Treffer: NeuraLoop: a high bandwidth closed-loop human-machine interface.
Front Neurorobot. 2021 Jul 15;15:648855. (PMID: 34335219)
J Neuroeng Rehabil. 2024 Jan 13;21(1):7. (PMID: 38218901)
Artif Organs. 2024 Jun;48(6):626-635. (PMID: 38149317)
Prog Biomed Eng (Bristol). 2023 Jan 06;5(1):. (PMID: 41074852)
Exp Brain Res. 2024 May;242(5):1047-1060. (PMID: 38467759)
IEEE Trans Neural Syst Rehabil Eng. 2023;31:208-217. (PMID: 36327175)
IEEE Trans Biomed Eng. 2003 Jul;50(7):848-54. (PMID: 12848352)
IEEE Trans Neural Syst Rehabil Eng. 2022;30:1310-1320. (PMID: 35533165)
J Neural Eng. 2024 Aug 22;21(4):. (PMID: 39079541)
J Neural Eng. 2020 Feb 12;17(1):016052. (PMID: 31899898)
IEEE Trans Neural Syst Rehabil Eng. 2021;29:1110-1119. (PMID: 34097613)
IEEE Trans Haptics. 2022 Jan-Mar;15(1):222-231. (PMID: 34618676)
Med Biol Eng Comput. 2020 Jan;58(1):83-100. (PMID: 31754982)
PLoS One. 2017 Oct 12;12(10):e0186132. (PMID: 29023548)
J Neuroeng Rehabil. 2012 Dec 10;9:85. (PMID: 23216679)
J Neuroeng Rehabil. 2021 May 25;18(1):87. (PMID: 34034762)
J Neural Eng. 2022 Apr 05;19(2):. (PMID: 35303732)
IEEE Trans Biomed Eng. 2022 May;69(5):1758-1766. (PMID: 34847014)
Front Neurosci. 2025 May 09;19:1519758. (PMID: 40415891)
J Neural Eng. 2021 Sep 07;18(5):. (PMID: 34416740)
IEEE Trans Neural Syst Rehabil Eng. 2019 Apr;27(4):760-771. (PMID: 30714928)
Sensors (Basel). 2023 Jan 18;23(3):. (PMID: 36772153)
IEEE Trans Neural Syst Rehabil Eng. 2023;31:2090-2100. (PMID: 37058389)
J Neural Eng. 2025 Jan 17;22(1):. (PMID: 39746322)
IEEE Trans Neural Syst Rehabil Eng. 2008 Jun;16(3):270-7. (PMID: 18586606)
IEEE Trans Biomed Circuits Syst. 2025 Jun;19(3):536-548. (PMID: 39312417)
IEEE Trans Neural Syst Rehabil Eng. 2010 Apr;18(2):185-92. (PMID: 20071269)
Appl Bionics Biomech. 2019 Mar 14;2019:9298758. (PMID: 31001360)
J Neuroeng Rehabil. 2014 Sep 15;11:138. (PMID: 25224266)
J Neuroeng Rehabil. 2016 Aug 04;13(1):73. (PMID: 27488270)
Ann Med. 2024 Dec;56(1):2306905. (PMID: 38294958)
J Neuroeng Rehabil. 2017 May 4;14(1):39. (PMID: 28472991)
J Neuroeng Rehabil. 2022 Jul 21;19(1):78. (PMID: 35864513)
IEEE Trans Neural Syst Rehabil Eng. 2018 Jun;26(6):1199-1208. (PMID: 29877844)
J Electromyogr Kinesiol. 2020 Oct;54:102440. (PMID: 32763743)
Weitere Informationen
Background: Myoelectric interfaces have emerged as powerful tools for human-machine interaction (HMI), enabling intuitive control of virtual and physical devices. However, most existing systems are limited by low spatial resolution and unidirectional communication. To address these limitations, we developed NeuraLoop, a wearable, high-bandwidth, bidirectional interface that integrates myoelectric (EMG) signal acquisition and electrotactile stimulation feedback within a single wearable textile-based platform.
Methods: NeuraLoop comprises a flexible matrix of 32 EMG recording and 32 electrotactile stimulation pads controlled by a compact electronic unit. We evaluated the system in two experimental tasks involving ten healthy subjects to demonstrate: (1) online classification of four transient thumb micro-gestures (thumb rightwards, leftwards, upwards, and downwards swipe directions), and (2) closed-loop control of a virtual cursor using micro-gesture commands and spatially encoded tactile feedback. A time-division multiplexing (TDM) strategy was implemented to enable simultaneous stimulation and recording.
Results: The subjects achieved a median success rate of 82% on the first attempt and over 94% within two attempts during online classification with visual feedback. All four micro-gestures were classified with similar accuracy. In the closed-loop control task with tactile feedback, participants navigated a 3 × 4 grid using only electrotactile stimulation, achieving 70% accuracy for exact target hits and 95% when including the hits in the neighboring cells (1 cell distance error).
Conclusions: NeuraLoop demonstrates the feasibility of high-bandwidth, bidirectional HMI using a wearable, textile-based interface. The system enables accurate recognition of subtle micro-gestures and effective delivery of spatially encoded tactile feedback. These capabilities open new possibilities for intuitive control in applications such as prosthetics, rehabilitation, and virtual/augmented reality. Future work will explore multimodal feedback encoding and proportional gesture control.
(© 2025. The Author(s).)
Declarations. Ethics approval and consent to participate: Prior to the start of the experimental session, all participants received oral and written information about the study and provided their written informed consent. The study was conducted in accordance with the Declaration of Helsinki and approved by the North Denmark Region Committee on Health Research Ethics (N-20220001). Competing interests: LPM founded a startup to further develop and apply the NeuraLoop technology. SD is an Associate Editor in the Journal of NeuroEngineering and Rehabilitation.