Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains constrained by classical noise limits and a reliance on macroscopic ensembles. We propose a unifying generational framework to organize the evolving landscape of quantum biosensors based on their utilization of quantum resources. First-generation devices utilize discrete energy levels for signal transduction but follow classical scaling laws. Second-generation sensors exploit quantum coherence to reach the standard quantum limit, while third-generation architectures leverage entanglement and spin squeezing to approach Heisenberg-limited precision. We further define an emerging fourth generation characterized by the end-to-end integration of quantum sensing with quantum learning and variational circuits, enabling adaptive inference directly within the quantum domain. By analyzing critical parameters such as bandwidth matching and sensor-tissue proximity, we identify key technological bottlenecks and propose a roadmap for transitioning from measuring physical observables to extracting structured biological information with quantum-enhanced intelligence.

翻译：量子传感技术为超灵敏生物医学感知提供了变革性潜力，但其临床转化仍受限于经典噪声极限和对宏观系综的依赖。我们提出一个统一的代际框架，基于量子资源的利用方式来组织不断演进的量子生物传感器格局。第一代器件利用分立能级进行信号转导，但遵循经典标度律。第二代传感器利用量子相干性达到标准量子极限，而第三代架构则借助纠缠和自旋压缩逼近海森堡极限精度。我们进一步定义了新兴的第四代，其特征是量子传感与量子学习及变分电路的端到端集成，能够在量子域内直接实现自适应推理。通过分析带宽匹配和传感器-组织接近度等关键参数，我们识别出关键技术瓶颈，并提出了一条从测量物理可观测到利用量子增强智能提取结构化生物信息的路线图。