Applications, industrial transformation and commercial value of brain-computer interface technology_Journal of Biomedical Engineering

Authors：

LUO Jiangong ^1,2 , DING Peng ^1,2 , GONG Anmin ³ , TIAN Guixin ^1,2 , XU Haotian ^1,2 , ZHAO Lei ⁴ ,  FU Yunfa ^1,2

1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China;
2. Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China;
3. College of Information Engineering, Engineering University of PAP, Xi’an 710000, P. R. China;
4. Faculty of Science, Kunming University of Science and Technology, Kunming 650500, P. R. China;

Corresponding?author：

Keywords：

Brain computer interface; The Copernican revolution of brain computer interface; Medical and non-medical application; Industrial transformation; Commercial value

DOI：

10.7507/1001-5515.202108068

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Brain-computer interface (BCI) is a revolutionary human-computer interaction technology, which includes both BCI that can output instructions directly from the brain to external devices or machines without relying on the peripheral nerve and muscle system, and BCI that bypasses the peripheral nerve and muscle system and inputs electrical, magnetic, acoustic and optical stimuli or neural feedback directly to the brain from external devices or machines. With the development of BCI technology, it has potential application not only in medical field, but also in non-medical fields, such as education, military, finance, entertainment, smart home and so on. At present, there is little literature on the relevant application of BCI technology, the current situation of BCI industrialization at home and abroad and its commercial value. Therefore, this paper expounds and discusses the above contents, which are expected to provide valuable information for the public and organizations, BCI researchers, BCI industry translators and salespeople, and improve the cognitive level of BCI technology, further promote the application and industrial transformation of BCI technology and enhance the commercial value of BCI, so as to serve mankind better.

Citation： LUO Jiangong, DING Peng, GONG Anmin, TIAN Guixin, XU Haotian, ZHAO Lei, FU Yunfa. Applications, industrial transformation and commercial value of brain-computer interface technology. Journal of Biomedical Engineering, 2022, 39(2): 405-415. doi: 10.7507/1001-5515.202108068 Copy

