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fNIRS

5 entries
September 2026

Adding fNIRS to EEG Fails to Improve Brain-Controlled Stimulation in 16-Person Trial

Combining EEG with functional near-infrared spectroscopy (fNIRS) did not make brain-controlled electrical stimulation more accurate in a blinded randomized trial of 16 healthy volunteers. The hybrid and EEG-only groups showed no statistically significant differences in real-time three-class recall, sense of agency, attention or physical comfort; median recall was 53.5% in the hybrid group and 57.3% with EEG alone. The researchers also released the full EEG-fNIRS dataset.

Anhui Hospital to Build 400-Person Post-Stroke BCI Dataset

About 70% to 80% of stroke survivors cannot live independently because of physical disability, and regaining walking function is central to changing that. This observational, cross-sectional study plans to enroll 200 stroke patients and 200 healthy controls, collecting EEG, fNIRS, sEMG, fMRI and other central and peripheral physiological signals alongside clinical measures such as Facial Action Units, the Berg Balance Scale and Fugl-Meyer motor function. The goal is a reusable non-invasive BCI dataset for stroke rehabilitation research. First enrollment is set for October 1, 2026.

ANT Neuro, optohive to Build Hybrid EEG-fNIRS Cap

ANT Neuro, the Dutch EEG equipment maker headquartered in Hengelo, announced a strategic collaboration on September 1, 2026 with optohive AG, the Swiss developer of the HiveOne functional near-infrared spectroscopy system. Under the agreement, HiveOne will be sold and supported through ANT Neuro's regional sales and technical teams, reaching the research customers the company says it has served for nearly 30 years. The two will also co-develop a hybrid cap that holds ANT Neuro's eego EEG technology and HiveOne together and synchronizes both data streams through Lab Streaming Layer; optohive was founded in 2025 as an ETH Zurich spin-off, the announcement said.
August 2026

Tianjin University's MTGNet Denoises EEG, Lifting Fatigue Detection by Over 6 Points

EEG signals are only microvolts strong, so blinks, jaw clenching and muscle activity easily contaminate them. Researchers at Tianjin University and Tiangong University in northern China proposed MTGNet, a framework that suppresses these artifacts while preserving the information downstream tasks need. On the public EEGDenoiseNet dataset, it cut spectral relative root-mean-square error by 18.9%, 31.5% and 14.0% for EMG, EOG and mixed artifacts respectively; on a real-world fatigue EEG dataset, it raised classification accuracy by 6.20 to 6.69 percentage points over unprocessed input. Adapting the framework to a new task takes only 0.33 million low-rank adaptation (LoRA) parameters and no paired clean EEG reference.
April 2026

Chinese Registry Logs EEG-fNIRS BCI Trial for Arm Recovery After Hemorrhagic Stroke

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.
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