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.	張新. 腦電信號分析在認知功能中的研究. 重慶: 重慶大學, 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.	李穎潔, 樊飛燕, 陳興時. 腦電分析在認知研究中的進展. 北京生物醫學工程, 2006, 25(3): 321-324.
7.	徐梅松. 重復經顱磁刺激和計算機輔助認知訓練對輕度認知功能障礙改善的臨床研究. 天津: 天津醫科大學, 2014.
8.	吳祥寶, 徐京華. 復雜性與腦功能. 生物物理學報, 1991, 7(1): 103-106.
9.	趙麗, 萬柏坤, 綦宏志, 等. 老年性癡呆患者EEG復雜度比較分析. 應用科學學報, 2003, 21(4): 411-415.
10.	萬柏坤, 陳騫, 綦宏志. 早老性癡呆的腦電復雜度與近似熵特征分析. 北京生物醫學工程, 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. 基于復雜度分析的阿爾茨海默病、輕度認知功能障礙與正常老年人的腦電研究. 天津: 天津醫科大學, 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.	王華麗, 袁慧書, 蘇敏瑩, 等. 輕度認知障礙患者多模態磁共振特征. 中華內科雜志, 2010, 49(8): 680-683.
17.	曹秋云, 江開達, 劉永昌, 等. 阿爾茨海默病與輕度認知功能障礙病人腦正電子發射計算機斷層掃描的對照研究. 中華醫學雜志, 2002, 82(23): 1616-1616.
18.	洪珊珊, 韓伯軍, 王慶廣, 等. 遺忘型輕度認知障礙患者額葉體積與額葉纖維結構的對照研究. 中華行為醫學與腦科學雜志, 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. 癡呆癥患者非藥物干預方法的研究進展. 中華現代護理雜志, 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.	陳翠芳. 游戲療法對輕度老年癡呆患者認知功能及主觀幸福感的改善效果. 現代中西醫結合雜志, 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.	齊曉英. 基于腦電信號分析的輕度認知障礙評估與干預系統設計. 秦皇島: 燕山大學, 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. 張新. 腦電信號分析在認知功能中的研究. 重慶: 重慶大學, 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. 李穎潔, 樊飛燕, 陳興時. 腦電分析在認知研究中的進展. 北京生物醫學工程, 2006, 25(3): 321-324.
7. 徐梅松. 重復經顱磁刺激和計算機輔助認知訓練對輕度認知功能障礙改善的臨床研究. 天津: 天津醫科大學, 2014.
8. 吳祥寶, 徐京華. 復雜性與腦功能. 生物物理學報, 1991, 7(1): 103-106.
9. 趙麗, 萬柏坤, 綦宏志, 等. 老年性癡呆患者EEG復雜度比較分析. 應用科學學報, 2003, 21(4): 411-415.
10. 萬柏坤, 陳騫, 綦宏志. 早老性癡呆的腦電復雜度與近似熵特征分析. 北京生物醫學工程, 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. 基于復雜度分析的阿爾茨海默病、輕度認知功能障礙與正常老年人的腦電研究. 天津: 天津醫科大學, 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. 王華麗, 袁慧書, 蘇敏瑩, 等. 輕度認知障礙患者多模態磁共振特征. 中華內科雜志, 2010, 49(8): 680-683.
17. 曹秋云, 江開達, 劉永昌, 等. 阿爾茨海默病與輕度認知功能障礙病人腦正電子發射計算機斷層掃描的對照研究. 中華醫學雜志, 2002, 82(23): 1616-1616.
18. 洪珊珊, 韓伯軍, 王慶廣, 等. 遺忘型輕度認知障礙患者額葉體積與額葉纖維結構的對照研究. 中華行為醫學與腦科學雜志, 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. 癡呆癥患者非藥物干預方法的研究進展. 中華現代護理雜志, 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. 陳翠芳. 游戲療法對輕度老年癡呆患者認知功能及主觀幸福感的改善效果. 現代中西醫結合雜志, 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. 齊曉英. 基于腦電信號分析的輕度認知障礙評估與干預系統設計. 秦皇島: 燕山大學, 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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