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. 2021 May 28;11:11275. doi: 10.1038/s41598-021-90688-4

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Real-Time Classification. (a) Set of 6 functional hand postures/grip modes: (1) closed hand/fist, (2) thumb-up and hook grip, (3) tripod pinch, (4) open hand/neutral position, (5) fine pinch, and (6) pointed index. (b) Time-distributed system outputs during a real-time inference test performed by user 3. The user cycles through every gesture, holding them for a few seconds and resting in the neutral position (label 4) in between. The top plot shows the system’s predictions (neural network + majority vote). The bottom plot displays the aligned mean Teager-Kaiser Energy (TKE) value to give an idea of the system’s responsiveness to the muscle contractions.