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最新の出版物:脳コンピュータインターフェース(BCI)に関する特許

脳コンピューターインターフェース

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Brain-computer interface
脳コンピューターインターフェースは直接 コミュニケーション 脳と外部機器間の連携を強化し、インタラクションと感覚回復に革命をもたらす。

脳コンピュータインターフェースとは、神経組織と外部の計算システムとの間の直接的な通信経路であり、従来の神経筋出力経路を迂回して、記録された脳活動をデバイスコマンド、合成音声、または復元された感覚フィードバックにリアルタイムで変換するものである。

この分野は侵襲性の軸に沿って分かれています。非侵襲的な手法 — 頭皮脳波、機能的近赤外線 分光法 外科手術のリスクなしに信号取得を可能にするが、空間分解能と信号対雑音比が著しく制限される。皮質表面に配置された皮質脳波グリッドは中間層を占め、ユタアレイやニューラリンクのフレキシブルスレッド電極システムに代表される完全な皮質内アプローチは、外科的埋め込み、異物反応、および電極の長期的な安定性劣化という代償を伴うものの、数百から数千のニューロンからの単一ユニットスパイクを同時に記録する。

信号処理 パイプライン - 急増 並べ替え, local field potential decomposition, and increasingly deep learning decoders trained on neural population dynamics — translate raw electrophysiology into high-dimensional control signals, with motor cortex decoding for cursor control and robotic limb actuation and speech area decoding for imagined or attempted speech synthesis representing the two most clinically advanced application tracks. 閉ループ architectures that combine neural recording with precisely timed cortical or peripheral neurostimulation are advancing stroke rehabilitation, treatment-resistant depression, and epilepsy management simultaneously.

以下に索引付けされた出版物と特許は、電極材料科学、ASICフロントエンドアンプ設計、デコーダアルゴリズム、ワイヤレス神経テレメトリ、生体適合性研究、および 臨床試験 侵襲性のあらゆるスペクトルにわたる結果:

これは、脳コンピュータインターフェース (BCI) に関する英語の世界中の出版物と特許の最新のセレクションです。多くの科学オンラインジャーナルから、BCI、脳コンピュータインターフェース、ニューラルインターフェース、皮質脳波、皮質内電極アレイ、ユタアレイ、ニューラリンクインプラント、ステントロード BCI、EEG ベース BCI に分類され、焦点を絞っています。 モーター cortex decoding, neural spike sorting, local field potential BCI, spiking neural network decoder, neural signal amplifier, closed-loop neurostimulation, BCI motor neuroprosthesis, speech BCI, imagined speech decoding, BCI cursor control, BCI communication device, neural decoder algorithm, BCI artifact rejection, flexible neural probe, biocompatible neural electrode and BCI long-term stability.

Large language models reveal the neural tracking of linguistic context in attended and unattended multi-talker speech

Published on 2026-05-07 by @MIT

Abstract: AbstractLarge language models (LLMs) capture long-range contextual structure in natural language and have recently been shown to align with the human brain’s contextualized linguistic encoding. This makes them a promising computational probe for studying how context-dependent linguistic information is represented during natural speech perception. Speech perception often occurs in multi-talker environments, where attention must dynamically select among competing streams, yet how contextual info[...]


Our summary: Large language models align with human brain encoding of linguistic context. The study explores how attention affects neural tracking of speech in multi-talker environments. Findings indicate that both attended and unattended speech streams contribute to neural predictions based on contextual information.

language models, neural tracking, speech perception, auditory attention

Publication

Suppression of inflammation associated with implants

Patent published on the 2026-05-07 in WO under Ref WO2026092500 by SUNMED THERAPEUTIC LTD [CN] (Sun Joseph [cn], Sun Dongxu [cn])

Abstract: Provided herein are methods and compositions for suppressing a foreign body reaction, such as an implant-associated inflammation in a subject, by using an anti-Galectin-3 antibody. Such methods and compositions can be used in various areas applications where an implant is introduced, such as in brain-computer interface (BCI).[...]


Our summary: Methods and compositions are described for suppressing implant-associated inflammation using an anti-Galectin-3 antibody. These approaches target the foreign body reaction in subjects receiving implants. Applications include areas like brain-computer interfaces (BCI).

anti-Galectin-3, inflammation suppression, foreign body reaction, implants

Patent

Towards the use of functional near-infrared spectroscopy as an assessment tool in disorders of consciousness

Published on 2026-04-30 by @MIT

Abstract: AbstractFunctional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging tool for assessing patients with disorders of consciousness (DoC). While functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have advanced the detection of covert brain function, their use is often constrained by accessibility, medical and physical contraindications, and practical limitations. fNIRS offers a portable, safe, and cost-effective alternative capable of measuring he[...]


Our summary: Functional near-infrared spectroscopy (fNIRS) is a promising tool for assessing disorders of consciousness (DoC). It provides a portable and cost-effective alternative to fMRI and EEG for measuring brain function. Future research should focus on validation, multimodal integration, and ethical access to enhance DoC care.

fNIRS, disorders of consciousness, neuroimaging, brain-computer interfaces

Publication

A reference-less level-crossing adc with a bump-based adaptive-bias comparator

Patent published on the 2026-04-22 in EP under Ref EP4730654 by IMEC VZW [BE] (Yang Xiaolin [be], Xing Xiaonan [be], Sawigun Chutham [be], Mora Lopez Carolina [be])

Abstract: This disclosure relates to a comparator circuit and an ADC circuit for a neural interface. The ADC circuit includes the comparator circuit. The comparator circuit comprises a comparator to receive a first and a second signal, and internally amplify the first and the second signal. A bump bias circuit of the comparator circuit receives the amplified first and second signal, and causes the comparator to operate at a higher power level when a difference between the amplified first and second signal[...]


