Gesture Recognition Through Classification of Acoustic Muscle Sensing for Prosthetic Control-Reference-Cited by-同舟云学术

Gesture Recognition Through Classification of Acoustic Muscle Sensing for Prosthetic Control

Published:2017 Issue: Volume: Page:637-642
ISSN:0302-9743
Container-title:Biomimetic and Biohybrid Systems
language:
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Author:

Wilson Samuel^ORCID,Vaidyanathan Ravi

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-63537-8_61

Reference8 articles.

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2. Zeng, Y., Yang, Z.Y., Cao, W., Xia, C.M.: Hand-motion patterns recognition based on mechanomyographic signal analysis. In: 2009 International Conference on Future Biomedical Information Engineering (Fbie 2009), pp. 21–24 (2009)

3. Atzori, M., et al.: Electromyography data for non-invasive naturally-controlled robotic hand prostheses. Sci. Data 1, 140053 (2014). PMC Web. 11 May 2017

4. Al-Timemy, A.H., Bugmann, G., Escudero, J., Outram, N.: Classification of finger movements for the dexterous hand prosthesis control with surface electromyography. IEEE J. Biomed. Health Inf. 17(3), 608–618 (2013)

5. Silva, J., Chau, T., Goldenberg, A.: MMG-based multisensor data fusion for prosthesis control, pp. 2909–2912 (2003)

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