Detecting anomalies in activities of daily living of elderly residents via energy disaggregation and Cox processes

Monitoring the health of the elderly living independently in their own homes is a key issue in building sustainable healthcare models which support a country’s ageing population. Existing approaches have typically proposed remotely monitoring the behaviour of a household’s occupants through the use of additional sensors. However the costs and privacy concerns of such sensors have significantly limited their potential for widespread adoption. In contrast, in this paper we propose an approach which detects Activities of Daily Living, which we use as a proxy for the health of the household residents. Our approach detects appliance usage from existing smart meter data, from which the unique daily routines of the household occupants are learned automatically via a log Gaussian Cox process. We evaluate our approach using two real-world data sets, and show it is able to detect over 80% of kettle uses while generating less than 10% false positives. Furthermore, our approach allows earlier interventions in households with a consistent routine and fewer false alarms in the remaining households, relative to a fixed-time intervention benchmark

An investigation of electronic Protected Health Information (e-PHI) privacy policy legislation in California for seniors using in-home health monitoring systems

This study examined privacy legislation in California to identify those electronic Protected Health Information (e-PHI) privacy policies that are suited to seniors using in-home health monitoring systems. Personal freedom and independence are essential to a person\u27s physical and mental health, and mobile technology applications provide a convenient and economical method for monitoring personal health. Many of these apps are written by third parties, however, which poses serious risks to patient privacy. Current federal regulations only cover applications and systems developed for use by covered entities and their business partners. As a result, the responsibility for protecting the privacy of the individual using health monitoring apps obtained from the open market falls squarely on the states. The goal of this study was to conduct an exploratory study of existing legislation to learn what was being done at the legislative level to protect the security and privacy of users using in-home mobile health monitoring systems. Specifically, those developed and maintained by organizations or individuals not classified as covered entities under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). The researcher chose California due to its reputation for groundbreaking privacy laws and high population of seniors. The researcher conducted a content analysis of California state legislation, federal and industry best practices, and extant literature to identify current and proposed legislation regarding the protection of e-PHI data of those using in-home health monitoring systems. The results revealed that in-home health monitoring systems show promise, but they are not without risk. The use of smartphones, home networks, and downloadable apps puts patient privacy at risk, and combining systems that were not initially intended to function together carries additional concerns. Factors such as different privacy-protection profiles, opt-in/opt-out defaults, and privacy policies that are difficult to read or are not adhered to by the application also put user data at risk. While this examination showed that there is legislative support governing the development of the technology of individual components of the in-home health monitoring systems, it appears that the in-home health monitoring system as a whole is an immature technology and not in wide enough use to warrant legislative attention. In addition – unlike the challenges posed by the development and maintenance of the technology of in-home health monitoring systems – there is ample legislation to protect user privacy in mobile in-home health monitoring systems developed and maintained by those not classified as covered entities under HIPAA. Indeed, the volume of privacy law covering the individual components of the system is sufficient to ensure that the privacy of the system as a whole would not be compromised if deployed as suggested in this study. Furthermore, the legislation evaluated over the course of this study demonstrated consistent balance between technical, theoretical, and legal stakeholders. This study contributes to the body of knowledge in this area by conducting an in-depth review of current and proposed legislation in the state of California for the past five years. The results will help provide future direction for researchers and developers as they struggle to meet the current and future needs of patients using this technology as it matures. There are practical applications for this study as well. The seven themes identified during this study can serve as a valuable starting point for state legislators to evaluate existing and proposed legislation within the context of medical data to identify the need for legislation to assist in protecting user data against fraud, identity theft, and other damaging consequences that occur because of a data breach

Contribuitions and developments on nonintrusive load monitoring

Energy efficiency is a key subject in our present world agenda, not only because of greenhouse gas emissions, which contribute to global warming, but also because of possible supply interruptions. In Brazil, energy wastage in the residential market is estimated to be around 15%. Previous studies have indicated that the most savings were achieved with specific appliance, electricity consumption feedback, which caused behavioral changes and encouraged consumers to pursue energy conservation. Nonintrusive Load Monitoring (NILM) is a relatively new term. It aims to disaggregate global consumption at an appliance level, using only a single point of measurement. Various methods have been suggested to infer when appliances are turned on and off, using the analysis of current and voltage aggregated waveforms. Within this context, we aim to provide a methodology for NILM to determine which sets of electrical features and feature extraction rates, obtained from aggregated household data, are essential to preserve equivalent levels of accuracy; thus reducing the amount of data that needs to be transferred to, and stored on, cloud servers. As an addendum to this thesis, a Brazilian appliance dataset, sampled from real appliances, was developed for future NILM developments and research. Beyond that, a low-cost NILM smart meter was developed to encourage consumers to change their habits to more sustainable methods.Eficiência energética é um assunto essencial na agenda mundial. No Brasil, o desperdício de energia no setor residencial é estimado em 15%. Estudos indicaram que maiores ganhos em eficiência são conseguidos quando o usuário recebe as informações de consumo detalhadas por cada aparelho, provocando mudanças comportamentais e incentivando os consumidores na conservação de energia. Monitoramento não intrusivo de cargas (NILM da sigla em inglês) é um termo relativamente novo. A sua finalidade é inferir o consumo de um ambiente até observar os consumos individualizados de cada equipamento utilizando-se de apenas um único ponto de medição. Métodos sofisticados têm sido propostos para inferir quando os aparelhos são ligados e desligados em um ambiente. Dentro deste contexto, este trabalho apresenta uma metodologia para a definição de um conjunto mínimo de características elétricas e sua taxa de extração que reduz a quantidade de dados a serem transmitidos e armazenados em servidores de processamento de dados, preservando níveis equivalentes de acurácia. São utilizadas diferentes técnicas de aprendizado de máquina visando à caracterização e solução do problema. Como adendo ao trabalho, apresenta-se um banco de dados de eletrodomésticos brasileiros, com amostras de equipamentos nacionais para desenvolvimentos futuros em NILM, além de um medidor inteligente de baixo custo para desagregação de cargas, visando tornar o consumo de energia mais sustentável

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine