ArticleFrontiers in bioengineering and biotechnology2026
Anticipatory prediction of sit-to-stand and stand-to-sit transitions: a unified approach.
Article in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Introduction: Sit-to-stand ( Methods: To support the development of such assistance, we analyzed Results: The experimental results demonstrated that at least four synergy patterns were sufficient to represent these STS motions. In addition, the proposed method achieved an accuracy of 92.97 ± 0.86% with a forecasting time of 300 ms for motion state prediction, while the average temporal error remained consistently below 50 ms. Discussion: These findings indicate that muscle synergy analysis can effectively characterize different STS movement strategies and that the proposed deep neural network framework can provide sufficient lead time for assistive device activation. This approach may contribute to the development of effective mechanical assistance systems for individuals with impaired muscle strength or motor control.
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