Optimal Allocation of Time-Resources for Multihypothesis Activity-Level Detection
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Optimal time-resource allocation for activity-detection via multimodal sensing
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
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It is estimated that by the year 2010, the number of people over 65 years of age will reach 39 million. By 2030, that number is expected to over 70 million individuals in the 85 and older age group making them the fastest growing group of older individuals. Their growth rate is three times more than all of the 65 and older age groups put together. Falls and mobility issues are very common among older individuals and can have severe consequences. In older individuals, falls and mobility issues can occur as a result of normal age related changes such as changes in vision, gait, strength, disease progression, and medication. We introduce wireless microcontroller hardware and software that leverages micro electro mechanical system (MEMS) transducers which communicate with a server-based heuristics analytics system. The real-time heuristics analytics system performs correlation analysis which will allow for measuring and detecting of mobility related events correlated with, for example, specific disease progression and/or changes in medication dosing and scheduling. If there is excessive inactivity detected within a selected time period, notification will be sent by the heuristics analytics system to a response center.