| Abstract | Electric field sensors are used in a variety of ways to recognize different human actions and behaviors, for example, fall detection or classification of movements. However, very little is known about the number of sensors that are needed to achieve an acceptable recognition rate. Most systems just use as many sensors as possible to achieve confusion matrices with high true positive and true negative rates. In this paper, the relation of recognition rates and the size of a system composed of Passive Electric Field sensors shall be further investigated. For this purpose, several setups to recognize different human activities will be created and evaluated, each with a varying number of sensor tokens. |
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