On March 4, the 2026 National Two Sessions (annual plenary sessions of the National People's Congress and of the National Committee of the Chinese People's Political Consultative Conference) officially opened. In the medical device sector, topics such as AI, brain-computer interfaces, intelligent medical devices, innovation, global expansion, and senior healthcare became buzzwords, attracting widespread attention from delegates.
01
Surge in Interest for Brain-Computer Interfaces
Explosive Growth in Intelligent Medical Devices
On March 5, Li Lecheng, Minister of Industry and Information Technology, stated in an interview that full efforts should be made to advance the research, development, and iterative upgrading of next-generation artificial intelligence (AI) products, including brain-computer interfaces, autonomous vehicles, and robots, to promote scientific and technological breakthroughs and technology iteration. He called for vigorous support for the development of intelligent agricultural machinery and intelligent medical devices, allowing more intelligent products to meet the needs of various industries and sectors.
Currently, there has been considerable exploration of the application of brain-computer interfaces in the medical field.
Ming Dong, a member of the National Committee of the Chinese People's Political Consultative Conference (CPPCC), Vice President of Tianjin University, and Director of the Haihe Laboratory for Brain-Computer Interaction and Human-Machine Integration, noted that China's research, development, and application of brain-computer interface technology as a whole are currently positioned within the world's leading tier. In the "non-invasive" domain in particular, China is essentially keeping pace with the most advanced international level.
However, the development of brain-computer interfaces still faces numerous challenges in the transition from laboratory to clinical and industrial applications. Ming Dong believes that all technologies - from core electronic components to high-end general-purpose chips to foundational software products and key underlying system platforms - still need to mature progressively.
Wang Jian'an, a member of the National Committee of the CPPCC, an Academician of the Chinese Academy of Sciences, and President of The Second Affiliated Hospital of Zhejiang University School of Medicine, also found through research that the key aspects in translating brain-computer interface technology into the high-end medical devices still face systemic challenges, including limited core technologies, unclear industrial translation pathways, and the absence of an ethical regulatory framework.
He suggested that a national-level clinical access mechanism be established to select a group of leading institutions with both top-tier clinical capabilities and deep technical expertise to serve as "vanguards." These institutions would, under strict supervision, take the lead in conducting clinical research and applications, accumulating China's own clinical data and experience, rather than allowing all hospitals to rush in at once.
In addition, he emphasized promoting the building of a complete innovation ecosystem for brain-computer interfaces. "Technology must not remain confined to academic papers - the key is to break down the barriers between universities, scientific research institutes, and medical device enterprises. Only by forming an efficient innovation chain can a wild idea in the laboratory rapidly be turned into a finished medical device product that is safe and reliable, can be mass-produced, and has controllable costs."
Yao Dezhong, a deputy to the National People's Congress (NPC), Director of the China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, and Professor at the University of Electronic Science and Technology of China (UESTC), pointed out that although China already has a number of mature products in the non-invasive motor rehabilitation field and has achieved notable results in deep brain stimulation, core bottlenecks still remain. Pain points that urgently need to be resolved include the near-total reliance on imports for EEG (electroencephalogram) acquisition chips, the near-absence of original interface paradigms, and the failure to achieve widespread real-world applications.
Yao Dezhong believes it is necessary to map out the rigid-demand scenarios centered on the diagnosis and treatment of brain diseases, accelerate the formulation of industry norms and technical standards, and guide capital investment with precision. With regard to promoting the integration of scientific and technological innovation with industrial innovation, he recommends that government funding be used to guide joint research and development by enterprises and laboratories, allowing brain-computer interface technology to focus primarily on the diagnosis and treatment of major neuropsychiatric diseases, thereby establishing a new pattern that complements drug-based treatment.
02
Window of Opportunity Opening for Senior Healthcare
Deep Integration of AI with Medical Devices
In the context of population aging, can AI better leverage its advantages to support the development of senior healthcare?
Yu Qingming, a deputy to the NPC and Non-executive Director of Sinopharm Group, stated in an interview, "Currently, China has entered a moderately aging society. As of the end of 2025, the population aged 60 and above has reached 323 million, accounting for 23% of the total population. Addressing population aging has become an important starting point for formulating economic and social development policies."
