2026-08-03 00:00 Papers Movement & Control Translated from EN

2-Block EEG Gait Decoder Reaches 70.5 ms Latency

Summary This preprint reports a 2-block lightweight architecture for real-time EEG gait decoding that the authors say enables closed-loop lower-limb exoskeleton control. In closed-loop deployment, the study reports a 55.3% gait initiation success rate with Rex assistance and 52.7% volitionally, with a mean end-to-end processing time of 70.5 ms (±41.5). The authors add that the manuscript was accepted for publication at the 2026 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2026).

Why it matters This pilot study targets real-time, closed-loop EEG control of a lower-limb exoskeleton, a setting where motion artifacts and low signal-to-noise ratios have limited prior work. The 2-block design (PolyTVL front-end plus LSTM back-end) keeps the pipeline light enough for 70.5 ms end-to-end processing, and the reported 55.3% assisted and 52.7% volitional initiation success point to a practical path for EEG-driven gait assistance.

BCIwiki (bciwiki.com) — A 2-block lightweight architecture brought end-to-end latency in real-time EEG gait decoding down to 70.5 ms, according to a preprint posted to arXiv on August 3, 2026. The authors say EEG-based closed-loop control has been limited by motion artifacts and low signal-to-noise ratios. Their design splits the task: a front-end PolyTVL module compresses 32-channel EEG into a compact representation, and a back-end LSTM decoder classifies four gait phases (Stand, Initiate, Execute, Terminate).

In closed-loop deployment, the v01 configuration (PolyTVL+LSTM) reached a 55.3% gait initiation success rate with Rex assistance and 52.7% volitionally. The authors add that the manuscript was accepted for publication at the 2026 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2026).

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arxiv.org 2026-08-03

Motor Decoding Closed-loop Systems Non-invasive BCI

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