China

Researchers assessed the feasibility of a hybrid brain-computer interface that integrates motor imagery (MI) and steady-state visual evoked potentials (SSVEP) with robotic glove feedback for upper limb motor rehabilitation in 32 stroke patients, split into a conventional-treatment control group and an experimental group receiving 10- or 20-day BCI interventions. The experimental group showed considerable improvement in Fugl-Meyer scores over the control group, and the BCI achieved EEG classification accuracy up to 98.08% with stable operation; after longer training, accuracy rose, the laterality coefficient moved toward normal, and task-related brain connectivity strengthened. The authors say the hybrid system may overcome the limits of conventional therapy and single-modality BCIs.

The Chinese Clinical Trial Registry (ChiCTR) has logged a study of the safety and efficacy of early brain-computer interface training given after reperfusion therapy in patients with acute ischemic stroke, an attempt to pin down when in the recovery window such training should start. Registered on April 27, 2026 as ChiCTR2600123548, the trial has not begun recruiting, and design, sample size and sponsor are absent from the record carried by the WHO International Clinical Trials Registry Platform (ICTRP) and must be read from the original registration.

The Chinese Clinical Trial Registry (ChiCTR) has logged a multicenter randomized controlled trial testing whether brain-computer interface-based mindfulness meditation relieves the symptoms of chronic tinnitus. Registered on April 23, 2026 as ChiCTR2600123258, the trial has not begun enrolling patients, and its design, sample size and sponsor must be read from the original registration record. It is the first multicenter registration to combine BCI with mindfulness meditation for chronic tinnitus, moving the approach from single-center exploration toward multicenter validation.

A trial registered with the Chinese Clinical Trial Registry combines low-frequency rTMS with motor imagery brain-computer interface therapy, using conventional physical rehabilitation as the control, with the Fugl-Meyer upper extremity scale as the primary endpoint. The study has three parts: Part I compares BCI therapy with conventional rehabilitation, while Part III compares three rTMS protocols. It plans to enroll 213 participants, with first enrolment set for May 1, 2026; recruitment has not yet begun.

The trial combines a brain-computer interface with robotic mirror therapy into a single intervention, while the control arm receives conventional comprehensive rehabilitation only. It enrolls patients aged 30 to 80 with unilateral upper-limb motor impairment 1 to 6 months after ischemic or hemorrhagic stroke, whose lesions are confined to the basal ganglia. The primary endpoint is the Fugl-Meyer Assessment of the Upper Extremity, with EEG, functional MRI and the Modified Ashworth Scale among secondary measures. The planned enrollment is 40 patients, with first enrollment set for May 1, 2026.

A trial of a dual-task brain-computer interface (BCI) combining motor-intention detection with virtual reality training is recruiting patients to measure how it affects shoulder function after rotator cuff repair surgery, following its registration with the Chinese Clinical Trial Registry (ChiCTR) on April 20, 2026. The record has been reposted by the WHO International Clinical Trials Registry Platform (ICTRP).

A brain-computer interface (BCI) trial for upper-limb motor rehabilitation after hemorrhagic stroke was registered with the Chinese Clinical Trial Registry under the number ChiCTR2600122859 on April 20, 2026, and has not yet begun recruiting. The study combines electroencephalography (EEG) with functional near-infrared spectroscopy (fNIRS). The registration record does not disclose the study design, sample size or sponsor.

A Nature Communications study tested ultra-Flexible Implantable Neural Electrode arrays during awake surgery in 16 patients. Valid single-unit recordings were obtained in 11 patients, yielding 719 isolated neurons and as many as 135 simultaneously, while five early cases failed because of operating-room noise or damaged insertion needles. The work was intraoperative and does not establish long-term implant performance.

A trial registered in China pairs brain-computer interface technology with mindfulness meditation training for adolescents with depression, recording EEG alongside the sessions to see how brain activity changes. The question is whether real-time brain signals can be read during meditation and fed back into the training, making the intervention more responsive to each participant's state. Recruitment has not yet started, and the design, sample size and sponsor have not been disclosed.

Researchers at Xidian University built DisCo-Former, a Transformer framework for single-trial rapid serial visual presentation (RSVP) EEG decoding with three components guided by neurophysiological priors, then found its attention consistently collapsed: attention maps went nearly uniform and value-projection weights shrank toward 0. Stripping out the Transformer encoder left DisCo-MLP, a pure multilayer perceptron that matched or beat the Transformer version across two datasets and three evaluation regimes, with within-subject mean AUCs of about 0.94 to 0.98. For RSVP-EEG, the authors argue, modeling the signal's structure matters more than architectural complexity. The study was published in the International Journal of Neural Systems on April 10, 2026.