Currently, the supply of intelligent devices in the market that are precisely tailored to the medical and health needs of the elderly remains insufficient, with a gap between product suitability and actual demand. To this end, Yu Qingming stated that efforts should be directed at the supply side to optimize product structure.
With regard to promoting the deep integration of artificial intelligence with medical devices, Yu Qingming believes that support should be provided for enterprises to develop intelligent devices with functions such as heart rate, respiration, and eye movement monitoring, abnormality alerts, and two-way communication, so as to achieve timely intervention in health risks for elderly people living at home and build a strong safety net for elderly care.
With regard to developing multi-function intelligent service robots, Yu Qingming pointed out that the priority should be to develop products with functions such as home companionship, health consultation, and fitness guidance, upgrading devices from "functional tools" to warm health companions.
With regard to creating new consumption scenarios for senior healthcare, Yu Qingming stated that multi-departmental policy coordination should be strengthened, certain appropriate medical and health devices should be included in the healthcare insurance reimbursement catalogue, and applications of intelligent nursing and wearable rehabilitation robot products should be promoted in pilot cities for home-based elderly care, facilitating smart elderly care and alleviating the burden on society and families.
03
High Growth in Home Medical Devices
Acceleration of Intelligent Iteration
Ding Guanghong, a member of the National Committee of the CPPCC, focused this year on the standardization and development of home medical devices. Citing research data, he pointed out that over the past two years, China's home medical device market has maintained high-speed growth of over 20% per year, demonstrating enormous social demand and market potential.
Meanwhile, the intelligent iteration of products is also accelerating, with an increasing number of technologically advanced devices gradually entering households and becoming important tools for chronic disease management and daily health monitoring.
Ding stated that the advantage of home medical devices lies in their ability to continuously record fluctuations in the body's physiological indicators, providing more comprehensive data support for clinical treatment. "For example, measuring blood pressure at home can record multiple readings, reflecting the dynamic changes in blood pressure, which is very valuable for doctors in adjusting medication and treatment plans. In contrast, measurements taken in a hospital are often episodic values that may not accurately reflect the actual condition of the disease."
However, the rapid expansion of the market has also exposed numerous management shortcomings. Ding pointed out that there are currently problems of varying degrees in the production registration, circulation and sale, and use and maintenance of home medical devices. For example, the regulation of some devices is overly rigid, with unreasonable thresholds set for use, while other products that should be strictly managed are being sold freely online without effective regulation. Taking blood pressure monitors as an example, many households do not calibrate them after purchase for extended periods, using them for five or six years or even longer, making it difficult to guarantee accuracy. "Blood pressure monitors in hospitals must be mandatorily calibrated every year, and this awareness and service mechanism should apply to home use as well," said Ding.
In addition, some electronic products on the market make efficacy claims under the banner of "physical therapy," while their actual clinical effects remain unclear, which can easily mislead consumers. Ding believes that home medical devices cover a wide scope and involve complex product categories, and there is an urgent need to build a scientific tiered and classified management system, clearly defining what can be deregulated, what requires a prescription, and what must be strictly regulated, with particular emphasis on strengthening oversight of online sales channels.
To this end, Ding put forward five suggestions in his proposal: first, clarify the boundaries of product categories and build a scientific tiered and classified management mechanism; second, optimize product design and labeling to improve safety and convenience of use; third, standardize business formats and improve omni-channel regulatory rules; fourth, strengthen policy support to promote high-quality innovative development of the industry; and fifth, encourage the research, development, and promotion of high-end intelligent home medical devices.
He specifically mentioned that at the national level, incentive policies should be introduced to support universities, medical institutions, and enterprises in conducting joint research and development of home medical devices that are intelligent, technically advanced, and clinically effective.
04
Strengthening the Innovative Application of AI in Healthcare
Expanding Promotion at the Primary Healthcare Level
The rapid development of AI has opened up numerous imaginative spaces for the innovative revolution in the healthcare sector. In the future, how to better leverage AI's effectiveness to enhance healthcare quality and efficiency still requires the collective efforts of the industry.
