File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/JIOT.2021.3084560
- Scopus: eid_2-s2.0-85107216393
- WOS: WOS:000733323800036
Supplementary
- Citations:
- Appears in Collections:
Article: mmKey: Universal Virtual Keyboard using A Single Millimeter Wave Radio
Title | mmKey: Universal Virtual Keyboard using A Single Millimeter Wave Radio |
---|---|
Authors | |
Keywords | Wireless sensor networks millimeterwave radio. Training Wireless communication Vibrations Keyboards Cameras wireless sensing Wireless fidelity Virtual keyboard |
Issue Date | 2021 |
Citation | IEEE Internet of Things Journal, 2021 How to Cite? |
Abstract | Keyboard acts as one of the most commonly used mediums for human-computer interaction. Today, massive Internet of Things (IoT) devices are designed without a physical keyboard as they go tiny, but are almost all equipped with a wireless module for networks. In this work, we aim to enable a universal virtual keyboard using wireless signals, which would allow a typing interface for tiny IoT devices or serve as a portable alternative to the unwieldy physical keyboards. To this end, we present mmKey, the first universal virtual keyboard system using a single millimeter-wave (mmWave) radio. By leveraging the unique advantages of mmWave signals, mmKey converts any flat surface, with a printed paper keyboard, into an effective typing medium. mmKey enables concurrent keystrokes and supports multiple keyboard layouts (e.g., computer keyboard, piano keyboard, or phone keypad). We design a novel signal processing pipeline to detect, segment and separate, and finally recognize keystrokes. mmKey does not need any training except for a minimal one-time effort of only three key-presses for keyboard calibration upon the initial setup. We prototype mmKey using a commodity 802.11ad/ay chipset, customized to support radar-like operations, and evaluate it with different keyboard layouts under various settings. Experimental results with 10 participants demonstrate a keystroke recognition accuracy of > 95% for single-key case and > 90% for multi-key scenario, which leads to a word recognition accuracy of > 97%. |
Persistent Identifier | http://hdl.handle.net/10722/303782 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hu, Yuqian | - |
dc.contributor.author | Wang, Beibei | - |
dc.contributor.author | Wu, Chenshu | - |
dc.contributor.author | Liu, K. J.R. | - |
dc.date.accessioned | 2021-09-15T08:26:00Z | - |
dc.date.available | 2021-09-15T08:26:00Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | IEEE Internet of Things Journal, 2021 | - |
dc.identifier.uri | http://hdl.handle.net/10722/303782 | - |
dc.description.abstract | Keyboard acts as one of the most commonly used mediums for human-computer interaction. Today, massive Internet of Things (IoT) devices are designed without a physical keyboard as they go tiny, but are almost all equipped with a wireless module for networks. In this work, we aim to enable a universal virtual keyboard using wireless signals, which would allow a typing interface for tiny IoT devices or serve as a portable alternative to the unwieldy physical keyboards. To this end, we present mmKey, the first universal virtual keyboard system using a single millimeter-wave (mmWave) radio. By leveraging the unique advantages of mmWave signals, mmKey converts any flat surface, with a printed paper keyboard, into an effective typing medium. mmKey enables concurrent keystrokes and supports multiple keyboard layouts (e.g., computer keyboard, piano keyboard, or phone keypad). We design a novel signal processing pipeline to detect, segment and separate, and finally recognize keystrokes. mmKey does not need any training except for a minimal one-time effort of only three key-presses for keyboard calibration upon the initial setup. We prototype mmKey using a commodity 802.11ad/ay chipset, customized to support radar-like operations, and evaluate it with different keyboard layouts under various settings. Experimental results with 10 participants demonstrate a keystroke recognition accuracy of > 95% for single-key case and > 90% for multi-key scenario, which leads to a word recognition accuracy of > 97%. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Internet of Things Journal | - |
dc.subject | Wireless sensor networks | - |
dc.subject | millimeterwave radio. | - |
dc.subject | Training | - |
dc.subject | Wireless communication | - |
dc.subject | Vibrations | - |
dc.subject | Keyboards | - |
dc.subject | Cameras | - |
dc.subject | wireless sensing | - |
dc.subject | Wireless fidelity | - |
dc.subject | Virtual keyboard | - |
dc.title | mmKey: Universal Virtual Keyboard using A Single Millimeter Wave Radio | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/JIOT.2021.3084560 | - |
dc.identifier.scopus | eid_2-s2.0-85107216393 | - |
dc.identifier.eissn | 2327-4662 | - |
dc.identifier.isi | WOS:000733323800036 | - |