Neural Signal Decoding AI/ML Patent Landscape 2026
The neural signal decoding AI/ML field is in active growth, with annual filings expanding 205% over the measured window and no sign of peak in the evidence. The field remains fragmented — Battelle Memorial Institute leads with 8 patent families, yet the top five filers account for only 19% of the hundred largest filers’ combined total, leaving substantial room for new entrants.
A fragmented, fast-growing field where no single player has locked in a dominant position
Battelle Memorial Institute holds the largest position with 8 patent families, followed by BIOS Health Ltd at 6, and Zander Lab BV, Bennett University, and Zhejiang University each at 5. The corpus spans 139 patent families in total.
The top five filers collectively hold 19% of the hundred largest filers’ combined total — a notably thin concentration for a technology area of this strategic importance. No applicant has established a commanding lead, and the ranking shows a long tail of single-family filers.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | Battelle Memorial Institute | 8 | |
| 2 | BIOS Health Ltd | 6 | |
| 3 | Zander Lab BV | 5 | |
| 4 | Bennett University | 5 | |
| 5 | Zhejiang University | 5 | |
| 6 | Precision Neuroscience Corp | 3 | |
| 7 | Chandigarh University | 3 | |
| 8 | HUAZHONG UNIV OF SCI & TECH | 3 | |
| 9 | SR University | 3 | |
| 10 | Neurosilica Inc | 3 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | Prof. Sathyanarayanan Raman | 2 | |
| 12 | GUANGDONG ARTIFICIAL INTELLIGENCE & DIGITAL ECONOM… | 2 | |
| 13 | SAVEETHA INST OF MEDICAL & TECH SCI | 2 | |
| 14 | Manipal University Jaipur | 2 | |
| 15 | Carnegie Mellon University | 2 | |
| 16 | Strong Force TP Portfolio 2022 LLC | 2 | |
| 17 | Dr. S. Balamurugan | 2 | |
| 18 | Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences | 2 | |
| 19 | Science Corporation | 2 | |
| 20 | X Development LLC | 2 |
The fragmented structure means that a focused filing campaign in a well-defined sub-domain — neural decoding for electrotherapy, for example — could realistically secure a differentiated position. The absence of a dominant incumbent reduces freedom-to-operate barriers for new entrants but also signals that no single architecture or application paradigm has yet achieved consensus.
Filing counts for the most recent 18–24 months are understated due to patent publication lag; the competitive picture at the frontier is likely denser than the numbers suggest. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Filing volume is expanding sharply and AI computing dominates the technology mix
Two structural signals define this field: annual filing volume has grown 205% over the evidence window, and AI computing classes (G06N, G06F) are by far the dominant technical branches, though clinical application classes are a substantial secondary layer.
Annual filing trend
Filing activity grew steadily from 2017 through 2022, then accelerated markedly — 37 families were filed in 2024, the highest single-year count in the dataset. The 2025 and 2026 figures are understated by publication lag and should not be read as a slowdown; the lifecycle evidence confirms the field is still in the growth stage.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G06N (AI models) and G06F (digital data processing) dominate the IPC mix, reflecting the algorithmic core of decoding systems. A61B (diagnosis and surgery) is the largest clinical branch, indicating that signal acquisition and clinical context remain tightly coupled to the ML pipeline. A61N (electrotherapy), G16H (healthcare informatics), and A61F (implants and prostheses) are present but at significantly lower shares, pointing to adjacencies that are active but relatively under-developed.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Adaptive brain-computer interface decoding method …
The present invention discloses an adaptive brain-computer interface decoding method based on multi-model dynamic ensemble, where a traditional state-space model is improved, and a set of measurement functions instead of one fixed measurement function are used to dynamically characterize a relationship between observation variables and state variables; and… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Neural interface | 53 |
| 2 | Stroke Rehabilitation Method and System Using a Br… | 28 |
| 3 | 脑电信号分类模型训练方法、意图识别方法、设备及介质 | 12 |
| 4 | Authentication systems and methods using a brain c… | 9 |
| 5 | 一种基于多模型动态集成的自适应脑机接口解码方法 | 9 |
| 6 | Multi-modal brain-computer interface based system … | 9 |
| 7 | System and method for multi-stage brain-computer i… | 8 |
| 8 | Continuous decoding direct neural interface which … | 7 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the competitive structure means for R&D investment decisions
The combination of rapid growth, low concentration, and a deep AI-first technology stack creates an unusually open competitive window. The four structural reads below translate that evidence into actionable framing.