Cao Peng, a member of the National Committee of the CPPCC and Chairman of JD.com's Technology Committee, proposed strengthening the innovative application of AI in specialist and disease-specific medicine, encouraging the launch of national-level pilots for AI-assisted diagnosis and treatment in specialty care and disease-specific management, incorporating mature AI-assisted diagnosis and treatment plans into clinical pathway management, and comprehensively improving the precision and homogeneity of clinical diagnosis and treatment. He advocated promoting an AI-driven "consultation-testing-diagnosis-medication" closed-loop model, encouraging Internet medical platforms to build a full-process medical service closed loop driven by AI, and supporting the integrated model innovation of "AI-guided triage - online consultation - home-visit testing - drug delivery - rehabilitation management."
He suggested implementing a special action to enhance AI accessibility in primary healthcare, creating customized AI agents for community doctors and rural doctors, and promoting the "AI digital doctor" model, to comprehensively improve primary-level diagnosis and treatment service capabilities. He also called for using AI to simultaneously enhance both doctors' clinical and research capabilities, encouraging enterprises to develop full-process AI empowerment tools for doctors, and supporting platforms in offering basic functions to all doctors for free, thereby helping doctors improve clinical decision-making efficiency and research capabilities.
The tangible benefits of AI healthcare for primary care facilities have yet to be fully realized.
Dai Lizhong, a deputy to the NPC and Chairman of Sansure Biotech Inc., pointed out in an interview that challenges of insufficient support exist in primary-level AI healthcare service capabilities and supporting infrastructure: primary-level medical institutions lack professional AI-assisted diagnosis and treatment tools and online service terminal support, and medical personnel's ability to apply AI technology is insufficient, making it difficult to fully leverage the technological advantages of AI remote diagnosis and AI-assisted diagnosis.
"In reality, medical AI capital and technical resources are more concentrated in Grade A tertiary hospitals, with insufficient supply of miniaturized, low-cost, easy-to-operate products for primary-level healthcare," also stated Geng Funeng, a deputy to the NPC and Chairman of Good Doctor Group.
With regard to how to expand the promotion of AI healthcare at the primary level, Dai Lizhong proposed driving broader adoption through pilot programs and establishing demonstration sites as industry benchmarks, thereby driving the rapid on-the-ground implementation of AI healthcare technology. He suggested establishing "AI + Healthcare" innovation pilot zones, selecting regions with concentrated medical resources and a good internet foundation, and choosing different scenarios, including primary-level medical and health institutions, tertiary hospitals, and public health institutions, to conduct pilots in core scenarios such as AI remote diagnosis, infectious disease early warning, patient triage, and drug development assistance. He also suggested establishing a fault-tolerance and error-correction mechanism, dynamically adjusting pilot policies, increasing policy support and financial investment in pilot regions and units, providing subsidies to primary-level healthcare facilities that have introduced AI healthcare technology, and incorporating high-quality AI healthcare products into the scope of medical insurance reimbursement.
Geng Funeng suggested establishing a special subsidy fund for the application of AI agents by grassroots-level doctors, with central and local governments sharing the cost in proportion. He recommended providing 30%-50% purchase subsidies for AI agents procured to manage common diseases and chronic diseases at the primary level, with a higher rate applied in rural areas - for example, 50%-60% - along with annual operation and maintenance subsidies.
Dai Lizhong also mentioned that the current large-scale promotion of AI + healthcare development also faces the challenge of insufficient data supply. "Enterprises are more sensitive to market pain points and better understand the needs of the public, but medical data has characteristics of privacy and dispersion. Currently, China's mechanism for open sharing of medical data is imperfect, and most anonymized medical data has not been effectively made available to AI healthcare enterprises, resulting in enterprises lacking high-quality, large-scale training data and being unable to develop large AI models that are adapted to China's medical scenarios and have high precision. Technological innovation has fallen into the predicament of 'making bricks without straw,' which has become the core bottleneck for the commercialization of AI healthcare." Dai Lizhong called for accelerating the opening up of anonymized medical data, establishing a unified platform for the opening up of anonymized medical data, and clarifying the scope, standards, and procedures for data openness.
