一种用于基于边缘AI的胃肠道出血流速分类的胶囊式多波长无线光学系统
A Capsule-Sized Multi-Wavelength Wireless Optical System for Edge-AI-Based Classification of Gastrointestinal Bleeding Flow Rate
AI总结：
本研究提出一种胶囊式多波长无线光学系统，利用边缘AI实现胃肠道出血流速的高精度分类，提升临床决策支持能力。
摘要：
内镜后胃肠道再出血常在治疗止血后的前72小时内发生，仍然是早期发病率和死亡率的主要原因。现有的非侵入式监测方法主要提供二进制血液检测，缺乏对出血严重程度或流体动态的定量评估，限制了其在这一高风险时期支持及时临床决策的能力。在本工作中，我们开发了一种胶囊式、多波长光学传感无线平台，用于对胃肠道出血流速进行数量级级别的分类，利用传输光谱学和低功耗边缘人工智能。该系统进行时间分辨的多光谱测量，并采用轻量级的二维卷积神经网络进行设备上的流速分类，基于物理的验证确认与波长相关的血红蛋白吸收行为一致。在受控的体外实验中，模拟胃条件下的实验中，所提出的方法在多个出血流速级别上实现了总体分类准确率为98.75%，同时稳健地区分了多种非血液胃肠道干扰。通过在胶囊电子设备上执行嵌入式推断，该系统将整体能耗降低了约88%，相比连续无线传输原始数据，使长时间、电池供电的操作成为可能。将基于胶囊的诊断扩展到二进制血液检测之外，向连续、特定部位评估出血严重程度迈进，该平台有潜力支持更早识别临床显著的再出血，并在内镜后监测期间指导及时重新干预。
英文摘要：
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.
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