Our summary: The disclosure describes a reference-less level-crossing ADC featuring a bump-based adaptive-bias comparator. The comparator amplifies two input signals and adjusts its power level based on their difference. The ADC includes two comparator circuits and switching circuits controlled by a control circuit for capacitor state management.

ADC, comparator, adaptive-bias, neural interface

Patent

All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex

Published on 2026-04-17 by @MIT

Abstract: AbstractIntracranial electrophysiology offers a unique insight into the nature of information representation in the brain—it can be used to disentangle information encoded in gamma and high gamma frequencies from information encoded in lower frequencies. We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human ventral anterior temporal lobe (vATL). Power in gamma[...]


Our summary: Neural activity in the anterior ventral temporal cortex encodes semantic information across various spectral frequencies. Intracranial electrophysiology reveals that gamma and high gamma frequencies contribute to reliable decoding of animacy. A broader frequency range enhances decoding accuracy, supporting the concept of a local vATL hub interacting with distributed cortical spokes.

neural activity, semantic representation, electrocorticography, frequency decoding

Publication

Brain-computer interface system and method

Patent published on the 2026-03-26 in WO under Ref WO2026064733 by SCIENCE CORP [US] (Rostov Marat [us], Slager Nate [us], Walker Sage [us], Hodak Max [us], Sharpe Russell [us], Zhou Emma [us], Elsen Antonia [us])

Abstract: Variants of the system can include: a probe and an interface device. Variants of the method can include: configuring a signal pipeline and executing the signal pipeline. In variants, the system and/or method can function to record neural signals from a variety of brain-computer interface (BCI) probe devices. In a specific example, the system and/or method can enable high bandwidth neural recording and processing for BCI experiments.[...]


Our summary: The content describes a brain-computer interface system and method that includes a probe and an interface device. It details the configuration and execution of a signal pipeline to record neural signals from BCI devices. The system aims to enable high bandwidth neural recording and processing for BCI experiments.

brain-computer interface, neural signals, signal pipeline, high bandwidth

Patent

A novel hybrid BCI system combining single-channel SSVEP and PLR to improve classification accuracy and ITR

Published on 2026-03-24 by @OXFORD

Abstract: AbstractSteady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) have been widely studied because they provide high classification accuracy and information transfer rate (ITR) without requiring user training. To further enhance BCI performance, this study proposes a novel hybrid BCI that integrates single-channel SSVEP with the pupillary light reflex (PLR). Twelve healthy subjects participated in experiments involving three paradigms: SSVEP, PLR, and hybrid. Each sub[...]


Our summary: This study presents a hybrid BCI system that combines single-channel SSVEP and PLR to enhance classification accuracy and information transfer rate. The hybrid paradigm achieved a classification accuracy of 95.70%, outperforming both SSVEP and PLR methods. Results indicate that this approach can significantly improve BCI performance, potentially facilitating broader adoption.

BCI, SSVEP, PLR, classification

Publication

Neurophysiological screening of individual variability for robust decoding in c-VEP-based BCI

Published on 2026-03-20 by @MIT

Abstract: AbstractCode-modulated visual evoked-potential (c-VEP)-based reactive brain–computer interfaces (BCIs) deliver high information-transfer rates with minimal calibration, yet performance often collapses when models are transferred between users. We, therefore, pursue a two-fold aim: first, to pinpoint neurophysiological predictors that explain this inter-participant variability; second, to identify a decoding pipeline that sustains accuracy across users in a burst-c-VEP paradigm (brief, aperiodi[...]


Our summary: This study identifies neurophysiological predictors of inter-participant variability in c-VEP-based BCIs. It establishes a decoding pipeline that maintains accuracy across users using a lightweight approach. The proposed method achieves high trial-level accuracy while minimizing calibration time.

neurophysiology, brain-computer interface, visual evoked potential, decoding pipeline

Publication

取り上げるトピック: 脳コンピュータインターフェース、神経組織、外部計算システム、非侵襲的モダリティ、皮質脳波記録、皮質内アプローチ、信号処理パイプライン、スパイクソーティング、深層学習デコーダ、閉ループアーキテクチャ、神経刺激、生体適合性研究、臨床試験、神経テレメトリ、運動皮質デコーディング、音声合成、電極材料科学、ISO 13485、ISO 14971、IEC 60601、ISO/IEC 27001、およびISO 9001。

用語集

Brain-Computer Interface (BCI): 脳と外部機器との直接通信を可能にするシステムであり、神経活動を通してテクノロジーを制御することを可能にする。通常、信号の取得、処理、そして補助機器や神経補綴装置などのアプリケーション向けのコマンドへの変換が含まれる。

歴史的背景

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(日付が不明または関連性がない場合、例えば「流体力学」などでは、その注目すべき出現時期の概算値が提示されます。)

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