Brain-computer interface (BCI) is a new technology that subverts traditional human-computer interaction. In recent years, the Chinese government has attached great importance to developing brain-computer technology and launched Brain Science and Brain-Like Intelligence Technology in 2016.
China Brain Project: Brain Science and Brain-Like Intelligence Technology was launched in 2016. China's "Brain Project" has two directions: brain science oriented to explore the brain's secrets and overcome brain diseases, and brain-inspired research oriented towards building and developing artificial intelligence technology.
In China's 14th Five-Year Plan and the 2035 long-term goal outline, artificial intelligence and brain science are national strategic scientific and technological forces. The plan further points out that it is necessary to strengthen original and leading scientific and technological research, and concentrate superior resources to tackle scientific and technological frontiers.
Among them, brain-like computing and brain-computer fusion technology research and development are one of the important fields, and brain-computer interface technology is one of the keys to brain-computer intelligence fusion technology. The brain-computer intelligence fusion system can be widely used in neurorehabilitation, including cognitive monitoring and neuromodulation, and it is also widely used in biological intelligence fields such as animal robots.
Shanghai, Beijing and Hangzhou Are the First To Respond
Shanghai is the first city to propose interdisciplinary research on brain and brain-like projects using computational neuroscience as a bridge. Brewing began at the end of 2014, and the first primary research pre-research project was launched in March 2015. In May 2015, Shanghai issued 22 regulations for constructing a globally influential technological innovation center, listing brain science and artificial intelligence as the top major basic projects.
In December 2018, the city-level major special project on the fundamental transformation and application of brain and brain-inspired intelligence was launched, followed by related special projects such as the "Whole Brain Neural Connection Map and Cloned Monkey Model Project".
Beijing is also increasing policy support in related fields. On November 11, 2018, the Beijing Municipal Science and Technology Commission issued six notices to solicit reserve projects in six major technical fields in 2018, the first of which is cognition and brain-inspired technology.
In 2019, the Beijing Municipal Bureau of Economy and Information Technology issued a notice on "Beijing Robot Industry Innovation and Development Action Plan (2019-2022)". The critical work of the action plan points out that "in the field of elderly care and health services, society should lay out key technologies such as machine learning, tactile feedback, augmented reality, and brain-computer interface, and promote the development and production of rehabilitation robots such as multifunctional arms and exoskeleton robots, and intelligent nursing robots."
In 2021, Hangzhou West Lake District laid out the brain-computer intelligence industry, striving to build a brain-computer intelligence industry chain. The West Lake District Brain-Computer Intelligence Project aims to explore a new path of deep integration of industry, education, and research with state-owned enterprises as the main body and help West Lake District to build a national cooperation demonstration area.
Industry Status of Brain-Computer Interface Technology in China
Brain-computer interface technology involves multidisciplinary integration. Currently, researchers in China are mainly from research institutes and universities. Referring to foreign brain-computer research, Chinese institutions have made some progress in brain-computer research.
Major Research Institutions of Brain-Computer Interface Technology in China
Institution | Type | Research Directions and Achievements |
Professor Gao Xiaorong's team from the BCI Laboratory of Tsinghua University School of Medicine  | Non-invasive | It is the first to propose and realize the non-invasive BCI technology based on SSVEP. By decoding the oscillation frequency of the primary visual cortex of the brain, the stimulus that the user is looking at is determined and converted into corresponding command output. |
The team of Professor Li Yuanqing, School of Automation Science and Engineering, South China University of Technology  | Non-invasive | Achieved good scientific results in vegetative consciousness detection based on the brain-computer interface; established a brain-computer interface research and development platform and multiple brain-computer interface systems, including brain-controlled wheelchairs, brain-controlled nursing beds, brain-controlled TVs, brain-controlled lamps, etc. |
The team of Professor Lu Baoliang, Department of Computer Science and Engineering, Shanghai Jiaotong University  | Non-invasive | Remarkable results in EEG and emotion recognition, as well as fatigue driving. |
The team of Professor Ming Dong from the Institute of Medical Engineering and Translational Medicine, Tianjin University  | Non-invasive | Taking brain-computer interaction as the main line of research, it focuses on engineering applications in major fields such as special medicine and ergonomics, physical medicine, and rehabilitation engineering. It has researched neural ergonomics perception interaction, artificial neural rehabilitation robots, new brain-computer interfaces, and quantitative research. Research on new methods and technologies of nervous system cognition and regulation represented by EEG information calibration. |
