Electronics Department, University of Alcalá, Escuela Politécnica, Ctra. Madrid-Barcelona, Km. 33,600, 28871 Alcalá de Henares, Spain.
Sensors (Basel). 2017 Feb 11;17(2):351. doi: 10.3390/s17020351.
The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people' demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented.
人口老龄化以及他们越来越希望独立生活，这促使福利和医疗保健模式得到了发展。现有的基于使用身体传感器网络（BSN）直接进行健康监测的方法精确且准确。尽管如此，其侵入性导致了人们的不接受。新的方法通过监测日常生活活动（ADL）来寻求间接监测，事实证明这是一种合适的解决方案。ADL 监测系统使用许多异构传感器，侵入性较小，成本也低于 BSN，但无线传感器网络（WSN）的部署和维护阻止了它们的广泛接受。在这项工作中，提出了一种基于非侵入式负载监测（NILM）的新型人类活动监测技术。该提案仅使用智能电表数据，这导致最小的侵入性和潜在的大规模部署，成本最小。这可能是为智能家居开发可持续医疗保健模式的关键，这些模式能够满足老年人的需求。本研究还使用 Dempster-Shafer 理论来提供关于正常行为的日常评分。该方法已使用真实数据集进行了评估，并与高斯混合模型方法进行了基准测试。
