Study on the improvement of brain cognitive function status by mind-control game training_Journal of Biomedical Engineering

Authors：

 LI Xin ^1,2 , ZHANG Jie ^1,2 , SHI Chunyan ^1,2

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;

Corresponding author：

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

Keywords：

mild cognitive impairment; mind-control game training; electroencephalogram signal; continuous complexity

DOI：

10.7507/1001-5515.201810030

Video：

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This study uses mind-control game training to intervene in patients with mild cognitive impairment to improve their cognitive function. In this study, electroencephalogram (EEG) data of 40 participants were collected before and after two training sessions. The continuous complexity of EEG signals was analyzed to assess the status of cognitive function and explore the effect of mind-control game training on the improvement of cognitive function. The results showed that after two training sessions, the continuous complexity of EEG signal of the subject increased (0.012 44 ± 0.000 29, P < 0.05) and amplitude of curve fluctuation decreased gradually, indicating that with increase of training times, the continuous complexity increased significantly, the cognitive function of brain improved significantly and state was stable. The results of this paper may show that mind-control game training can improve the status of the brain cognitive function, which may provide support and help for the future intervention of cognitive dysfunction.

Citation： LI Xin, ZHANG Jie, SHI Chunyan. Study on the improvement of brain cognitive function status by mind-control game training. Journal of Biomedical Engineering, 2019, 36(3): 364-370, 378. doi: 10.7507/1001-5515.201810030 Copy

1.	Petersen R C, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol, 2001, 58(12): 1985-1992.
2.	Jak A J, Bondi M W, Delano-Wood L, et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. American Journal of Geriatric Psychiatry, 2009, 17(5): 368-375.
3.	Ravaglia G, Forti P, Maioli F, et al. Conversion of mild cognitive impairment to dementia: Predictive role of mild cognitive impairment subtypes and vascular risk factors. Dement Geriatr Cogn Disord, 2006, 21(1): 51-58.
4.	张新. 脑电信号分析在认知功能中的研究. 重庆: 重庆大学, 2010.
5.	Dauwels J, Vialatte F, Cichocki A. Diagnosis of Alzheimer's disease from EEG signals: where are we standing?. Curr Alzheimer Res, 2010, 7(6): 487-505.
6.	李颖洁, 樊飞燕, 陈兴时. 脑电分析在认知研究中的进展. 北京生物医学工程, 2006, 25(3): 321-324.
7.	徐梅松. 重复经颅磁刺激和计算机辅助认知训练对轻度认知功能障碍改善的临床研究. 天津: 天津医科大学, 2014.
8.	吴祥宝, 徐京华. 复杂性与脑功能. 生物物理学报, 1991, 7(1): 103-106.
9.	赵丽, 万柏坤, 綦宏志, 等. 老年性痴呆患者EEG复杂度比较分析. 应用科学学报, 2003, 21(4): 411-415.
10.	万柏坤, 陈骞, 綦宏志. 早老性痴呆的脑电复杂度与近似熵特征分析. 北京生物医学工程, 2005, 24(2): 103-107, 130.
