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Elderly care is one of the many applications supported by real-time activityrecognition systems. Traditional approaches use cameras, body sensor networks,or radio patterns from various sources for activity recognition. However, theseapproaches are limited due to ease-of-use, coverage, or privacy preservingissues. In this paper, we present a novel wearable Radio FrequencyIdentification (RFID) system aims at providing an easy-to-use solution withhigh detection coverage. Our system uses passive tags which aremaintenance-free and can be embedded into the clothes to reduce the wearing andmaintenance efforts. A small RFID reader is also worn on the user's body toextend the detection coverage as the user moves. We exploit RFID radio patternsand extract both spatial and temporal features to characterize variousactivities. We also address the issues of false negative of tag readings andtag/antenna calibration, and design a fast online recognition system. Antennaand tag selection is done automatically to explore the minimum number ofdevices required to achieve target accuracy. We develop a prototype systemwhich consists of a wearable RFID system and a smartphone to demonstrate theworking principles, and conduct experimental studies with four subjects overtwo weeks. The results show that our system achieves a high recognitionaccuracy of 93.6 percent with a latency of 5 seconds. Additionally, we showthat the system only requires two antennas and four tagged body parts toachieve a high recognition accuracy of 85 percent.

Toward a Wearable RFID System for Real-Time Activity Recognition Using Radio Patterns