Alanazi Turki M, Alduaiji Noha, Lhioui Chahira, Hamdaoui Rim, Asklany Somia, Hamdi Monia, Elrashidi Ali, Abbas Ghulam
Department of Electrical Engineering, College of Engineering, University of Hafr Al Batin, Hafr Al Batin, Saudi Arabia.
Department of Computer Science, College of Computer and Information Sciences, Majmaah University, Majmaah, Saudi Arabia.
PLoS One. 2025 Jul 11;20(7):e0327942. doi: 10.1371/journal.pone.0327942. eCollection 2025.
Wearable sensor (WS) technology in healthcare is essential because it makes medical diagnosis easier by continuously monitoring important changes in an individual's body. This technology is used to detect aberrant occurrences and predict medical dangers. A central connecting unit is used to stream and send accurate observations to improve the quality of medical diagnosis. In this paper, we present a Fair Dividend Interrupt Method (FDIM), a new way to arrange and improve the efficiency of combining WS inputs. This approach employs federated learning to prioritize interruptions based on their importance and WS criteria. This leads to well-structured streaming periods across numerous connecting devices, guaranteeing continuous sequences. The sequence determination uses balanced linear scheduling, optimizing the structure of sensing operations and increasing WS input availability when interruptions from multiple sensors, thereby boosting operating efficiency. The proposed approach outperforms baseline methods in access time, computational complexity, data utilization, processing time, aggregation ratio, and error rate by 10.18%, 5.19%, 10.57%, 8.48%, and 10.42%, respectively. Due to these developments, FDIM is now a highly efficient, scalable solution for wearable healthcare systems that allows accurate medical decision-making.
可穿戴传感器（WS）技术在医疗保健领域至关重要，因为它通过持续监测个体身体的重要变化，使医疗诊断更加容易。该技术用于检测异常情况并预测医疗风险。一个中央连接单元用于传输并发送准确的观测数据，以提高医疗诊断的质量。在本文中，我们提出了一种公平股息中断方法（FDIM），这是一种安排和提高WS输入组合效率的新方法。这种方法采用联邦学习，根据中断的重要性和WS标准对其进行优先级排序。这导致跨多个连接设备的结构化流传输周期，确保连续序列。序列确定使用平衡线性调度，优化传感操作的结构，并在多个传感器产生中断时提高WS输入的可用性，从而提高运行效率。所提出的方法在访问时间、计算复杂度、数据利用率、处理时间、聚合率和错误率方面分别比基线方法提高了10.18%、5.19%、10.57%、8.48%和10.42%。由于这些进展，FDIM现在是一种高效、可扩展的可穿戴医疗系统解决方案，能够实现准确的医疗决策。
