| DOI | Resolve DOI: https://doi.org/10.1145/3384419.3430712 |
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| Author | Search for: Wang, Ju; Search for: Li, Jianyan; Search for: Mazaheri, Mohammad Hossein; Search for: Katsuragawa, Keiko1; Search for: Vogel, Daniel; Search for: Abari, Omid |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems, November 16-19, 2020, Virtual Event Japan |
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| Subject | finger input; gesture; RFID; transmission line |
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| Abstract | We introduce a passive Radio Frequency IDentification (RFID) based system to detect finger gesture input for Human-Computer Interaction applications. The device is simple, inexpensive and does not require calibration to accommodate changes in the device location or the Radio Frequency (RF) environment. This is achieved by connecting the chips of two RFID tags together using a strip transmission line. The key observation is that touching different positions along the transmission line changes the impedance matching between each chip and its antenna, changing Received Signal Strength (RSS) values for each tag. When a finger slides in different directions between key positions along the transmission line, there are relative RSS patterns and trends that are robust to changes in the device location and the RF environment. We implemented and evaluated an detection algorithm and system using a commercial RFID reader and two commercial RFID chips. Results show that precision and recall are greater than 95% and 94% when detecting 10 finger gesture inputs across 48 different device locations. |
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| Publication date | 2020-11-16 |
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| Publisher | ACM |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | fed9e18c-a7b5-4496-b077-22bb25c783ca |
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| Record created | 2021-06-11 |
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| Record modified | 2021-06-14 |
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