Early growth stage — strategic positions are still being established
The lifecycle evidence classifies this field as Growth, with annual filings still rising and a 205% expansion over the measured window. The 2024 peak of 37 families in a single year has not yet eased. This is an early-mover window: foundational claim sets filed now have a realistic chance of shaping the prior-art landscape before a dominant architecture consolidates.
Lifecycle: GrowthNo dominant incumbent — the top five hold only 19% of the leading filers’ total
With the top five applicants holding 19% of the hundred largest filers’ combined total, and the leader (Battelle Memorial Institute) at 8 patent families, there is no entrenched fortress to work around. Every applicant in the ranking is a new entrant in momentum terms — none have a multi-cycle compounding lead. This structure favors challengers who can file broadly across a coherent sub-domain rather than compete head-to-head with an established portfolio.
Low concentrationNo co-applicant clusters identified in the evidence
The collaboration evidence contains no co-filing pairs, indicating that cross-institutional joint applications have not yet formed visible clusters in this corpus. This could reflect the field’s early stage, where most applicants are still building proprietary positions before partnering, or it could signal a gap in ecosystem development. Either way, a first-mover who establishes a collaborative filing program — linking clinical institutions with AI labs — would occupy an uncommon structural position.
Evidence pendingIndia leads by filing office; the US and China are the strategically critical markets
India is the lead filing jurisdiction by patent-record count, driven by a large number of academic and individual filers. The United States and China are the next two jurisdictions and represent the primary commercial and regulatory markets for neural interface and BCI products. WIPO (PCT) and Europe (EPO) follow, suggesting that international protection strategies are still being built out. An applicant seeking commercial leverage should prioritize US, China, and PCT filings regardless of where development is headquartered.
India · US · ChinaGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
Co-filing pairs, ranked by the number of jointly-filed patent families.
Battelle leads on AI and electrotherapy breadth; BIOS Health anchors the ML pipeline
All top applicants entered the ranked corpus as new entrants in momentum terms, confirming that no player has yet built a multi-cycle compounding lead. Technology emphasis, rather than portfolio depth, is the primary differentiator at this stage.
Battelle Memorial Institute
Battelle leads with 8 patent families, the largest single applicant position in the corpus. Its technology emphasis spans AI model computing (G06N 3), electrotherapy and radiation therapy (A61N 1), and manipulators and robots (B25J 13), making it the most technically diversified of the top filers. Momentum is classified as a new entrant, with 6 families filed in the recent window — indicating that this position has been built rapidly rather than accumulated over many cycles.
families: 8BIOS Health Ltd
BIOS Health Ltd holds 6 patent families and concentrates its portfolio across electric digital data processing (G06F 3) and AI model computing (G06N 3 and G06N 20) — a signal that its claims are anchored in the ML pipeline for neural decoding rather than the clinical hardware layer. This software-centric positioning differentiates it from Battelle’s broader hardware-and-algorithm stack and from Neurosilica’s materials-heavy focus.
families: 6| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| Battelle Memorial Institute | 6 | ▲ new entrant |
| Zhejiang University | 2 | ▲ new entrant |
| Zander Lab BV | 2 | ▲ new entrant |
| Bennett University | 5 | ▲ new entrant |
| Huazhong University of Science and Technology | 1 | ▲ new entrant |
| Precision Neuroscience Corp | 1 | ▲ new entrant |
| Chandigarh University | 3 | ▲ new entrant |
Under-served branches adjacent to the AI decoding core
Several IPC classes sit adjacent to the dominant G06N/G06F core but carry relatively few patent families. These represent areas where technical activity exists but prior-art density is low enough that a focused entry could establish a differentiated position.
