Information Processing and Optimization for Smart Health Monitoring Systems

智能健康监测系统的信息处理和优化

• 批准号: 418666-2013
• 负责人: Bui, Francis
• 金额: $ 1.82万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=531304
• 关键词: Information; Processing; Optimization; Smart; Health

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.

管理生理数据的需求在许多工程系统中普遍存在，特别是在医疗保健领域。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（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，该平台的一个主要挑战是资源限制，例如，能量、带宽和计算复杂度。与BAN相关的人为因素也对安全和隐私产生了独特的影响，因为通常涉及个性化的医疗数据。此外，针对有限的能源资源，已探索可再生能源战略，如能源收集和储存。虽然可再充电设备允许提高资源效率的潜力，但只有在相应地优化底层信息处理算法的情况下，才能完全实现这种可能性。