Abstract
This paper proposes a method based on a planar array of electrostatic induction electrodes, which uses human body electrostatics to measure the height of hand movements. The human body is electrostatically charged for a variety of reasons. In the process of a hand movement, the change of a human body’s electric field is captured through the electrostatic sensors connected to the electrode array. A measurement algorithm for the height of hand movements is used to measure the height of hand movements after the direction of it has been obtained. Compared with the tridimensional array, the planar array has the advantages of less space and easy deployment; therefore, it is more widely used. In this paper, a human hand movement sensing system based on human body electrostatics was established to perform verification experiments. The results show that this method can measure the height of hand movements with good accuracy to meet the requirements of non-contact human-computer interactions.
Highlights
The progress of computer and network technology and the continuous expansion of its application fields have promoted the continuous evolution of human-computer interactions
As a new generation of human-computer interaction, the natural user interface (NUI) [1] is gradually replacing the command-line and graphical user interfaces represented by the keyboard and the mouse [2,3]
This paper proposes a the height height of of hand movements based based on on aa planar
Summary
The progress of computer and network technology and the continuous expansion of its application fields have promoted the continuous evolution of human-computer interactions. The NUI does not require users to learn pre-designed operations but interacts with computers through voice, hand movements, facial expressions, or body gestures. Vision-based interaction [7] is a typical non-wearable device-based interaction, which can realize non-contact human-computer interactions, but its algorithm is complex and it is affected by ambient light, background, clothing, and so on [8]. This interaction relies on the exposed camera to obtain the user’s gesture information, which destroys the design sense of the devices and causes privacy issues for the user [9]. Wearable device-based methods have high detection accuracy [10], but Sensors 2020, 20, 2943; doi:10.3390/s20102943 www.mdpi.com/journal/sensors
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