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OBJECTIVE The goal of this effort was to investigate the feasibility of applying the ISO/IEEE 11073 (a.k.a. X73) standards, originally intended for bedside monitoring in hospital environments, to wearable, multi-sensor monitoring systems designed for home healthcare. METHODS The X73 upper-layer sub-standards (i.e., nomenclature specification, domain(More)
A point-of-care system for continuous health monitoring should be wearable, easy to use, and affordable to promote patient independence and facilitate acceptance of new home healthcare technology. Reconfigurability, interoperability, and scalability are important. Standardization supports these requirements, and encourages an open market where lower product(More)
Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight, intelligent physiological sensor platforms that can be seamlessly integrated into a body area network for health monitoring. Wireless body area networks (WBANs) promise unobtrusive ambulatory(More)
Motion artifact reduction and separation become critical when medical sensors are used in wearable monitoring scenarios. Previous research has demonstrated that independent component analysis (ICA) can be applied to pulse oximeter signals to separate photoplethysmographic (PPG) data from motion artifacts, ambient light, and other interference in low-motion(More)
Wireless body area networks (WBANs) and their supporting information infrastructures offer unprecedented opportunities to monitor state of health without constraining the activities of a wearer. These mobile point-of-care systems are now realizable due to the convergence of technologies such as low-power wireless communication standards, plug-and-play(More)
An automated hand-forearm ergometer with realtime data analysis would be a helpful tool to evaluate muscle fatigue mid-experiment, offering insights into changes in electromyogram parameters that can be used to track fatigue in the hand and forearm musculature. This work presents real-time additions to a custom, automated hand-forearm ergometer that will(More)
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