research-article

IndexPen: Two-Finger Text Input with Millimeter-Wave Radar

Authors:

Alexander D. Galvan,

Kaveh Pahlavan,

Erin T. SoloveyAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 6, Issue 2

Article No.: 79, Pages 1 - 39

https://doi.org/10.1145/3534601

Published: 07 July 2022 Publication History

Abstract

In this paper, we introduce IndexPen, a novel interaction technique for text input through two-finger in-air micro-gestures, enabling touch-free, effortless, tracking-based interaction, designed to mirror real-world writing. Our system is based on millimeter-wave radar sensing, and does not require instrumentation on the user. IndexPen can successfully identify 30 distinct gestures, representing the letters A-Z, as well as Space, Backspace, Enter, and a special Activation gesture to prevent unintentional input. Additionally, we include a noise class to differentiate gesture and non-gesture noise. We present our system design, including the radio frequency (RF) processing pipeline, classification model, and real-time detection algorithms. We further demonstrate our proof-of-concept system with data collected over ten days with five participants yielding 95.89% cross-validation accuracy on 31 classes (including noise). Moreover, we explore the learnability and adaptability of our system for real-world text input with 16 participants who are first-time users to IndexPen over five sessions. After each session, the pre-trained model from the previous five-user study is calibrated on the data collected so far for a new user through transfer learning. The F-1 score showed an average increase of 9.14% per session with the calibration, reaching an average of 88.3% on the last session across the 16 users. Meanwhile, we show that the users can type sentences with IndexPen at 86.2% accuracy, measured by string similarity. This work builds a foundation and vision for future interaction interfaces that could be enabled with this paradigm.

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Cited By

Li ZWei HXie ZPeng YSuh JFeiner SSajda P(2024)PhysioLabXR: A Python Platform for Real-Time, Multi-modal, Brain–Computer Interfaces and Extended Reality ExperimentsJournal of Open Source Software10.21105/joss.058549:93(5854)Online publication date: Jan-2024
https://doi.org/10.21105/joss.05854
Zhang DZhang XXie YZhang FWang XLi YZhang D(2024)LoCalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314367:4(1-27)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631436
Chen JGuo SLv SCui GKong L(2024)A Lightweight Hand-Gesture Recognition Network With Feature Fusion Prefiltering and FMCW Radar Spatial Angle EstimationIEEE Sensors Journal10.1109/JSEN.2024.343297224:17(27926-27936)Online publication date: 1-Sep-2024
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Index Terms

IndexPen: Two-Finger Text Input with Millimeter-Wave Radar
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies
    2. Interaction devices
      1. Haptic devices

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 6, Issue 2

July 2022

1551 pages

EISSN:2474-9567

DOI:10.1145/3547347

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Published: 07 July 2022

Published in IMWUT Volume 6, Issue 2

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https://doi.org/10.21105/joss.05854
Zhang DZhang XXie YZhang FWang XLi YZhang D(2024)LoCalProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314367:4(1-27)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631436
Chen JGuo SLv SCui GKong L(2024)A Lightweight Hand-Gesture Recognition Network With Feature Fusion Prefiltering and FMCW Radar Spatial Angle EstimationIEEE Sensors Journal10.1109/JSEN.2024.343297224:17(27926-27936)Online publication date: 1-Sep-2024
https://doi.org/10.1109/JSEN.2024.3432972
Yu JTseng YTseng P(2024)A mmWave MIMO Radar-Based Gesture Recognition Using Fusion of Range, Velocity, and Angular InformationIEEE Sensors Journal10.1109/JSEN.2024.335539524:6(9124-9134)Online publication date: 15-Mar-2024
https://doi.org/10.1109/JSEN.2024.3355395
Chen QCui ZZhou ZTian YCao Z(2024)MMHTSR: In-Air Handwriting Trajectory Sensing and Reconstruction Based on mmWave RadarIEEE Internet of Things Journal10.1109/JIOT.2023.332525811:6(10069-10083)Online publication date: 15-Mar-2024
https://doi.org/10.1109/JIOT.2023.3325258
Yang XWang XDong GYan ZSrivastava MHayashi EZhang Y(2023)HeadarProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36109007:3(1-28)Online publication date: 27-Sep-2023
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Wang XLiu TFeng CFang DChen X(2023)RF-CMProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808597:1(1-28)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580859
Zeng SWan HShi SWang W(2023)mSilentProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808387:1(1-28)Online publication date: 28-Mar-2023
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Zhang DZhang XLi SXie YLi YWang XZhang D(2023)LT-FallProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808357:1(1-24)Online publication date: 28-Mar-2023
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