Poliero Tommaso, Toxiri Stefano, Anastasi Sara, Monica Luigi, Ortiz Darwin G Caldwelll Jesus
IEEE Int Conf Rehabil Robot. 2019 Jun;2019:559-564. doi: 10.1109/ICORR.2019.8779519.
Despite the growing interest, the adoption of industrial exoskeletons may still be held back by technical limitations. To enhance versatility and promote adoption, one aspect of interest could be represented by the potential of active and quasi-passive devices to automatically distinguish different activities and adjust their assistive profiles accordingly. This contribution focuses on an active back-support exoskeleton and extends previous work proposing the use of a Support Vector Machine to classify walking, bending and standing. Thanks to the introduction of a new feature-forearm muscle activity-this study shows that it is possible to perform reliable online classification. As a consequence, the authors introduce a new hierarchically-structured controller for the exoskeleton under analysis.
尽管人们对此的兴趣与日俱增，但工业外骨骼的应用可能仍会受到技术限制的阻碍。为了提高通用性并促进其应用，主动和准被动设备自动区分不同活动并相应调整其辅助配置文件的潜力可能是一个值得关注的方面。本文聚焦于一种主动式背部支撑外骨骼，并扩展了先前的工作，提出使用支持向量机对行走、弯腰和站立进行分类。由于引入了一项新特征——前臂肌肉活动，本研究表明可以进行可靠的在线分类。因此，作者为所分析的外骨骼引入了一种新的分层结构控制器。