Source: Saibailan Devices
01
Surge in Interest for Brain-Computer Interfaces
Explosive Growth in Intelligent Medical Devices
On March 5, Li Lecheng, Minister of Industry and Information Technology, stated in an interview that full efforts should be made to advance the research, development, and iterative upgrading of next-generation artificial intelligence (AI) products, including brain-computer interfaces, autonomous vehicles, and robots, to promote scientific and technological breakthroughs and technology iteration. He called for vigorous support for the development of intelligent agricultural machinery and intelligent medical devices, allowing more intelligent products to meet the needs of various industries and sectors.
Currently, there has been considerable exploration of the application of brain-computer interfaces in the medical field.
Ming Dong, a member of the National Committee of the Chinese People's Political Consultative Conference (CPPCC), Vice President of Tianjin University, and Director of the Haihe Laboratory for Brain-Computer Interaction and Human-Machine Integration, noted that China's research, development, and application of brain-computer interface technology as a whole are currently positioned within the world's leading tier. In the "non-invasive" domain in particular, China is essentially keeping pace with the most advanced international level.
However, the development of brain-computer interfaces still faces numerous challenges in the transition from laboratory to clinical and industrial applications. Ming Dong believes that all technologies - from core electronic components to high-end general-purpose chips to foundational software products and key underlying system platforms - still need to mature progressively.
Wang Jian'an, a member of the National Committee of the CPPCC, an Academician of the Chinese Academy of Sciences, and President of The Second Affiliated Hospital of Zhejiang University School of Medicine, also found through research that the key aspects in translating brain-computer interface technology into the high-end medical devices still face systemic challenges, including limited core technologies, unclear industrial translation pathways, and the absence of an ethical regulatory framework.
He suggested that a national-level clinical access mechanism be established to select a group of leading institutions with both top-tier clinical capabilities and deep technical expertise to serve as "vanguards." These institutions would, under strict supervision, take the lead in conducting clinical research and applications, accumulating China's own clinical data and experience, rather than allowing all hospitals to rush in at once.
In addition, he emphasized promoting the building of a complete innovation ecosystem for brain-computer interfaces. "Technology must not remain confined to academic papers - the key is to break down the barriers between universities, scientific research institutes, and medical device enterprises. Only by forming an efficient innovation chain can a wild idea in the laboratory rapidly be turned into a finished medical device product that is safe and reliable, can be mass-produced, and has controllable costs."
Yao Dezhong, a deputy to the National People's Congress (NPC), Director of the China-Cuba Belt and Road Joint Laboratory on Neurotechnology and Brain-Apparatus Communication, and Professor at the University of Electronic Science and Technology of China (UESTC), pointed out that although China already has a number of mature products in the non-invasive motor rehabilitation field and has achieved notable results in deep brain stimulation, core bottlenecks still remain. Pain points that urgently need to be resolved include the near-total reliance on imports for EEG (electroencephalogram) acquisition chips, the near-absence of original interface paradigms, and the failure to achieve widespread real-world applications.
Yao Dezhong believes it is necessary to map out the rigid-demand scenarios centered on the diagnosis and treatment of brain diseases, accelerate the formulation of industry norms and technical standards, and guide capital investment with precision. With regard to promoting the integration of scientific and technological innovation with industrial innovation, he recommends that government funding be used to guide joint research and development by enterprises and laboratories, allowing brain-computer interface technology to focus primarily on the diagnosis and treatment of major neuropsychiatric diseases, thereby establishing a new pattern that complements drug-based treatment.
02
Window of Opportunity Opening for Senior Healthcare
Deep Integration of AI with Medical Devices
In the context of population aging, can AI better leverage its advantages to support the development of senior healthcare?
Yu Qingming, a deputy to the NPC and Non-executive Director of Sinopharm Group, stated in an interview, "Currently, China has entered a moderately aging society. As of the end of 2025, the population aged 60 and above has reached 323 million, accounting for 23% of the total population. Addressing population aging has become an important starting point for formulating economic and social development policies."