A randomized controlled trial of motor-imagery brain-computer interface (BCI) training for swallowing difficulty after stroke was registered with the Chinese Clinical Trial Registry (ChiCTR) on April 9, 2026, under the number ChiCTR2600122162. It will test whether the training improves swallowing function in stroke patients, and has not yet begun recruiting.

People's Daily Online reported that BrainCo completed an RMB 2 billion Series B+ round in January 2026, the largest single BCI financing in China at the time. The report did not disclose the lead investor, a complete investor list or the post-money valuation. The round indicates a capital-intensive expansion phase across BrainCo's non-invasive and medical product lines.

To reduce negative transfer in motor imagery BCIs, the study presents an adaptive dynamic transfer learning framework that decomposes EEG time-frequency features via wavelet convolution, matches source and target samples through a dynamic transfer attention module, and uses a joint loss to shrink marginal and class-conditional differences. On BNCI2014001, BNCI2014002 and BNCI2015001 it reached 78.78%, 82.11% and 78.19% accuracy, averaging 0.13% to 27.7% above baseline algorithms.

On 31 March 2026 Hubei's provincial science and technology department approved the formation of a provincial brain-computer interface technology innovation centre, led by Tongji Hospital in Wuhan together with 12 organisations including Huazhong University of Science and Technology and Hubei Optics Valley Laboratory. Chinese reports describe it as the country's first provincial BCI platform positioned as comprehensive and full-chain. Its stated priorities are neural signal decoding, domestic sourcing of core components, and refining both non-invasive and implanted approaches. It is headed by Tang Zhouping, the hospital's party secretary.

Researchers propose DPMS-Net, a deep network that uses dynamic convolution to mine discriminative cues across temporal, spatial and frequency dimensions, combines channel and temporal attention, and adds a spectral-domain analysis component to surface subtle oscillatory features hidden in the EEG spectrum. On the BCI Competition IV 2a and 2b datasets it reached subject-dependent accuracies of 83.93% and 88.38%, and 67.67% on a self-collected stroke-patient dataset. The authors say its efficient decoding and robustness suit neurorehabilitation BCI systems.

The study presents MAPS-CS, an online SSVEP brain-computer interface that selects channels dynamically during the experiment. A multi-dimensional feature framework covering signal energy, stability and inter-channel correlation quantifies anomalies and generates scores that a hierarchical decision step combines into a channel-quality score to identify and remove bad channels — with no training required. Against the channel ensemble (CE) method, MAPS-CS lifted standard FBCCA accuracy by 3.5%, 4.1%, 4.4% and 6.5% at stimulus durations of 2 s, 1.5 s, 1 s and 0.5 s, the best among the CE, binary harmony search and TOP-K local optimization methods compared.

A randomized controlled trial in 120 patients with post-stroke hemiplegia found that pairing brain-computer interface (BCI) rehabilitation training with a gait robot accelerated lower-limb recovery and improved muscle activation patterns more than either intervention on its own. After eight weeks, BCI training, gait-robot training and the combination all improved lower-limb motor function, muscle activity and gait compared with routine training, but the combined group showed the largest increases in integrated electromyography of the tibialis anterior and gastrocnemius, along with a greater gain in step frequency and a greater reduction in step width.

A new entry in the Chinese Clinical Trial Registry covers a study using brain-computer interface technology for functional recovery after stroke. The record, ChiCTR2600120924, was posted on March 23, 2026, and lists its status as not yet recruiting. The registry listing carries only bibliographic details, so the trial design, sample size and sponsor remain undisclosed.

Nine Jiangsu provincial departments in eastern China led by the Department of Industry and Information Technology issued the Action Plan for Innovative Development of the Brain-Computer Interface Industry in Jiangsu in March 2026, implementing national guidance from seven ministries. Its most distinctive provision covers industrial deployment, directing firms in hazardous materials, nuclear power, mining and electricity to pilot BCI systems in safety management and deep-sea and deep-pit operations, sectors no other provincial document names. Headline goals are at least two provincial clusters by 2027 and two to three leading enterprises by 2030. Its quantitative targets sit at the end of 14 tasks and all fall in 2030, including at least 15 programme projects, 15 key technology tasks, about 10 innovation platforms, 30 certified flagship products, 20 registered medical devices and a dataset of at least 20,000 samples.

