Information Processing and Optimization for Smart Health Monitoring Systems

管理生理数据的需求在许多工程系统中很普遍，特别是在医疗保健系统中。最近在相互交织的研究领域也取得了进展，导致了一个具有深远影响的技术平台的出现：体域网络（BAN），它代表了许多领域的融合，包括仪器仪表、计算机科学和通信。然而，自成立以来，该平台面临的主要挑战是资源限制，例如能源、带宽和计算复杂性。与ban相关的人为因素在安全和隐私方面也具有独特的影响，因为经常涉及个性化的医疗数据。此外，针对有限的能源资源，探索了能量收集和储存等可再生策略。虽然可充电设备允许提高资源效率的潜力，但这种可能性只有在底层信息处理算法得到相应优化的情况下才能完全实现。

The need to manage physiological data is prevalent in many engineering systems, especially those in healthcare. There have also been recent advances in intertwined research areas, leading to the emergence of a technological platform with far-reaching implications: the body-area network (BAN), which represents the convergence of many fields, including instrumentation, computer science, and communications. However, since inception, a major challenge of the platform has been the resource constraints, e.g., energy, bandwidth and computational complexity. The human factor associated with BANs also carries unique implications with respect to security and privacy, since personalized medical data are often involved. In addition, to target the limited energy resource, renewable strategies such as energy harvesting and storage have been explored. While rechargeable devices allow for the potential of improved resource efficiency, this possibility is only fully realized if the underlying information processing algorithms are optimized accordingly.