11.	Abásolo D, Hornero R, Gómez C, et al. Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure. Med Eng Phys, 2006, 28(4): 315-322.
12.	Xu Meisong. Complexity analysis of electroencephalogram in patients with Alzheimer's disease and mild cognitive impairment. Chin Med Abstr (Intern Med), 2013, 46(10): 687-691.
13.	Mcbride J C, Zhao Xiaopeng, Munro N B, et al. Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease. Comput Methods Programs Biomed, 2014, 114(2): 153-163.
14.	祝本菊. 基于复杂度分析的阿尔茨海默病、轻度认知功能障碍与正常老年人的脑电研究. 天津: 天津医科大学, 2012.
15.	Mcdonald C R, Gharapetian L, Mcevoy L K, et al. Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment. Neurobiol Aging, 2012, 33(2): 242-253.
16.	王华丽, 袁慧书, 苏敏莹, 等. 轻度认知障碍患者多模态磁共振特征. 中华内科杂志, 2010, 49(8): 680-683.
17.	曹秋云, 江开达, 刘永昌, 等. 阿尔茨海默病与轻度认知功能障碍病人脑正电子发射计算机断层扫描的对照研究. 中华医学杂志, 2002, 82(23): 1616-1616.
18.	洪珊珊, 韩伯军, 王庆广, 等. 遗忘型轻度认知障碍患者额叶体积与额叶纤维结构的对照研究. 中华行为医学与脑科学杂志, 2012, 21(10): 913-915.
19.	Han S D, Arfanakis K, Fleischman D A, et al. Functional connectivity variations in mild cognitive impairment: associations with cognitive function. J Int Neuropsychol Soc, 2012, 18(1): 39-48.
20.	周晶, 倪平, 毛靖. 痴呆症患者非药物干预方法的研究进展. 中华现代护理杂志, 2014, 20(33): 4278-4281.
21.	Spector A, Orrell M, Davies S, et al. Reminiscence therapy for dementia. Cochrane Database Syst Rev, 2000, 3: CD001120.
22.	Rosen A C, Sugiura L, Kramer J H, et al. Cognitive training changes hippocampal function in mild cognitive impairment: a pilot study. Journal of Alzheimers Disease, 2011, 26(3): 349-357.
23.	Savulich G, Piercy T, Fox C, et al. Cognitive training using a novel memory game on an iPad in patients with amnestic mild cognitive impairment(aMCI). Int J Neuropsychopharmacol, 2017, 20(8): 624-633.
24.	陈翠芳. 游戏疗法对轻度老年痴呆患者认知功能及主观幸福感的改善效果. 现代中西医结合杂志, 2012, 21(3): 260-261.
25.	Amjad I, Toor H, Niazi I K, et al. Xbox 360 Kinect Cognitive Games Improve Slowness, Complexity of EEG, and Cognitive Functions in Subjects with Mild Cognitive Impairment: A Randomized Control Trial. Games for Health Journal, 2018, 8(2): 144-152.
26.	Anguera J A, Boccanfuso J, Rintoul J L, et al. Video game training enhances cognitive control in older adults. Nature, 2013, 501(7465): 97-101.
27.	Jirayucharoensak S, Israsena P, Pan-Ngum S, et al. A game-based neurofeedback training system for cognitive rehabilitation in the elderly//International Conference on Pervasive Computing Technologies for Healthcare. Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST), 2014: 278-281.
28.	Liu Y, Sourina O, Hou X. Neurofeedback games to improve cognitive abilities//2014 International Conference on Cyberworlds, Santander, 2014: 161-168.
29.	齐晓英. 基于脑电信号分析的轻度认知障碍评估与干预系统设计. 秦皇岛: 燕山大学, 2017.
30.	Lempel A, Ziv J. On the complexity of finite sequences. IEEE Trans Inf Theory, 1976, 22(1): 75-81.
31.	Kaspar F, Schuster H G. Easily calculable measure for the complexity of spatiotemporal patterns. Phys Rev A, 1987, 36(2): 842-848.

