The Internet of Medical Things (IoMT) enables intelligent healthcare services but faces challenges such as dynamic topology, energy constraints, and diverse QoS requirements. This paper proposes QQMR, a Q-learning-based QoS-aware multipath routing method for WBANs. QQMR classifies data into three priority levels and employs adaptive multi-level queuing and fuzzy C-means clustering to optimize routing decisions. It maintains separate learning policies for each data type and selects primary and backup paths accordingly. Experimental results demonstrate improved packet delivery ratio and significant reductions in delay, routing overhead, and energy consumption compared to existing methods.

翻译：医疗物联网（IoMT）能够提供智能医疗服务，但面临动态拓扑、能量约束及多样化QoS需求等挑战。本文提出QQMR——一种基于Q学习的QoS感知WBAN多路径路由方法。QQMR将数据划分为三个优先级等级，采用自适应多级队列和模糊C均值聚类优化路由决策。该方法为每种数据类型维护独立的学习策略，并据此选择主路径和备用路径。实验结果表明，与现有方法相比，该方法在提升数据包投递率的同时，显著降低了延迟、路由开销和能耗。