The team of Professor Jin Jing, School of Information Science and Engineering, East China University of Science and Technology  | Non-invasive | Research on the new rehabilitation technology for stroke patients based on brain-computer interface technology, the design of assistive technology for patients with amyotrophic lateral sclerosis, and the application of pattern recognition and machine learning in biosignal recognition. |
The team of Professor Bi Luzheng from the School of Machinery and Vehicles, Beijing Institute of Technology  | Non-invasive | Motor imagery-based brain-computer interface research in vehicle control. |
The team of Professor Yang Banghua, School of Mechanical and Electrical Engineering and Automation, Shanghai University  | Non-invasive | Mainly research the application of motion imagery brain-computer interface decoding technology, virtual reality technology, BCI combined with VR technology in medical rehabilitation, including rehabilitation training systems for stroke patients, etc. |
Professor Wu Dongrui's team from the Brain-Computer Interface and Machine Learning Laboratory of the School of Automation, Huazhong University of Science and Technology  | Non-invasive | Emotional computing and intelligent medical treatment of brain-computer interface. |
Professor Xu Guanghua's team from Xi'an Jiaotong University  | Non-invasive | Focus on the brain-computer active-passive collaborative rehabilitation mechanism of stroke rehabilitation and brain-controlled stroke rehabilitation robots. |
Professor Fu Yunfa's team from Kunming University of Science and Technology  | Non-invasive | Focus on research on theories, methods, models, and innovative applications of brain information processing and brain-computer interaction control and communication; functional brain neuroimaging, brain network connectivity calculations, and brain-computer interfaces and innovative applications. |
Researcher Yu Shan's team from the Institute of Automation, Chinese Academy of Sciences  | Invasive | Research on highly biocompatible electrode materials, high-performance brain-computer interface chips, minimally invasive implant technology, and highly robust encoding and decoding algorithms. |
The team of Professor Zheng Xiaoxiang, Institute of Brain-Computer Interface, Zhejiang University  | Invasive | In 2020, the team completed the first domestic invasive BCI clinical transformation research. |
Researcher Cui Hong's team from the Institute of Neuroscience, Chinese Academy of Sciences  | Invasive | Research interests are mainly in the neural basis of motor control, decoding methods, and brain-computer interface to help design brain-like intelligent robots and prosthetics and rehabilitate patients with movement disorders. |
Due to multiple constraints, such as technology and ethics, the research investment in invasive brain-computer interfaces is less than that of non-invasive brain-computer interfaces.
The number of research institutions and enterprises is far less than that of non-invasive brain-computer interfaces. Regarding acquisition equipment, the research and development of the critical components of the invasive brain-computer interface develop simultaneously with semiconductor materials and processing technology because of the particularity of brain tissue; the acquisition equipment has exceptionally high requirements for safety.
In addition to traditional rigid electrodes, in terms of flexible electrodes, Neuralink has developed a technology that Musk calls "neural lace", which implants tiny electrodes in the human brain, and inserts micron-scale threads into the areas of the brain that control movement.
In China, Kedo Brain Machine, established in 2016, has also developed a variety of invasive brain microelectrodes. However, the maximum use time of invasive electrodes is no more than two years, and there are still technological bottlenecks.
Great Market Potential, New Investment Hotspot, and Promising Future
In the past two years, with the continuous advancement of brain science, and artificial intelligence technology, brain-computer interfaces have also received more attention. No matter it is Facebook's plan to acquire brain-computer interface startup CTRL- Labs, or Neuralink, a brain-computer interface startup under Elon Musk, held a high-profile release event in August 2020 to disclose the latest research results, which pushed the brain-computer interface from the laboratory to the public view and became a current investment hotspot.
In China, Neuracle Technology (Changzhou) Co., Ltd., a professional technology company in the field of brain-computer interface, also completed a B-series round of financing.
Alibaba Damo Academy released the "Top Ten Technological Trends in 2021" forecast, pointing out that brain-computer interfaces will usher in significant progress and help humans surpass biological limits.
According to data from QYResearch, the global brain-computer interface market reached 1.2 billion yuan in 2019 and is expected to reach 2.7 billion yuan in 2026, with a compound annual growth rate of 12.4%. Among them, North America is the largest market in the world, accounting for more than 60% of the total market share.
China's research and development of brain-computer interfaces are in the early stages, and both the technology and the market start later than foreign countries.
Currently, enterprises are mainly concentrated in the medical field, and the application scenarios in the non-medical area mainly include education and smart home.