A61N · Electrotherapy and radiation therapy
With 21 patent records, A61N is the largest of the lower-share branches — present but sparse relative to the AI computing core. Neural decoding outputs that directly drive closed-loop electrotherapy or neurostimulation sit squarely in this class, yet the prior art is thin. Applicants with clinical partnerships and validated decoding pipelines have a plausible entry path: file method claims linking decoded intent signals to stimulation parameter adjustment, a workflow that spans G06N and A61N jointly.
Search this in Eureka →G16H · Healthcare informatics
G16H carries 18 patent records in this corpus — low relative to the volume of clinical data that neural decoding systems generate. Decoded signal streams, longitudinal patient outcome data, and cross-modal biomarker integration are all natural G16H subject matter. The sparse prior art makes this branch attractive for applicants building BCI platforms that couple decoding outputs to electronic health records or population-level analytics; the realistic entry path runs through clinical data standardization claims that complement existing G06N decoding IP.
Search this in Eureka →How top applicants differ by technology route
Route coverage across the main technology branches in the current evidence set.
| Player | G06N 3 · Computing based on AI models | A61B 5 · Diagnosis & surgery | G06F 3 · Electric digital data processing | G06N 20 · Computing based on AI models | A61N 1 · Electrotherapy & radiation therapy |
|---|---|---|---|---|---|
| Bennett University | Strong · 4 | Strong · 4 | Strong · 5 | Strong · 3 | Emerging · 1 |
| Battelle Memorial Institute | Strong · 8 | Absent | Moderate · 3 | Absent | Strong · 5 |
| BIOS Health Ltd | Strong · 5 | Absent | Strong · 5 | Strong · 5 | Absent |
| Zander Lab BV | Strong · 5 | Strong · 3 | Strong · 5 | Absent | Absent |
| Zhejiang University | Strong · 5 | Absent | Strong · 3 | Absent | Absent |
| Dr. Jayashree Prasad | Strong · 2 | Strong · 2 | Strong · 2 | Absent | Absent |
| Precision Neuroscience Corp | Absent | Strong · 3 | Absent | Strong · 2 | Moderate · 1 |
Frequently asked questions
The evidence covers 139 patent families in scope. This is a relatively small corpus by IP standards, consistent with an early-growth field where commercial applications are still being validated.
Battelle Memorial Institute leads with 8 patent families. The second-ranked applicant, BIOS Health Ltd, holds 6. The margin is narrow, and all top applicants are classified as new entrants in momentum terms, meaning no one has compounded a multi-cycle lead.
Annual filings grew 205% over the evidence window, and the lifecycle evidence classifies the field as Growth with filings still rising. The 2025 and 2026 data points are understated by publication lag and should not be read as a real deceleration.
India has the highest patent-record count in the evidence, driven by academic filers. For commercial strategy, the United States and China are the next two jurisdictions and represent the primary BCI and neural interface markets. WIPO (PCT) and Europe (EPO) are present but at lower volumes, suggesting international protection is still being built out.
A61N (electrotherapy and radiation therapy) and G16H (healthcare informatics) are the largest under-served adjacent branches by patent-record count, at 21 and 18 records respectively. A61F (implants and prostheses) and G05B (control and regulating systems) are also sparse. These branches have plausible technical linkage to neural decoding workflows but carry relatively thin prior art.
The collaboration evidence contains no identified co-applicant pairs in this corpus. Cross-institutional joint filing has not yet formed visible clusters, which is consistent with an early-growth field where applicants are building proprietary positions before partnering.
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Disclaimer. This page is generated from PatSnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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