Currently, the supply of intelligent devices in the market that are precisely tailored to the medical and health needs of the elderly remains insufficient, with a gap between product suitability and actual demand. To this end, Yu Qingming stated that efforts should be directed at the supply side to optimize product structure.
With regard to promoting the deep integration of artificial intelligence with medical devices, Yu Qingming believes that support should be provided for enterprises to develop intelligent devices with functions such as heart rate, respiration, and eye movement monitoring, abnormality alerts, and two-way communication, so as to achieve timely intervention in health risks for elderly people living at home and build a strong safety net for elderly care.
With regard to developing multi-function intelligent service robots, Yu Qingming pointed out that the priority should be to develop products with functions such as home companionship, health consultation, and fitness guidance, upgrading devices from "functional tools" to warm health companions.
With regard to creating new consumption scenarios for senior healthcare, Yu Qingming stated that multi-departmental policy coordination should be strengthened, certain appropriate medical and health devices should be included in the healthcare insurance reimbursement catalogue, and applications of intelligent nursing and wearable rehabilitation robot products should be promoted in pilot cities for home-based elderly care, facilitating smart elderly care and alleviating the burden on society and families.
03
High Growth in Home Medical Devices
Acceleration of Intelligent Iteration
Ding Guanghong, a member of the National Committee of the CPPCC, focused this year on the standardization and development of home medical devices. Citing research data, he pointed out that over the past two years, China's home medical device market has maintained high-speed growth of over 20% per year, demonstrating enormous social demand and market potential.
Meanwhile, the intelligent iteration of products is also accelerating, with an increasing number of technologically advanced devices gradually entering households and becoming important tools for chronic disease management and daily health monitoring.
Ding stated that the advantage of home medical devices lies in their ability to continuously record fluctuations in the body's physiological indicators, providing more comprehensive data support for clinical treatment. "For example, measuring blood pressure at home can record multiple readings, reflecting the dynamic changes in blood pressure, which is very valuable for doctors in adjusting medication and treatment plans. In contrast, measurements taken in a hospital are often episodic values that may not accurately reflect the actual condition of the disease."
However, the rapid expansion of the market has also exposed numerous management shortcomings. Ding pointed out that there are currently problems of varying degrees in the production registration, circulation and sale, and use and maintenance of home medical devices. For example, the regulation of some devices is overly rigid, with unreasonable thresholds set for use, while other products that should be strictly managed are being sold freely online without effective regulation. Taking blood pressure monitors as an example, many households do not calibrate them after purchase for extended periods, using them for five or six years or even longer, making it difficult to guarantee accuracy. "Blood pressure monitors in hospitals must be mandatorily calibrated every year, and this awareness and service mechanism should apply to home use as well," said Ding.
In addition, some electronic products on the market make efficacy claims under the banner of "physical therapy," while their actual clinical effects remain unclear, which can easily mislead consumers. Ding believes that home medical devices cover a wide scope and involve complex product categories, and there is an urgent need to build a scientific tiered and classified management system, clearly defining what can be deregulated, what requires a prescription, and what must be strictly regulated, with particular emphasis on strengthening oversight of online sales channels.
To this end, Ding put forward five suggestions in his proposal: first, clarify the boundaries of product categories and build a scientific tiered and classified management mechanism; second, optimize product design and labeling to improve safety and convenience of use; third, standardize business formats and improve omni-channel regulatory rules; fourth, strengthen policy support to promote high-quality innovative development of the industry; and fifth, encourage the research, development, and promotion of high-end intelligent home medical devices.
He specifically mentioned that at the national level, incentive policies should be introduced to support universities, medical institutions, and enterprises in conducting joint research and development of home medical devices that are intelligent, technically advanced, and clinically effective.
04
Strengthening the Innovative Application of AI in Healthcare
Expanding Promotion at the Primary Healthcare Level
The rapid development of AI has opened up numerous imaginative spaces for the innovative revolution in the healthcare sector. In the future, how to better leverage AI's effectiveness to enhance healthcare quality and efficiency still requires the collective efforts of the industry.