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2.	Graimann B, Allison B, Pfurtscheller G. Brain-computer interfaces: revolutionizing human-computer interaction. Springer Publishing Company, 2013.
3.	伏云發, 龔安民, 陳超, 等. 面向實用的腦-機接口: 縮小研究與實際應用之間的差距. 北京: 科學出版社, 2022.
4.	Allison B Z, Dunne S, Leeb R, et al. Towards practical brain-computer interfaces: bridging the gap from research to real-world applications. Berlin : Springer Publishing Company, 2012.
5.	Barinaga M. Turning thoughts into actions. Science, 1999, 286(5441): 888-890.
6.	Wolpaw J R, Birbaumer N, Heetderks W J, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng, 2000, 8(2): 164-173.
7.	Stephen H. Scott. Converting thoughts into action. Nature, 2006, 442: 141-142.
8.	伏云發, 丁鵬, 羅建功, 等. 腦-計算機接口. 國防工業出版社, 北京, 2021.
9.	Douibi K, Le Bars S, Lemontey A, et al. Toward EEG-based BCI applications for industry 4. 0: challenges and possible applications. Front Hum Neurosci, 2021, 15: 705064.
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11.	Mudgal S K, Sharma S K, Chaturvedi J, et al. Brain computer interface advancement in neurosciences: applications and issues. Interdisciplinary Neurosurgery, 2020: 20.
12.	李靜雯, 王秀梅. 腦機接口技術在醫療領域的應用. 信息通信技術與政策, 2021, 2021(2): 87-91.
13.	陳小剛, 楊晨, 陳菁菁, 等. 腦機接口技術發展新趨勢——基于2019-2020年研究進展. 科技導報, 2021, 39(19): 56-65.
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16.	Wolpaw J R, Millán J, Ramsey N F. Brain-computer interfaces: definitions and principles. Handb Clin Neurol, 2020, 168: 15-23.
17.	龔瑜, 藺俊斌, 郝赤子, 等. 腦機接口在脊髓損傷康復中的應用進. 中國康復醫學雜志, 2020, 35(6): 744-748.
18.	Matarasso A K, Rieke J D, White K, et al. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): training of volitional wrist extension after stroke, a case series pilot study. PLoS One, 2021, 16(5): e0250431.
19.	Neto L L, Constantini A C, Chun R. Communication vulnerable in patients with amyotrophic lateral sclerosis: a systematic review. Neuro Rehabilitation, 2017, 40(4): 561-568.
20.	Lee D Y, Lee M, Lee S W. Decoding imagined speech based on deep metric learning for intuitive BCI communication. IEEE Trans Neural Syst Rehabil Eng, 2021, 29: 1363-1374.
21.	Jamil N, Belkacem A, Ouhbi S, et al. Noninvasive electroencephalography equipment for assistive, adaptive, and rehabilitative brain-computer interfaces: a systematic literature review. Sensors (Basel), 2021, 21(14): 4754.
22.	蔣麗勇, 劉術, 刁天喜, 等. 腦機接口技術進展及潛在軍事醫學應用. 軍事醫學, 2021, 45(10): 780-785.
23.	柯清超, 王朋利. 腦機接口技術教育應用的研究進展. 中國電化教育, 2019, 2019(10): 14-22.
24.	Mehta A. Applying brain computer interface technology for playing games. International Journal of Engineering and Management Research, 2021, 11(3): 213-220.
25.	王繼龍. 多類運動想象腦電信號識別方法研究及其在AR場景中的應用. 長春: 東北電力大學, 2021.
26.	堯德中. 腦-機接口: 如何從實驗室到現實場景?. 生物醫學工程學雜志, 2021, 38(3): 405-408.
27.	Veena N, Mahalakshmi S, Guruprasad S. Consumer BCI devices-applications and challenges. Advanced Aspects of Engineering Research, 2021, 11: 81-91.
28.	呂曉彤, 丁鵬, 李思語, 等. 腦機接口人因工程及應用:以人為中心的腦機接口設計和評價方法. 生物醫學工程學雜志, 2021, 38(2): 210-223.
29.	宋艷, 劉峰, 黃夢璇, 等. 新興技術產品商業化過程中的“峽谷”跨越研究——基于技術采用生命周期理論視角. 研究與發展管理, 2013, 25(4): 76-86.
30.	Lee M H, Kwon O Y, Kim Y J, et al. EEG dataset and openBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy. Gigascience, 2019, 8(5): giz002.
31.	Zhang Y. Invasive BCI and noninvasive BCI with VR/AR technology//International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021). SPIE, 2021, 12153: 186-192.
32.	Feng J K, Jin J, Daly I, et al. An optimized channel selection method based on multifrequency CSP-rank for motor imagery-based BCI system. Comput Intell Neurosci, 2019, 2019: 8068357.
33.	Leuthardt E C, Moran D W, Mullen T R. Defining surgical terminology and risk for brain computer interface technologies. Front Neurosci, 2021, 15: 599549.
34.	中國人工智能產業發展聯盟. 腦機接口技術在醫療健康領域應用白皮書. 北京: 中國人工智能產業發展聯盟, 2021.
35.	中國電子技術標準化研究院. 腦機接口標準化白皮書. 北京: 中國電子技術標準化研究院, 2021.
36.	Thompson M C. Critiquing the concept of BCI illiteracy. Sci Eng Ethics, 2019, 25(4): 1217-1233.
37.	Gilbert F, Cook M, O'brien T, et al. Embodiment and estrangement: results from a first-in-human "intelligent BCI" trial. Sci Eng Ethics, 2019, 25(1): 83-96.
38.	Rainey S, Maslen H, Savulescu J. When thinking is doing: responsibility for BCI-mediated action. AJOB Neurosci, 2020, 11(1): 46-58.
39.	Jawad A J. Bioethics of medical devices based on brain computer interfaces (BCI). J Clinic Res Bioeth, 2021, 12(S8): 1000003.
40.	中國信息通信研究院. 腦機接口技術創新與產業發展研究報告. 北京: 中國信息通信研究院, 2021.

1. 伏云發, 郭衍龍, 張夏冰, 等. 腦-機接口--革命性的人機交互. 北京: 國防工業出版社, 2020.
2. Graimann B, Allison B, Pfurtscheller G. Brain-computer interfaces: revolutionizing human-computer interaction. Springer Publishing Company, 2013.
3. 伏云發, 龔安民, 陳超, 等. 面向實用的腦-機接口: 縮小研究與實際應用之間的差距. 北京: 科學出版社, 2022.
4. Allison B Z, Dunne S, Leeb R, et al. Towards practical brain-computer interfaces: bridging the gap from research to real-world applications. Berlin : Springer Publishing Company, 2012.
5. Barinaga M. Turning thoughts into actions. Science, 1999, 286(5441): 888-890.
6. Wolpaw J R, Birbaumer N, Heetderks W J, et al. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng, 2000, 8(2): 164-173.
7. Stephen H. Scott. Converting thoughts into action. Nature, 2006, 442: 141-142.
8. 伏云發, 丁鵬, 羅建功, 等. 腦-計算機接口. 國防工業出版社, 北京, 2021.
9. Douibi K, Le Bars S, Lemontey A, et al. Toward EEG-based BCI applications for industry 4. 0: challenges and possible applications. Front Hum Neurosci, 2021, 15: 705064.
10. Guger C, Prabhakaran V, Spataro R, et al. Editorial: breakthrough BCI applications in medicine. Front Neurosci, 2020, 14: 598247.
11. Mudgal S K, Sharma S K, Chaturvedi J, et al. Brain computer interface advancement in neurosciences: applications and issues. Interdisciplinary Neurosurgery, 2020: 20.
12. 李靜雯, 王秀梅. 腦機接口技術在醫療領域的應用. 信息通信技術與政策, 2021, 2021(2): 87-91.
13. 陳小剛, 楊晨, 陳菁菁, 等. 腦機接口技術發展新趨勢——基于2019-2020年研究進展. 科技導報, 2021, 39(19): 56-65.
14. Zhuang M, Wu Q, Wan F, et al. State-of-the-art non-invasive brain–computer interface for neural rehabilitation: a review. Journal of Neurorestoratology, 2020, 8(1): 4.
15. Lahane P, Jagtap J, Inamdar A, et al. A review of recent trends in EEG based brain-computer interface//2019 International Conference on Computational Intelligence in Data Science (ICCIDS), IEEE, 2019: 1-6.
16. Wolpaw J R, Millán J, Ramsey N F. Brain-computer interfaces: definitions and principles. Handb Clin Neurol, 2020, 168: 15-23.
17. 龔瑜, 藺俊斌, 郝赤子, 等. 腦機接口在脊髓損傷康復中的應用進. 中國康復醫學雜志, 2020, 35(6): 744-748.
18. Matarasso A K, Rieke J D, White K, et al. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): training of volitional wrist extension after stroke, a case series pilot study. PLoS One, 2021, 16(5): e0250431.
19. Neto L L, Constantini A C, Chun R. Communication vulnerable in patients with amyotrophic lateral sclerosis: a systematic review. Neuro Rehabilitation, 2017, 40(4): 561-568.
20. Lee D Y, Lee M, Lee S W. Decoding imagined speech based on deep metric learning for intuitive BCI communication. IEEE Trans Neural Syst Rehabil Eng, 2021, 29: 1363-1374.
21. Jamil N, Belkacem A, Ouhbi S, et al. Noninvasive electroencephalography equipment for assistive, adaptive, and rehabilitative brain-computer interfaces: a systematic literature review. Sensors (Basel), 2021, 21(14): 4754.
22. 蔣麗勇, 劉術, 刁天喜, 等. 腦機接口技術進展及潛在軍事醫學應用. 軍事醫學, 2021, 45(10): 780-785.
23. 柯清超, 王朋利. 腦機接口技術教育應用的研究進展. 中國電化教育, 2019, 2019(10): 14-22.
24. Mehta A. Applying brain computer interface technology for playing games. International Journal of Engineering and Management Research, 2021, 11(3): 213-220.
25. 王繼龍. 多類運動想象腦電信號識別方法研究及其在AR場景中的應用. 長春: 東北電力大學, 2021.
26. 堯德中. 腦-機接口: 如何從實驗室到現實場景?. 生物醫學工程學雜志, 2021, 38(3): 405-408.
27. Veena N, Mahalakshmi S, Guruprasad S. Consumer BCI devices-applications and challenges. Advanced Aspects of Engineering Research, 2021, 11: 81-91.
28. 呂曉彤, 丁鵬, 李思語, 等. 腦機接口人因工程及應用:以人為中心的腦機接口設計和評價方法. 生物醫學工程學雜志, 2021, 38(2): 210-223.
29. 宋艷, 劉峰, 黃夢璇, 等. 新興技術產品商業化過程中的“峽谷”跨越研究——基于技術采用生命周期理論視角. 研究與發展管理, 2013, 25(4): 76-86.
30. Lee M H, Kwon O Y, Kim Y J, et al. EEG dataset and openBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy. Gigascience, 2019, 8(5): giz002.
31. Zhang Y. Invasive BCI and noninvasive BCI with VR/AR technology//International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2021). SPIE, 2021, 12153: 186-192.
32. Feng J K, Jin J, Daly I, et al. An optimized channel selection method based on multifrequency CSP-rank for motor imagery-based BCI system. Comput Intell Neurosci, 2019, 2019: 8068357.
33. Leuthardt E C, Moran D W, Mullen T R. Defining surgical terminology and risk for brain computer interface technologies. Front Neurosci, 2021, 15: 599549.
34. 中國人工智能產業發展聯盟. 腦機接口技術在醫療健康領域應用白皮書. 北京: 中國人工智能產業發展聯盟, 2021.
35. 中國電子技術標準化研究院. 腦機接口標準化白皮書. 北京: 中國電子技術標準化研究院, 2021.
36. Thompson M C. Critiquing the concept of BCI illiteracy. Sci Eng Ethics, 2019, 25(4): 1217-1233.
37. Gilbert F, Cook M, O'brien T, et al. Embodiment and estrangement: results from a first-in-human "intelligent BCI" trial. Sci Eng Ethics, 2019, 25(1): 83-96.
38. Rainey S, Maslen H, Savulescu J. When thinking is doing: responsibility for BCI-mediated action. AJOB Neurosci, 2020, 11(1): 46-58.
39. Jawad A J. Bioethics of medical devices based on brain computer interfaces (BCI). J Clinic Res Bioeth, 2021, 12(S8): 1000003.
40. 中國信息通信研究院. 腦機接口技術創新與產業發展研究報告. 北京: 中國信息通信研究院, 2021.

Journal of Biomedical Engineering

Applications, industrial transformation and commercial value of brain-computer interface technology

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