A Chinese trial will measure the immediate effects of a non-invasive brain-machine interface combined with multimodal training on neurophysiological function in patients with upper-limb hemiparesis after stroke. It was registered with the Chinese Clinical Trial Registry as ChiCTR2600120046 on March 9, 2026 and has not begun recruiting.

Four Chinese ministries jointly issued science-technology insurance guidance, listing BCI alongside AI and quantum technology as key sectors for dedicated insurance products.

Researchers have proposed MSARFNet, a multi-scale attention-based reconstruction fusion network that reached average classification accuracies of 84.64% and 87.96% on the BCI Competition IV 2a and 2b motor imagery datasets, outperforming several existing methods. The network extracts spatio-temporal features through parallel multi-scale convolutional branches and fuses them with an attention mechanism to sharpen transient motor-imagery responses, targeting the non-stationary EEG signals and inter-subject variability that make MI decoding unreliable. The study was published on February 27, 2026, in IEEE Journal of Biomedical and Health Informatics.

The Chinese Clinical Trial Registry (ChiCTR) has logged a study of a brain-computer interface (BCI)-enabled cognitive rehabilitation system, set to test its clinical effect in patients with mild cognitive impairment. Registered on February 25, 2026 as ChiCTR2600119334, the trial is not yet recruiting.

Researchers propose a function predefined convolutional neural network (FPCNN) for decoding spontaneous EEG in brain-computer interfaces. Its learnable function predefined convolution (FPC) layer searches for the key spatial-frequency parameters of spontaneous EEG so the parameters carry clear physical meaning, and it builds trainable orthogonal detectors on the FPC to capture complex phase-varying signals. On three spontaneous EEG datasets, FPCNN outperformed state-of-the-art methods by 2.09%, 3.08% and 3.41%, with single-round training and testing taking just 67.96 and 19.36 seconds on non-GPU hardware, which the authors say makes it suited to EEG processing in diverse environments.

The study presents an EEG emotion recognition framework that couples discriminative channel selection with hierarchical spatial-temporal modeling. Wavelet coherence and mutual information adaptively select informative channels across frequency bands, and a spatial-temporal graph-aware network (STG-Net) models inter-channel spatial relations and the temporal evolution of emotional states before fusing frequency-spatial-temporal features for classification. The authors report better recognition accuracy and model efficiency than state-of-the-art methods.

NeuroXess broke ground on a roughly 14,300-square-meter BCI manufacturing project in Jiangxi province in eastern China. The company said the facility would produce flexible implantable electrodes, neural recording equipment, surgical robots and fully implanted wireless BCI systems, with a target of stable supply at the 10,000-unit scale. NeuroXess expects the factory to begin operating in the second half of 2026, but the capacity and timeline remain company projections.

BrainCo's FocusXin Medical Edition combines a single-channel prefrontal EEG device registered as 浙械注准20232071898 with ADHD rehabilitation software registered as 浙械注准20252211934. The Class II system is intended for supplementary rehabilitation training in children aged 6 to 12 with ADHD. Its defined medical use should not be generalized into approval for an unspecified consumer BCI product.

Tongji Hospital in Wuhan implanted a 64-channel high-throughput flexible electrode array made by Wuhan Neuracom into a 31-year-old man paralysed by a spinal cord injury on 26 November 2025. The procedure was charged under the country's first BCI medical service price schedule, issued by Hubei's healthcare security bureau in March 2025, which sets implantation at 6,552 yuan. China's National Healthcare Security Administration calls it the first BCI operation in the country carried out under a state-set price. This patient's costs were covered by research funding.

The General Office of China's Jiangxi Provincial People's Government issued Several Measures for Accelerating the Development of Brain-Computer Interface Technology and Industry in Jiangxi on November 26, 2025, document number Gan Fu Ting Fa [2025] No. 29, setting out 11 measures across four areas. It was the first provincial document to follow the seven-ministry national guidance and is the only one that sets no quantitative industry targets at all. Its eleventh measure calls for implementing BCI research ethics guidelines and establishing mutual recognition of clinical research ethics review, a first among provincial documents. Other measures deploy a provincial major science and technology programme, back Ganjiang New Area in building a rehabilitation centre and a high-quality EEG dataset, and offer early regulatory engagement plus rewards for Class II and Class III innovative device approvals.

Tongji Hospital in Wuhan announced a brain-computer interface research institute on 5 September 2025, which it says is the first of its kind run by a hospital in China rather than by a university or a company. The institute covers basic research, clinical application and commercialisation, with the stated aim of building a full-chain BCI system spanning prevention, diagnosis, treatment and rehabilitation of neurological disease.