Although most studies reported on technical improvements in methods for detecting changes in ADL, few, if any, determined the benefits to the patient of telemonitoring for changes in ADL or correlation with any physiological changes. We propose sensor and system characteristics for improved user acceptance and deployment in a large-scale care plan. We present areas requiring further investigation.
Our results suggest that integrated care monitoring technologies have a potential for providing improved care and can have positive impact on well-being of the elderly by enabling timely intervention. Long-term BP and pulse oximetry data could indicate exacerbation and lead to effective intervention; physical activity data provided important information on the well-being of patients. However, there remains a need for better understanding of long-term variations in vital signs and activity data to establish intervention protocols for improved disease management.
This paper describes the implementation of an end-to-end remote monitoring platform based on the IEEE 11073 standards for personal health devices (PHD). It provides an overview of the concepts and approaches and describes how the standard has been optimized for small devices with limited resources of processor, memory, and power that use short-range wireless technology. It explains aspects of IEEE 11073, including the domain information model, state model, and nomenclature, and how these support its plug-and-play architecture. It shows how these aspects underpin a much larger ecosystem of interoperable devices and systems that include IHE PCD-01, HL7, and BlueTooth LE medical devices, and the relationship to the Continua Guidelines, advocating the adoption of data standards and nomenclature to support semantic interoperability between health and ambient assisted living in future platforms. The paper further describes the adaptions that have been made in order to implement the standard on the ZigBee Health Care Profile and the experiences of implementing an end-to-end platform that has been deployed to frail elderly patients with chronic disease(s) and patients with diabetes.
BackgroundChanges in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data.MethodsOur approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times.ResultsThe User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients.ConclusionsWe observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-014-0102-x) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.