A Statistical Model for the Influence of Body Dynamics on the Gain Pattern of Wearable Antennas in Off-Body Radio Channels

Abstract

The goal of this paper is to address a statistical approach for modelling the influence of body dynamics on the gain pattern of wearable antennas in Body Area Networks, particularly in off-body radio channels. A dynamic model was developed based on Motion Capture data, describing a realistic human body movement. Antennas are located on 4 typical positions (i.e., Head, Chest, Arm and Leg), for which statistics of antenna orientation (i.e., average and standard deviation of elevation and azimuth angles) were calculated for 2 dynamic scenarios, i.e., Walk and Run. Based on the rotation of the antenna, the statistics of gain patterns of a wearable patch antenna operating at 2.45 GHz were calculated. The standard deviation of the change in the antenna orientation is the highest for the Arm location, reaching $$19^{\circ }$$ 19 ? and $$37^{\circ }$$ 37 ? for the Run scenario, for elevation and azimuth angles, respectively. For most of the scenarios, the distribution of the change in antenna orientation fits well to a Kumaraswamy distribution (using the $$\chi ^2_{95\,\%}$$ ? 95 % 2 test). For all antenna positions and the Walk scenario, the standard deviation is $$<4^{\circ }$$ < 4 ? .