Radar sensing technologies now offer new opportunities for gesturally interacting with a smart environment by capturing microgestures via a chip that is embedded in a wearable device, such as a smartwatch, a nger or a ring. Such microgestures are issued at a very small distance from the device, regardless of whether they are contact-based, such as on the skin, or contactless. As this category of microgestures remains largely unexplored, this paper reports the results of a gesture elicitation study that was conducted with twenty-ve participants who expressed their preferred user-dened gestures for interacting with a radar-based sensor on nineteen referents that represented frequent Internet-of-things tasks. This study clustered the 25 19 D 475 initially elicited gestures into four categories of microgestures, namely, micro, motion, combined, and hybrid, and thirty-one classes of distinct gesture types and produced a consensus set of the nineteen most preferred microgestures. In a conrmatory study, twenty new participants selected gestures from this classication for thirty referents that represented tasks of various orders; they reached a high rate of agreement and did not identify any new gestures. This classication of radar-based gestures provides researchers and practitioners with a larger basis for exploring gestural interactions with radar-based sensors, such as for hand gesture recognition.
Magrofuoco, N., Perez-Medina, J.-., Roselli, P., Vanderdonckt, J., Villarreal, S. (2019). Eliciting contact-based and contactless gestures with radar-based sensors. IEEE ACCESS, 7, 176982-176997 [10.1109/ACCESS.2019.2951349].
Eliciting contact-based and contactless gestures with radar-based sensors
Roselli P.;
2019-11-04
Abstract
Radar sensing technologies now offer new opportunities for gesturally interacting with a smart environment by capturing microgestures via a chip that is embedded in a wearable device, such as a smartwatch, a nger or a ring. Such microgestures are issued at a very small distance from the device, regardless of whether they are contact-based, such as on the skin, or contactless. As this category of microgestures remains largely unexplored, this paper reports the results of a gesture elicitation study that was conducted with twenty-ve participants who expressed their preferred user-dened gestures for interacting with a radar-based sensor on nineteen referents that represented frequent Internet-of-things tasks. This study clustered the 25 19 D 475 initially elicited gestures into four categories of microgestures, namely, micro, motion, combined, and hybrid, and thirty-one classes of distinct gesture types and produced a consensus set of the nineteen most preferred microgestures. In a conrmatory study, twenty new participants selected gestures from this classication for thirty referents that represented tasks of various orders; they reached a high rate of agreement and did not identify any new gestures. This classication of radar-based gestures provides researchers and practitioners with a larger basis for exploring gestural interactions with radar-based sensors, such as for hand gesture recognition.File | Dimensione | Formato | |
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