We present a new fall-detection method using a floor sensor based on near-field imaging. The test floor had a resolution of 9 × 16. The shape, size, and magnitude of the patterns are used for classification. A test including 650 events and ten people yielded a sensitivity of 91% and a specificity of 91%.
-We analyze the performance of a novel human tracking system, which uses the electric near field to sense human presence. The positioning accuracy with moving targets is measured using raw observations, observation centroids and Kalman filtered centroids. In addition to this, the multi-target discrimination performance is studied with two people and a Rao-Blackwellized Monte Carlo data association algorithm. A reel-based triangulation system is used as the reference positioning system. The mean positioning error for five test subjects walking at different speeds is 21 centimeters. The discrimination performance is 90% when the distance between the two people is over 0.8 meters. With distance over 1.1 meters the discrimination performance is 99%.
In this study, an improved version of the low-frequency indoor location system, with a larger detection range and more durable antenna laminate, is presented. The basic system uses quad antennas, placed under the floor surface, to locate tags with 125-kHz radio signals. The improvements were achieved with a one-layer laminate construction and transmitter electronics that can feed larger currents to the antennas. The measured tag detection height was 2 m, which is adequate for location applications. The low-frequency signal was not affected by normal objects. The tag location reliability of 96.3% was verified with a practical test.
The chapter describes the state of the art and potentialities of near-field imaging (NFI) technology, applications, and nursing tools in health care. First, principles of NFI are discussed. Various uses of NFI sensor data are presented. The data can be used for indoor tracking, automatic fall detection, activity monitoring, bed exit detection, passage control, vital functions monitoring, household automation and other applications. Special attention is given to the techniques and problems in localization, posture recognition, vital functions recording and additional functions for people identification. Examples of statistical analysis of person behavior are given. Three cases of realized applications of NFI technique are discussed.
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