Barely Significant
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an important trend

497 sentences · 497 papers · 1,689 search hits before verification · confirmed specimen

Sighted at

p=0.066

Listed by Hankins (2013) · Otte et al. (2022)

In the literature

By obtaining, classifying and identifying electromyogramsto predict the intention of human limbs, sEMG can be applied to various fields such as prosthetic movement control, limb rehabilitation evaluation, gait analysis, neuromuscular function evaluation, and it has gradually become an important trend for the future [ 62 , 63 ].
This result underscores an important trend: methods that incorporate multi‐view learning (such as STMIGCL and Spatial‐MGCN) or contrastive learning (such as STMIGCL and GraphST) tend to produce smoother domain boundaries in domain identification tasks, significantly reducing the occurrence of discrete points.