Abstract
Utilizing Impulse Radio Ultra-WideBand (IR-UWB) radar for vital sign monitoring has attracted growing interest due to the noncontact measurement without privacy concerns. Most of existing researches assume that the subject's chest is directed to the radar antenna, to ensure the strength of backscattered signals from chest movement. However, a large angle between the antenna and the subject's chest caused by the body orientation badly affects the monitoring accuracy. Multiple observations of the same cardiopulmonary activity from different orientations provide more available measurements. This paper addresses the challenge by using an IR-UWB radar network instead of a single radar. Three IR-UWB radars are placed as endpoints of an equilateral triangle to collect vital sign information of a subject sitting at the center. A Conditional Generative Adversarial Network (CGAN) method is proposed to fuse multisensory data. First, the body orientation is classified by combining signal features and a random forest classifier. Then the impact of different angles on vital sign monitoring results is discussed and validated in each orientation. The data fusion process is modelled as an extended generative network with orientation based condition to produce the enhanced vital signal. This signal is optimized with the discriminator network to a fitted sinusoidal wave with heartbeat and respiratory information. Experimental results on measuring Heartbeat Rate (HR) in different orientations reveal the effectiveness and stability of the proposed method.
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More From: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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