journal article
Dec 11, 2019
LimbMotion
Abstract
Wearable-based human-computer interaction is a promising technology to enable various applications. This paper aims to track the 3D posture of the entire limb, both wrist/ankle and elbow/knee, of a user wearing a smart device. This limb tracking technology can trace the geometric motion of the limb, without introducing any training stage usually required in gesture recognition approaches. Nonetheless, the tracked limb motion can also be used as a generic input for gesture-based applications. The 3D posture of a limb is defined by the relative positions among main joints, e.g., shoulder, elbow, and wrist for an arm. When a smartwatch is worn on the wrist of a user, its position is affected by both elbow and shoulder motions. It is challenging to infer the entire 3D posture when only given a single point of sensor data from the smartwatch. In this paper, we propose LimbMotion, an accurate and real-time limb tracking system. The performance gain of LimbMotion comes from multiple key technologies, including an accurate attitude estimator based on a novel two-step filter, fast acoustic ranging, and point clouds-based positioning. We implemented LimbMotion and evaluated its performance using extensive experiments, including different gestures, moving speeds, users, and limbs. Results show that LimbMotion achieves real-time tracking with a median error of 7.5cm to 8.9cm, which outperforms the state-of-the-art approach by about 32%.
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References
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Metrics
24
Citations
50
References
Details
- Published
- Dec 11, 2019
- Vol/Issue
- 3(4)
- Pages
- 1-24
- License
- View
Authors
Funding
Fundamental Research Funds for the Central Universities
Award: No. 2018FZA5013
National Science Foundation of China
Award: No.61872437, 61772465
Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars
Award: No. LR19F020001
Cite This Article
Han Zhou, Yi Gao, Xinyi Song, et al. (2019). LimbMotion. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(4), 1-24. https://doi.org/10.1145/3369836
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