Cao Peng, a member of the National Committee of the CPPCC and Chairman of JD.com's Technology Committee, proposed strengthening the innovative application of AI in specialist and disease-specific medicine, encouraging the launch of national-level pilots for AI-assisted diagnosis and treatment in specialty care and disease-specific management, incorporating mature AI-assisted diagnosis and treatment plans into clinical pathway management, and comprehensively improving the precision and homogeneity of clinical diagnosis and treatment. He advocated promoting an AI-driven "consultation-testing-diagnosis-medication" closed-loop model, encouraging Internet medical platforms to build a full-process medical service closed loop driven by AI, and supporting the integrated model innovation of "AI-guided triage - online consultation - home-visit testing - drug delivery - rehabilitation management."
He suggested implementing a special action to enhance AI accessibility in primary healthcare, creating customized AI agents for community doctors and rural doctors, and promoting the "AI digital doctor" model, to comprehensively improve primary-level diagnosis and treatment service capabilities. He also called for using AI to simultaneously enhance both doctors' clinical and research capabilities, encouraging enterprises to develop full-process AI empowerment tools for doctors, and supporting platforms in offering basic functions to all doctors for free, thereby helping doctors improve clinical decision-making efficiency and research capabilities.
The tangible benefits of AI healthcare for primary care facilities have yet to be fully realized.
Dai Lizhong, a deputy to the NPC and Chairman of Sansure Biotech Inc., pointed out in an interview that challenges of insufficient support exist in primary-level AI healthcare service capabilities and supporting infrastructure: primary-level medical institutions lack professional AI-assisted diagnosis and treatment tools and online service terminal support, and medical personnel's ability to apply AI technology is insufficient, making it difficult to fully leverage the technological advantages of AI remote diagnosis and AI-assisted diagnosis.
"In reality, medical AI capital and technical resources are more concentrated in Grade A tertiary hospitals, with insufficient supply of miniaturized, low-cost, easy-to-operate products for primary-level healthcare," also stated Geng Funeng, a deputy to the NPC and Chairman of Good Doctor Group.
With regard to how to expand the promotion of AI healthcare at the primary level, Dai Lizhong proposed driving broader adoption through pilot programs and establishing demonstration sites as industry benchmarks, thereby driving the rapid on-the-ground implementation of AI healthcare technology. He suggested establishing "AI + Healthcare" innovation pilot zones, selecting regions with concentrated medical resources and a good internet foundation, and choosing different scenarios, including primary-level medical and health institutions, tertiary hospitals, and public health institutions, to conduct pilots in core scenarios such as AI remote diagnosis, infectious disease early warning, patient triage, and drug development assistance. He also suggested establishing a fault-tolerance and error-correction mechanism, dynamically adjusting pilot policies, increasing policy support and financial investment in pilot regions and units, providing subsidies to primary-level healthcare facilities that have introduced AI healthcare technology, and incorporating high-quality AI healthcare products into the scope of medical insurance reimbursement.
Geng Funeng suggested establishing a special subsidy fund for the application of AI agents by grassroots-level doctors, with central and local governments sharing the cost in proportion. He recommended providing 30%-50% purchase subsidies for AI agents procured to manage common diseases and chronic diseases at the primary level, with a higher rate applied in rural areas - for example, 50%-60% - along with annual operation and maintenance subsidies.
Dai Lizhong also mentioned that the current large-scale promotion of AI + healthcare development also faces the challenge of insufficient data supply. "Enterprises are more sensitive to market pain points and better understand the needs of the public, but medical data has characteristics of privacy and dispersion. Currently, China's mechanism for open sharing of medical data is imperfect, and most anonymized medical data has not been effectively made available to AI healthcare enterprises, resulting in enterprises lacking high-quality, large-scale training data and being unable to develop large AI models that are adapted to China's medical scenarios and have high precision. Technological innovation has fallen into the predicament of 'making bricks without straw,' which has become the core bottleneck for the commercialization of AI healthcare." Dai Lizhong called for accelerating the opening up of anonymized medical data, establishing a unified platform for the opening up of anonymized medical data, and clarifying the scope, standards, and procedures for data openness.
Source: Saibailan Devices