Improving the quality of healthcare and the prospects of "aging in place" using wireless sensor technology requires solving difficult problems in scale, energy management, data access, security, and privacy. We present AlarmNet, a novel system for assisted-living and residential monitoring that uses a two-way flow of data and analysis between the front and back-ends to enable context-aware protocols that are tailored to residents' individual patterns of living.AlarmNet integrates environmental, physiological, and activity sensors in a scalable, heterogeneous architecture.The SenQ query protocol provides real-time access to data and lightweight in-network processing. Circadian Activity Rhythm (CAR) analysis learns resident activity patterns and feeds them back into the network to aid context-aware power management and dynamic privacy policies.
Abstract-Advances in semiconductor technology have resulted in the creation of miniature medical embedded systems that can wirelessly monitor the vital signs of patients. These lightweight medical systems can aid providers in large disasters who become overwhelmed with the large number of patients, limited resources, and insufficient information. In a mass casualty incident, small embedded medical systems facilitate patient care, resource allocation, and real-time communication in the Advanced Health and Disaster Aid Network (AID-N). We present the design of electronic triage tags on lightweight, embedded systems with limited memory and computational power. These electronic triage tags use noninvasive, biomedical sensors (pulse oximeter, electrocardiogram, and blood pressure cuff) to continuously monitor the vital signs of a patient and deliver pertinent information to first responders. This electronic triage system facilitates the seamless collection and dissemination of data from the incident site to key members of the distributed emergency response community. The real-time collection of data through a mesh network in a mass casualty drill was shown to approximately triple the number of times patients that were triaged compared with the traditional paper triage system.
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