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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17.	龚瑜, 蔺俊斌, 郝赤子, 等. 脑机接口在脊髓损伤康复中的应用进. 中国康复医学杂志, 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.
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23.	柯清超, 王朋利. 脑机接口技术教育应用的研究进展. 中国电化教育, 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.	王继龙. 多类运动想象脑电信号识别方法研究及其在AR场景中的应用. 长春: 东北电力大学, 2021.
26.	尧德中. 脑-机接口: 如何从实验室到现实场景?. 生物医学工程学杂志, 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.	吕晓彤, 丁鹏, 李思语, 等. 脑机接口人因工程及应用:以人为中心的脑机接口设计和评价方法. 生物医学工程学杂志, 2021, 38(2): 210-223.
29.	宋艳, 刘峰, 黄梦璇, 等. 新兴技术产品商业化过程中的“峡谷”跨越研究——基于技术采用生命周期理论视角. 研究与发展管理, 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.	中国人工智能产业发展联盟. 脑机接口技术在医疗健康领域应用白皮书. 北京: 中国人工智能产业发展联盟, 2021.
35.	中国电子技术标准化研究院. 脑机接口标准化白皮书. 北京: 中国电子技术标准化研究院, 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.	中国信息通信研究院. 脑机接口技术创新与产业发展研究报告. 北京: 中国信息通信研究院, 2021.

1. 伏云发, 郭衍龙, 张夏冰, 等. 脑-机接口--革命性的人机交互. 北京: 国防工业出版社, 2020.
2. Graimann B, Allison B, Pfurtscheller G. Brain-computer interfaces: revolutionizing human-computer interaction. Springer Publishing Company, 2013.
3. 伏云发, 龚安民, 陈超, 等. 面向实用的脑-机接口: 缩小研究与实际应用之间的差距. 北京: 科学出版社, 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. 伏云发, 丁鹏, 罗建功, 等. 脑-计算机接口. 国防工业出版社, 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. 李静雯, 王秀梅. 脑机接口技术在医疗领域的应用. 信息通信技术与政策, 2021, 2021(2): 87-91.
13. 陈小刚, 杨晨, 陈菁菁, 等. 脑机接口技术发展新趋势——基于2019-2020年研究进展. 科技导报, 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. 龚瑜, 蔺俊斌, 郝赤子, 等. 脑机接口在脊髓损伤康复中的应用进. 中国康复医学杂志, 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. 蒋丽勇, 刘术, 刁天喜, 等. 脑机接口技术进展及潜在军事医学应用. 军事医学, 2021, 45(10): 780-785.
23. 柯清超, 王朋利. 脑机接口技术教育应用的研究进展. 中国电化教育, 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. 王继龙. 多类运动想象脑电信号识别方法研究及其在AR场景中的应用. 长春: 东北电力大学, 2021.
26. 尧德中. 脑-机接口: 如何从实验室到现实场景?. 生物医学工程学杂志, 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. 吕晓彤, 丁鹏, 李思语, 等. 脑机接口人因工程及应用:以人为中心的脑机接口设计和评价方法. 生物医学工程学杂志, 2021, 38(2): 210-223.
29. 宋艳, 刘峰, 黄梦璇, 等. 新兴技术产品商业化过程中的“峡谷”跨越研究——基于技术采用生命周期理论视角. 研究与发展管理, 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. 中国人工智能产业发展联盟. 脑机接口技术在医疗健康领域应用白皮书. 北京: 中国人工智能产业发展联盟, 2021.
35. 中国电子技术标准化研究院. 脑机接口标准化白皮书. 北京: 中国电子技术标准化研究院, 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. 中国信息通信研究院. 脑机接口技术创新与产业发展研究报告. 北京: 中国信息通信研究院, 2021.

Journal of Biomedical Engineering

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

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