Seamless tracing of human behavior using complementary wearable and house-embedded sensors.
This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system.
AGH-University of Science and Technology, 30, Mickiewicz Ave., 30-059 Kraków, Poland. august@agh.edu.pl.
Piotr
P
Augustyniak
AGH-University of Science and Technology, 30, Mickiewicz Ave., 30-059 Kraków, Poland. msmolen@agh.edu.pl.
Magdalena
M
Smoleń
AGH-University of Science and Technology, 30, Mickiewicz Ave., 30-059 Kraków, Poland. zibi@agh.edu.pl.
Zbigniew
Z
Mikrut
AGH-University of Science and Technology, 30, Mickiewicz Ave., 30-059 Kraków, Poland. kantoch@agh.edu.pl.
Eliasz
E
Kańtoch
D061725:Accelerometry / Q000295:instrumentation*; D056044:Actigraphy / Q000295:instrumentation*; D001519:Behavior / Q000502:physiology*; D003195:Computer Communication Networks / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000295:instrumentation*; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D018511:Systems Integration; D014741:Video Recording / Q000295:instrumentation*