PPubMed12 Jan 2026Cited 3×

Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration

Sheng Wang, Xiaobin Song, Xiaopan Song, Yang Gu, Zhuangzhuang Cong, Yi Shen, Linwei Yu

Abstract

Title: Highlights 1. The latest advancements in neural signal decoding and the integration of flexible bioelectronics for non-invasive brain-computer interfaces are reviewed. 2. Multimodal data fusion, hardware-software co-optimization, and closed-loop control strategies are critical for enhancing the robustness, adaptability, and real-time performance of brain-computer interface (BCI) systems. 3. The robust real-world deployment of BCIs requires breakthroughs in cross-subject generalization, environmental adaptability, and system reproducibility.

A figure from Non-Invasive Brain-Computer Interfaces: Converging Frontiers in Neural Signal Decoding and Flexible Bioelectronics Integration — fig. from the paper

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A review of recent advances in non‑invasive BCI signal decoding and flexible bioelectronics, highlighting multimodal fusion, co‑optimization, and deployment challenges.

What’s new

i.Comprehensive review of state‑of‑the‑art neural signal decoding techniques for non‑invasive BCIs
ii.Survey of flexible bioelectronic materials (e.g., nanowires, hydrogels) and their performance metrics
iii.Identification of key factors—multimodal data fusion, hardware‑software co‑optimization, closed‑loop control—that enhance BCI robustness and real‑time performance
iv.Outline of remaining challenges for real‑world deployment, including cross‑subject generalization, environmental adaptability, and reproducibility

How they did it

The authors performed a literature review, compiling recent studies on neural decoding algorithms, deep‑learning approaches, and flexible nanomaterial‑based electrodes, and synthesized the findings into thematic categories such as multimodal fusion and co‑optimization.

What they found

Ag nanowire electrodes show sheet resistance 2.8 Ω sq⁻¹ (up to 3.6 Ω sq⁻¹) with stretchability up to 40 % while maintaining excellent signal quality
Nickel silicide nanowires achieve conductivity 2 × 10⁶ S m⁻¹, stretchability up to 50 %, and resistance change < ±1.7 % after 10 000 cycles
d‑Sorbitol‑PEDOT/PSS hydrogels reach conductivity > 1 000 S m⁻¹ and stretchability up to 60 % with strain‑insensitive resistance
Multimodal fusion and hardware‑software co‑optimization are highlighted as critical for improving robustness and real‑time performance of BCI systems

Caveats

✕Current non‑invasive BCI systems still lack reliable cross‑subject generalization
✕Environmental adaptability and long‑term reproducibility of flexible electrodes remain insufficiently demonstrated
✕Absence of standardized benchmarks hampers objective comparison of decoding and hardware performance

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