Capacitive Proximity Sensor Array With a Simple High Sensitivity Capacitance Measuring Circuit for Human-Computer Interaction

Capacitive proximity sensor uses electric fields to detect contactless objects like human body. Owing to its simplicity and low cost, it is an attractive choice for the application of human-computer interaction. For existing capacitive proximity sensor systems, their detection ranges are less than 2...

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Veröffentlicht in:IEEE sensors journal 2018-07, Vol.18 (14), p.5906-5914
Hauptverfasser: Ye, Yong, He, Chunlong, Liao, Bin, Qian, Gongbin
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Sprache:eng
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Zusammenfassung:Capacitive proximity sensor uses electric fields to detect contactless objects like human body. Owing to its simplicity and low cost, it is an attractive choice for the application of human-computer interaction. For existing capacitive proximity sensor systems, their detection ranges are less than 20 cm that cannot meet the requirements of the applications for long distance sensing. This motivates us to develop a new capacitive proximity sensor system for human-computer interaction in this paper. A capacitive sensor array, which consists of 4 × 4 sensor units with comb shapes, is first designed. The dimensions of the whole array and a single unit are, respectively, 30 cm × 30 cm and 4 cm × 4 cm, which are comprehensively considered with hand swing distance in natural state and the sensing distance. More specifically, an outer guard with a lattice-like structure which encloses sensor cells is designed to reduce the crosstalk from its neighboring cells, and a simple capacitance measuring circuit is presented. Comparing to the charge/discharge, ac-based and CDC-chip-based capacitance measuring circuit, the proposed measuring circuit offers plain design, highest sensitivity (3.53 V/pF), and fastest speed (4 μs). The experimental results show that the system can capture hand motion up to 45 cm and get hand motion trajectory using the hand position tracking algorithm. These features indicate that the proposed system is very suitable for human-computer interaction applications in the future, such as rehabilitation training and somatosensory game.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2018.2840093