State of the Art Methods of Machine Learning for Prosthetic Hand Development: A Review-Reference-Cited by-同舟云学术

State of the Art Methods of Machine Learning for Prosthetic Hand Development: A Review

Published:2023 Issue: Volume: Page:555-574
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Triwiyanto Triwiyanto,Maghfiroh Anita Miftahul,Musvika Syevana Dita,Amrinsani Farid,Syaifudin ,Mak’ruf Ridha,Rachmat Nur,Caesarendra Wahyu,Sulowicz Maciej

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-0248-4_37

Reference65 articles.

1. Triwiyanto T, Rahmawati T, Pawana IPA, Lamidi L (2021) State-of-the-art method in prosthetic hand design : a review. J Biomim Biomater Biomed Eng 50:15–24. https://doi.org/10.4028/www.scientific.net/JBBBE.50.15

2. Lenzi T, Lipsey J, Sensinger JW (2016) The RIC arm—a small anthropomorphic transhumeral prosthesis. el 21:2660–2671. https://doi.org/10.1109/TMECH.2016.2596104

3. Toledo C, Simon A, Muñoz R, Vera A, Leija L, Hargrove L (2012) A comparison of direct and pattern recognition control for a two degree-of-freedom above elbow virtual prosthesis. In: Proceedings annual international conference of the IEEE engineering in medicine and biology society. EMBS. 60611, pp 4332–4335. https://doi.org/10.1109/EMBC.2012.6346925

4. Gautam A, Panwar M, Wankhede A, Arjunan SP, Naik GR, Acharyya A, Kumar DK (2020) LoCoMo-Net: a low-complex deep learning framework for sEMG based hand movement recognition for prosthetic control. IEEE J Transl Eng Heal Med 1–12 (2020). https://doi.org/10.1109/JTEHM.2020.3023898

5. Van Der Niet O, van der Sluis CK (2013) Functionality of i-LIMB and i-LIMB pulse hands: case report. J Rehabil Res Dev 50:1123

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