Major Chip Manufacturers for Brain-Computer Interface
Company Name | Introduction | Research Direction | Product |
NEURALINK  | Founded in 2015, Musk acquired it in 2016. | Focus on invasive brain-computer interface research, mainly research and develop brain-computer interface technology that implants artificial intelligence into the human cerebral cortex. | In 2019, Neuralink released the self-developed N1 brain sensor chip, which converts the recorded cell membrane surface potential into digital signals through filtering and other processing. |
 NeuroSky | Founded in San Jose, USA in 2004, with internationally leading biosignal sensing technology | Mainly engaged in the technical research and development of biological signal acquisition and processing, brain-computer interface, and other fields. | NeuroSky ThinkGear technology fully integrates the functions of brainwave signal acquisition, filtering, amplification, A/D conversion, data processing, and analysis into an ASIC chip. |
CEC CLOUD BRAIN (TIANJIN) TECH CO., LTD.  | Established in Tianjin in 2018 | Tianjin University and China Electronics Corporation cooperate to build a national health medical big data cloud brain center | In 2019, a highly integrated brain-computer interaction chip "Brain Whisperer" was developed. |
 NeuraMatrix | Tianjin University and China Electronics Corporation cooperate to build a national health medical big data cloud brain center. | Development of a new generation of brain-computer interface platform, covering brain-computer interface chips, systematic equipment, software and hardware integration platform | After several rounds of iterations, NeuraMatrix's self-developed brain-computer interface chip has been taped out and will be released soon. |
Main application products of Chinese brain-computer interface technology in the field of medical and health
Company | Introduction | Research Direction | Product |
 Neuracle Technology (Changzhou) Co., Ltd. | Founded in 2011 by experts from the Neural Engineering Laboratory of Tsinghua University | Non-invasive, minimally invasive brain-computer interface | Build a brain-computer interface technology platform centered on neural signal collection, analysis, and feedback, and form a series of non-invasive and minimally invasive products and solutions. The research and development focuses on brain science research, mental and psychological disease screening, and monitoring of various nervous system diseases. , diagnosis and rehabilitation. |
BrainCo  | Founded in 2015, the first Chinese team incubated by Harvard Innovation Lab | Non-invasive brain-computer interface | Development of non-invasive wearable devices for cognitive and emotional training, functional recovery for hemiplegic patients. Using non-invasive non-invasive hybrid brain-computer interface technology, through wearing equipment to collect and process the human body's electroencephalogram (EEG) and electromyography (EMG), to realize the reading of brain information and the control of external devices. |
Shanghai Idea-Interaction Tech.Co.,Ltd.  | Founded in 2016, incubated in the Electromechanical Laboratory of Shanghai Jiaotong University | R&D and production of limb rehabilitation equipment, the main product is EEG cap | An eCon wireless EEG collection device, which can collect and save the user's brain wave signal from the brain epidermis; eConHand hand function rehabilitation device, used to assist stroke patients in hand function rehabilitation training. |
BrainUp  | Founded in 2018, headquartered in Beijing | Focus on brain science, brain health screening, EEG algorithm, EEG data open platform and other cutting-edge technology applications in brain science | BrainUp, an intelligent brain-computer interaction headband for home sleep aids, monitors all-round EEG signals. |
 Zhen Tec | Founded in 2018, relying on the technical advantages of Xi'an Jiaotong University | Research and development of brain-controlled active-passive collaborative rehabilitation robots and various brain-computer interface related systems | Wireless portable medical-grade EEG headset, which can be applied to sleep monitoring, emotion recognition and cognitive rehabilitation. |
 Jiangsu Brain Machine Fusion Intelligence Institute | Established in Suzhou in 2019, relying on the research team of the Institute of Semiconductors, Chinese Academy of Sciences | Focus on the development of core devices and solutions for brain state detection and brain-computer interface | EEG signals are used to detect and identify fatigue states. Edge computing processors with high energy efficiency realize the local execution of complex brain-computer interface algorithms. |
 Hangzhou Neuro Science and Technology Co., Ltd | Established in Hangzhou in December 2014 | Brain science medical overall solution, AI algorithm technology research, software and hardware product development | Brain science case database and algorithm, brain science big data cloud platform and electroencephalogragh and other self-developed supporting hardware |
Brain-computer Interface Technology and Industry Challenges
Brain-computer interface technology is of great research value in the medical field and has a wide range of applications. However, its research and development costs are high, the cycle is long, the technology maturity and productization are low, and technology development faces many challenges.
First of all, from the perspective of science and technology, the number of neurons in medicine is huge and complex, and the current research on brain feedback stimulation and brain working mechanism is minimal;
Technically, the signal acquisition method needs to be improved. The biggest challenge of the invasive interface is how to minimize the damage to the brain. As the implantation time prolongs, the puncture electrode is wrapped by inflammatory cells, leading to signal loss.
The non-invasive signal is poor, and there are many interference components in the process of EEG signal acquisition, such as muscle signal interference, and the design of EEG signal acquisition equipment with strong anti-interference ability needs to be solved.
Currently, the BCI system's maximum information conversion speed can be greater than 300 bit/min, far from the speed required for normal communication. How to improve the signal processing method to make it systematized and generalized to quickly, accurately, and effectively design a practical BCI system also needs to be studied;
From the perspective of security and ethics, there are risks of privacy leakage, including hacker attacks, mind control, and data theft. In particular, implanting invasive devices into the human body may cause trauma and infection to the human brain tissue. Therefore, issues of equipment security, personal privacy security, right to know and consent, autonomy and responsibility attribution, as well as issues of social fairness and justice that may arise after the use of brain-computer interface devices to obtain certain "capabilities" all need to be addressed as soon as possible;
Another critical point is that there is currently no unified basic theoretical framework for the brain-computer interface, and there is a lack of evaluation criteria that can scientifically evaluate the performance of brain-computer interface systems. There is no precedent for commercialization and regulation.
Since the brain-computer interface technology and the market are still in the early stages, the industry scale is unclear, product compliance is open to question, and there are no relevant laws to follow.
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