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Implementing and validating an environmental and health monitoring system

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This article has been cited by other articles in PMC. Others have described overall security challenges in health-monitoring systems [ 4 ], and initial ideas for protecting health-data integrity [ 11 ], but an in-depth and realistic analysis of the problem is lacking in the literature. Abstract As the nation's healthcare information infrastructure continues to evolve, new technologies promise to provide readily accessible health information that can help people address personal and community health concerns. To design a secure health-monitoring system, we first need to understand what determines the quality of the medical sensor data and how we can quantify the degree of the data quality. Concerns about privacy and information quality, however, may impede the development and deployment of these technologies for remote health monitoring. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For evaluation, we will implement a proof of concept for secure health monitoring. When the data is used for medical research or epidemiological studies, public health can be endangered. The problem becomes harder when the hardware or software components are integrated into a personal device such as a cellular phone, a PDA, or a smart watch. Received May 17; Accepted May

Implementing and validating an environmental and health monitoring system


To design a quality-control framework, we first analyzed the health-monitoring system as a sequence of processes, assigned related factors to each process, and then identified possible methods for the quality control of individual factors. Quality Control Framework In this section, we design a quality-control framework based on the risk analysis in the previous section. Others have described overall security challenges in health-monitoring systems [ 4 ], and initial ideas for protecting health-data integrity [ 11 ], but an in-depth and realistic analysis of the problem is lacking in the literature. Such devices have limited security features and are vulnerable to unauthorized access; some security mechanisms like TPM [ 8 , 9 ] may be too restrictive and difficult to use. There are many opportunities for the data to become lost, damaged, forged, or exposed: Privacy and information quality, however, are two major concerns in the development and deployment of remote health-monitoring systems [ 4 , 5 ]. The problem is especially challenging, given the difficulty of hardening low-cost sensors and the personal devices that collect, process, and forward the medical data, and given that all such devices will communicate over wireless networks. Fortunately, present information technology brings us the hope that significant improvements in the public' health and wellbeing are not only possible but close at hand. Education helps, but people make mistakes and many fail to implement security practices [ 7 ]. Concerns about privacy and information quality, however, may impede the development and deployment of these technologies for remote health monitoring. In this paper, we design a framework for secure remote health-monitoring systems; we build a realistic risk model for sensor-data quality and propose a new health-monitoring architecture that is secure despite the weaknesses of common personal devices. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Specifically, we want to i build a realistic risk model for sensor-data quality, by interacting with health professionals, ii develop protocols and mechanisms for data protection and quality assurance, and iii propose a new health-monitoring architecture that is secure despite the weaknesses of common personal devices. The problem is difficult due to the lack of control over the situation at the patient's end. Introduction The nation has an urgent need to build a national healthcare information infrastructure NHII that provides health information to all who need to make sound decisions about health [ 1 ]. Abstract As the nation's healthcare information infrastructure continues to evolve, new technologies promise to provide readily accessible health information that can help people address personal and community health concerns. The problem becomes harder when the hardware or software components are integrated into a personal device such as a cellular phone, a PDA, or a smart watch. The use of dedicated devices, however, would be costly, has limited flexibility, and may reduce patient participation. Insufficient data integrity may cause health professionals to mistrust the data and may make them reluctant to use devices that may, otherwise, be beneficial to patient health. To be viable, any such system must provide usable devices that respect patient privacy while also retaining data quality required for the medical purpose it serves. The framework is a set of processes that ensure, verify, and evaluate the data quality. As a preliminary analysis, we recently identified eleven factors that can affect the quality of medical sensor data [ 5 ] see next section for detail. Medical sensing begins with sensing the physiology of the patient sense process. Upon receiving the data from the device, the provider's server evaluates the validity of the data verify process and then presents the data to the provider. Given the time available one year , we will focus most on the data-quality issues. When the data is inappropriately disclosed, it may expose the patient's medical problems, and details of treatments underway.

Implementing and validating an environmental and health monitoring system


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