1. Petersen R C, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol, 2001, 58(12): 1985-1992.
2. Jak A J, Bondi M W, Delano-Wood L, et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. American Journal of Geriatric Psychiatry, 2009, 17(5): 368-375.
3. Ravaglia G, Forti P, Maioli F, et al. Conversion of mild cognitive impairment to dementia: Predictive role of mild cognitive impairment subtypes and vascular risk factors. Dement Geriatr Cogn Disord, 2006, 21(1): 51-58.
4. 张新. 脑电信号分析在认知功能中的研究. 重庆: 重庆大学, 2010.
5. Dauwels J, Vialatte F, Cichocki A. Diagnosis of Alzheimer's disease from EEG signals: where are we standing?. Curr Alzheimer Res, 2010, 7(6): 487-505.
6. 李颖洁, 樊飞燕, 陈兴时. 脑电分析在认知研究中的进展. 北京生物医学工程, 2006, 25(3): 321-324.
7. 徐梅松. 重复经颅磁刺激和计算机辅助认知训练对轻度认知功能障碍改善的临床研究. 天津: 天津医科大学, 2014.
8. 吴祥宝, 徐京华. 复杂性与脑功能. 生物物理学报, 1991, 7(1): 103-106.
9. 赵丽, 万柏坤, 綦宏志, 等. 老年性痴呆患者EEG复杂度比较分析. 应用科学学报, 2003, 21(4): 411-415.
10. 万柏坤, 陈骞, 綦宏志. 早老性痴呆的脑电复杂度与近似熵特征分析. 北京生物医学工程, 2005, 24(2): 103-107, 130.
11. Abásolo D, Hornero R, Gómez C, et al. Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure. Med Eng Phys, 2006, 28(4): 315-322.
12. Xu Meisong. Complexity analysis of electroencephalogram in patients with Alzheimer's disease and mild cognitive impairment. Chin Med Abstr (Intern Med), 2013, 46(10): 687-691.
13. Mcbride J C, Zhao Xiaopeng, Munro N B, et al. Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease. Comput Methods Programs Biomed, 2014, 114(2): 153-163.
14. 祝本菊. 基于复杂度分析的阿尔茨海默病、轻度认知功能障碍与正常老年人的脑电研究. 天津: 天津医科大学, 2012.
15. Mcdonald C R, Gharapetian L, Mcevoy L K, et al. Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment. Neurobiol Aging, 2012, 33(2): 242-253.
16. 王华丽, 袁慧书, 苏敏莹, 等. 轻度认知障碍患者多模态磁共振特征. 中华内科杂志, 2010, 49(8): 680-683.
17. 曹秋云, 江开达, 刘永昌, 等. 阿尔茨海默病与轻度认知功能障碍病人脑正电子发射计算机断层扫描的对照研究. 中华医学杂志, 2002, 82(23): 1616-1616.
18. 洪珊珊, 韩伯军, 王庆广, 等. 遗忘型轻度认知障碍患者额叶体积与额叶纤维结构的对照研究. 中华行为医学与脑科学杂志, 2012, 21(10): 913-915.
19. Han S D, Arfanakis K, Fleischman D A, et al. Functional connectivity variations in mild cognitive impairment: associations with cognitive function. J Int Neuropsychol Soc, 2012, 18(1): 39-48.
20. 周晶, 倪平, 毛靖. 痴呆症患者非药物干预方法的研究进展. 中华现代护理杂志, 2014, 20(33): 4278-4281.
21. Spector A, Orrell M, Davies S, et al. Reminiscence therapy for dementia. Cochrane Database Syst Rev, 2000, 3: CD001120.
22. Rosen A C, Sugiura L, Kramer J H, et al. Cognitive training changes hippocampal function in mild cognitive impairment: a pilot study. Journal of Alzheimers Disease, 2011, 26(3): 349-357.
23. Savulich G, Piercy T, Fox C, et al. Cognitive training using a novel memory game on an iPad in patients with amnestic mild cognitive impairment(aMCI). Int J Neuropsychopharmacol, 2017, 20(8): 624-633.
24. 陈翠芳. 游戏疗法对轻度老年痴呆患者认知功能及主观幸福感的改善效果. 现代中西医结合杂志, 2012, 21(3): 260-261.
25. Amjad I, Toor H, Niazi I K, et al. Xbox 360 Kinect Cognitive Games Improve Slowness, Complexity of EEG, and Cognitive Functions in Subjects with Mild Cognitive Impairment: A Randomized Control Trial. Games for Health Journal, 2018, 8(2): 144-152.
26. Anguera J A, Boccanfuso J, Rintoul J L, et al. Video game training enhances cognitive control in older adults. Nature, 2013, 501(7465): 97-101.
27. Jirayucharoensak S, Israsena P, Pan-Ngum S, et al. A game-based neurofeedback training system for cognitive rehabilitation in the elderly//International Conference on Pervasive Computing Technologies for Healthcare. Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST), 2014: 278-281.
28. Liu Y, Sourina O, Hou X. Neurofeedback games to improve cognitive abilities//2014 International Conference on Cyberworlds, Santander, 2014: 161-168.
29. 齐晓英. 基于脑电信号分析的轻度认知障碍评估与干预系统设计. 秦皇岛: 燕山大学, 2017.
30. Lempel A, Ziv J. On the complexity of finite sequences. IEEE Trans Inf Theory, 1976, 22(1): 75-81.
31. Kaspar F, Schuster H G. Easily calculable measure for the complexity of spatiotemporal patterns. Phys Rev A, 1987, 36(2): 842-848.

Journal of Biomedical Engineering

Study on the improvement of brain cognitive function status by mind-control game training

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