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: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573778
• 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. In response to these challenges, we propose novel information processing strategies conducive to a "smart" health monitoring system (SHMS) embodying these design principles: (i) resource efficiency, to alleviate limited resources; (ii) variable quality of service provision, to cope with varying application scenarios; (iii) recharging regime, to exploit the renewable energy potential; (iv) security and privacy, to prevent unauthorized access. Due to its adaptivity, the SHMS platform is also applicable to other contexts besides healthcare, including workplace safety, multimedia education and entertainment, as well as law enforcement and military operations. In this research program, the focus will be first on healthcare, with other contexts considered as future extensions. This is a logical and practical selection, since telemedicine and healthcare facilities offer high-impact application scenarios for SHMS. Indeed, providing an efficient healthcare environment, which directly affects human quality of life, has always been a challenging but worthy pursuit. The successful application of SHMS for healthcare would represent not only technical advances but also social progress.

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。 为了应对这些挑战，我们提出了新的信息处理策略，有利于“智能”健康监测系统（SHMS）体现这些设计原则：（i）资源效率，以减轻有限的资源;（ii）可变的服务质量提供，以科普不同的应用场景;（iii）充电制度，以利用可再生能源的潜力;（iv）保安及私隐，以防止未经授权的取用。由于其适应性，SHMS平台也适用于医疗保健以外的其他环境，包括工作场所安全，多媒体教育和娱乐，以及执法和军事行动。在该研究计划中，重点将首先放在医疗保健上，其他背景被视为未来的扩展。这是一个合乎逻辑和实用的选择，因为远程医疗和医疗保健设施为SHMS提供了高影响力的应用场景。事实上，提供一个高效的医疗环境，直接影响人类的生活质量，一直是一个具有挑战性但值得追求的目标。SHMS在医疗保健领域的成功应用不仅代表着技术的进步，也代表着社会的进步。