RESUMEN

Remote monitoring of health and mobility is critical in the support of aging-in-place for seniors. However, it is challenging to passively monitor individuals in multi-resident homes. In this paper we present a new method for the identification of individuals using simple wall-mounted radio frequency (RF) transceivers and IR sensors with fingerprinting techniques. The approach is passive or device-free in that it does not require the person being identified to wear any transmitting device Classification is achieved using features derived from measuring the disruption of RF received signal strength (RSS) among 4 transceivers positioned across either a hallway or doorframe. Three IR sensors provide timing information. Results are given for 3 test subjects (1 female, 2 males). The approach achieves over 98% classification accuracy in distinguishing the female from the male subjects and over 83% in distinguishing between the males using a Gaussian Mixture Model for classification. More than 2300 labeled examples per subject were used for training. When the training data is reduced to less than 140 examples per subject, 96% and 82% classification accuracy is still achieved respectively.

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RESUMEN

We present a device-free indoor tracking system that uses received signal strength (RSS) from radio frequency (RF) transceivers to estimate the location of a person. While many RSS-based tracking systems use a body-worn device or tag, this approach requires no such tag. The approach is based on the key principle that RF signals between wall-mounted transceivers reflect and absorb differently depending on a person's movement within their home. A hierarchical neural network hidden Markov model (NN-HMM) classifier estimates both movement patterns and stand vs. walk conditions to perform tracking accurately. The algorithm and features used are specifically robust to changes in RSS mean shifts in the environment over time allowing for greater than 90% region level classification accuracy over an extended testing period. In addition to tracking, the system also estimates the number of people in different regions. It is currently being developed to support independent living and long-term monitoring of seniors.

RESUMEN

In this paper we present a new method for passively measuring walking speed using a small array of radio transceivers positioned on the walls of a hallway within a home. As a person walks between a radio transmitter and a receiver, the received signal strength (RSS) detected by the receiver changes in a repeatable pattern that may be used to estimate walking speed without the need for the person to wear any monitoring device. The transceivers are arranged as an array of 4 with a known distance between the array elements. Walking past the first pair of transceivers will cause a peak followed by a second peak when the person passes the second pair of transceivers. The time difference between these peaks is used to estimate walking speed directly. We further show that it is possible to estimate the walking speed by correlating the shape of the signal using a single pair of transceivers positioned across from each other in a hallway or doorframe. RMSE performance was less than 15 cm/s using a 2-element array, and less than 8 cm/s using a 4-element array relative to a gait mat used for ground truth.

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