
17. Puthankattil S D, Joseph P K. Analysis of EEG signals using wavelet entropy and approximate entropy: a case study on depression patients. International Scholarly and Scientific Research & Innovation, 2004, 8(7): 420-424.
18. 朱嘉诚, 李颖洁, 曹丹, 等. 抑郁症患者正性情绪加工脑电样本熵异常研究. 信号处理, 2018, 34(08): 943-951.
19. Azarnoosh M, Motie Nasrabadi A, Mohammadi M R, et al. Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: symbolic dynamics. Chaos Solitons Fractals, 2011, 44(12): 1054-1062.
20. Conrad C, Niess H, Jauch K W, et al. Overture for growth hormone: requiem for interleukin-6?. Crit Care Med, 2007, 35(12): 2709-2713.
21. 郭蓉. 大学生抑郁症的心理音乐治疗. 教育评论, 2007(5): 82-83.
22. Fachner J, Gold C, Erkkilä J. Music therapy modulates fronto-temporal activity in rest-EEG in depressed clients. Brain Topogr, 2013, 26(2): 338-354.
23. 钟盈花, 龚玲, 闻毅. 正性音乐刺激联合舍曲林治疗对首发抑郁症大学生焦虑抑郁情绪及生活质量的影响. 南昌大学学报: 医学版, 2017, 57(5): 45-49.
24. Bressan R A, Crippa J A. The role of dopamine in reward and pleasure behaviour--review of data from preclinical research. Acta Psychiatr Scand Suppl, 2005, 111(427): 14-21.
25. Takayama Y, Miura E, Miura K, et al. Condition of depressive symptoms among Japanese dental students. Odontology, 2011, 99(2): 179-187.
26. 李园园. 冠心病经皮冠状动脉介入术后合并抑郁情绪的临床调查. 延安: 延安大学, 2016.
27. 张娟娟, 刘小榕, 陈美芬. 积极心理学团体心理辅导对轻度抑郁大学新生的干预研究. 课程教育研究, 2016, 26: 13.
28. 毛峡, 朱刚. 1/f 波动数据的产生及其舒适感分析. 北京航空航天大学学报, 2002, 28(3): 253-256.
29. 刘慧, 和卫星, 陈晓平. 生物时间序列的近似熵和样本熵方法比较. 仪器仪表学报, 2004, 25(S1): 806-807, 812.
30. Sun minghou, Zhao Qinglin, Hu Bin, et al. The research of depression based on power spectrum// International Conference on Brain Informatics and Health (BIH), 2015, 9250: 401-409.
31. Yum M K, Jung K Y, Kang H C, et al. Effect of a ketogenic diet on EEG: analysis of sample entropy. Seizure, 2008, 17(6): 561-566.
32. Zhu Xueling, Wang Xiang, Xiao Jing, et al. Altered white matter integrity in first-episode, treatment-naive young adults with major depressive disorder: a tract-based spatial statistics study. Brain Res, 2011, 1369: 223-229.
33. 何梦璇. 丹栀逍遥散治疗轻中度抑郁症的疗效观察及机制研究. 名医, 2019(02): 260.

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Improving college students sub-threshold depression by music neurofeedback

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