微型胶囊通过多波长光学传感与边缘AI，实现胃出血流速的定量分类。
A Capsule-Sized Multi-Wavelength Wireless Optical System for Edge-AI-Based Classification of Gastrointestinal Bleeding Flow Rate
- 采用多波长透射光谱结合轻量卷积网络，在设备端实时分类出血流速。
- 体外实验中对多种流速等级分类准确率达98.75%，且可区分非血液干扰物。
- 嵌入式推理使能耗降低88%，支持长时间电池供电监测，适合术后连续追踪。
内镜治疗后72小时内常发生再出血，仍是早期发病率和死亡率的主要原因。现有无创监测方法多仅提供二元血检结果，缺乏对出血严重程度或流速动态的量化评估，难以在高风险期支持及时临床决策。本文开发了一种微型胶囊式、多波长光学无线传感平台，利用透射光谱与低功耗边缘人工智能，实现对胃肠道出血流速的量级分类。系统进行时序多光谱测量，并采用轻量二维卷积神经网络在设备端完成流速分类，物理机制验证表明其结果与血红蛋白波长依赖性吸收行为一致。在模拟胃部条件的体外实验中，该方法在多个流速等级上整体分类准确率达98.75%，并能稳健区分多种非血液胃肠干扰物。通过在胶囊电子系统内直接执行推理，相比持续无线传输原始数据，整体能耗降低约88%，使长时间电池供电运行成为可能。该平台将胶囊诊断从二元血检拓展至连续、局部的出血严重程度评估，有望在术后随访中更早识别有临床意义的再出血，指导及时再干预。
原文摘要 · Abstract (English)
Post-endoscopic gastrointestinal (GI) rebleeding frequently occurs within the first 72 hours after therapeutic hemostasis and remains a major cause of early morbidity and mortality. Existing non-invasive monitoring approaches primarily provide binary blood detection and lack quantitative assessment of bleeding severity or flow dynamic, limiting their ability to support timely clinical decision-making during this high-risk period. In this work, we developed a capsule-sized, multi-wavelength optical sensing wireless platform for order-of-magnitude-level classification of GI bleeding flow rate, leveraging transmission spectroscopy and low-power edge artificial intelligence. The system performs time-resolved, multi-spectral measurements and employs a lightweight two-dimensional convolutional neural network for on-device flow-rate classification, with physics-based validation confirming consistency with wavelength-dependent hemoglobin absorption behavior. In controlled in vitro experiments under simulated gastric conditions, the proposed approach achieved an overall classification accuracy of 98.75% across multiple bleeding flow-rate levels while robustly distinguishing diverse non-blood gastrointestinal interference. By performing embedded inference directly on the capsule electronics, the system reduced overall energy consumption by approximately 88% compared with continuous wireless transmission of raw data, making prolonged, battery-powered operation feasible. Extending capsule-based diagnostics beyond binary blood detection toward continuous, site-specific assessment of bleeding severity, this platform has the potential to support earlier identification of clinically significant rebleeding and inform timely re-intervention during post-endoscopic surveillance.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。