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This study proposes a long short-term memory (LSTM) neural network to predict five LMs (level-walking, ramp ascent\/descent, stair ascent\/descent) with greater lead time compared to state-of-the-art methods. We examined the optimal sequence length (SL) for LSTM-based LM prediction, using data from inertial sensors placed on the lower limbs and the lower back, along with a waist-mounted infrared laser. Ten subjects walked in real-life scenarios, both with and without an ankle\u2013foot exoskeleton. Results show that a 1-s SL provides the most advanced and accurate LM prediction, outperforming SLs of 0.6, 0.8, and 1.2\u00a0s. The proposed LSTM model achieved an accuracy of 98\u2009\u00b1\u20090.31%, predicting LMs 0.66\u00a0s in advance (for an average stride time of 1.98\u2009\u00b1\u20090.83\u00a0s). Level-walking presented more misclassifications, and the model primarily relied on inertial data over laser input. Overall, these findings demonstrate the LSTM\u2019s strong predictive capability for both assisted and non-assisted walking and independent of which limb executes the transition, supporting its applicability for exoskeleton-assisted locomotion.<\/jats:p>","DOI":"10.1007\/s10489-025-06416-2","type":"journal-article","created":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T23:40:49Z","timestamp":1742341249000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Locomotion mode prediction in real-life walking with and without ankle\u2013foot exoskeleton assistance"],"prefix":"10.1007","volume":"55","author":[{"given":"Sim\u00e3o P.","family":"Carvalho","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9547-3051","authenticated-orcid":false,"given":"Joana","family":"Figueiredo","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o J.","family":"Cerqueira","sequence":"additional","affiliation":[]},{"given":"Cristina P.","family":"Santos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,19]]},"reference":[{"key":"6416_CR1","doi-asserted-by":"publisher","unstructured":"Whittle MW (2012) Gait analysis an introduction, 4th ed. 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