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User authentication plays an important role in securing systems and devices by preventing unauthorized accesses. Although surface Electromyogram (sEMG) has been widely applied for human machine interface (HMI) applications, it has only seen a very limited use for user authentication. In this paper, we investigate the use of multi-channel sEMG signals of hand gestures for user authentication. We propose a new deep anomaly detection-based user authentication method which employs sEMG images generated from multi-channel sEMG signals. The deep anomaly detection model classifies the user performing the hand gesture as client or imposter by using sEMG images as the input. Different sEMG image generation methods are studied in this paper. The performance of the proposed method is evaluated with a high-density hand gesture sEMG (HD-sEMG) dataset and a sparse-density hand gesture sEMG (SD-sEMG) dataset under three authentication test scenarios. Among the sEMG image generation methods, root mean square (RMS) map achieves significantly better performance than others. The proposed method with RMS map also greatly outperforms the reference method, especially when using SD-sEMG signals. The results demonstrate the validity of the proposed method with RMS map for user authentication.
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Exploring Undergraduate Biochemistry Students’ Gesture Production Through an Embodied Framework
Students often use gesture to complement verbal descriptions of 3D biomolecular structure. Here, the authors uncover two emergent patterns of gesture production by undergraduates while explaining the mechanism of K+channel function. They also identify shifts in gesture use following exposure to an augmented reality-based virtual 3D model of the channel.
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- Award ID(s):
- 1841992
- PAR ID:
- 10553244
- Editor(s):
- Gouvea, Julia
- Publisher / Repository:
- CBE LSE
- Date Published:
- Journal Name:
- CBE—Life Sciences Education
- Volume:
- 23
- Issue:
- 2
- ISSN:
- 1931-7913
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1187/cbe.23-06-0106
