Abstract

Current trends in Human–Computer Interface (HCI) have brought on a wave of new consumer devices that can track the motion of our hands. These devices have enabled more natural interfaces with computer applications. Data gloves are commonly used as input devices, equipped with sensors that detect the movements of hands and communication unit that interfaces those movements with a computer. Unfortunately, the high cost of sensor technology inevitably puts some burden to most general users. In this research, we have proposed a low-cost data glove concept based on printed polymeric sensor to make pressure and bending sensors fabricated by a consumer ink-jet printer. These sensors were realized using a conductive polymer (poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) [PEDOT:PSS]) thin film printed on glossy photo paper. Performance of these sensors can be enhanced by addition of dimethyl sulfoxide (DMSO) into the aqueous dispersion of PEDOT:PSS. The concept of surface resistance was successfully adopted for the design and fabrication of sensors. To demonstrate the printed sensors, we constructed a data glove using such sensors and developed software for real time hand tracking. Wireless networks based on low-cost Zigbee technology were used to transfer data from the glove to a computer. To our knowledge, this is the first report on low cost data glove based on paper pressure sensors. This low cost implementation of both sensors and communication network as proposed in this paper should pave the way toward a widespread implementation of data glove for real-time hand tracking applications.Implications for RehabilitationData gloves can interface the movements of hands to a computer, translating human needs to assistive functions such as controlling of home appliances.We have proposed a low-cost data glove concept based on printed polymeric bending and pressure sensor using consumer ink-jet printer.This low cost implementation of the printed sensors and Zigbee communication network as proposed in this paper should pave the way toward a widespread applications of data glove for real-time hand tracking in healthcare.

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