Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:3649-3652. doi: 10.1109/EMBC48229.2022.9871023.
Investigations on how the central nervous system (CNS) effortlessly conducts complex hand movements have led to an extensive study of synergies or movement primitives. Of the different types of hand synergies, kinematic and muscle synergies have been widely studied in literature, but only a few studies have fused both. In this paper kinematic and muscle activities recorded from the activities of daily living were first fused and then dimensionally reduced through principal component analysis (PCA). By using these principal components or musculoskeletal synergies in a weighted linear combination, the recorded kinematics and muscle activities were reconstructed. The performance of these musculoskeletal synergies in reconstructing the movements was compared to the kinematic and muscle synergies reported previously in the literature by us and others. The results from these findings indicate that musculoskeletal synergies perform better than the synergies extracted without fusion. These newly demonstrated musculoskeletal synergies might improve neural control of robotics, prosthetics and exoskeletons. Clinical Relevance- In this paper, musculoskeletal synergies were extracted from the fusion of kinematic and muscle activities recorded from the activities of daily living. These newly demonstrated musculoskeletal synergies might enhance our understanding of neural control of robotics, prosthetics and exoskeletons.
关于中枢神经系统(CNS)如何轻松地进行复杂手部运动的研究,导致了对协同作用或运动基元的广泛研究。在不同类型的手部协同作用中,运动学和肌肉协同作用在文献中得到了广泛研究,但只有少数研究将两者融合在一起。在本文中,首先融合了日常生活活动中记录的运动学和肌肉活动,然后通过主成分分析(PCA)进行降维。通过在加权线性组合中使用这些主成分或肌肉骨骼协同作用,可以重建记录的运动学和肌肉活动。将这些肌肉骨骼协同作用与我们和其他人之前在文献中报告的运动学和肌肉协同作用进行比较,以评估它们在重建运动方面的性能。这些发现的结果表明,肌肉骨骼协同作用的性能优于没有融合时提取的协同作用。这些新提出的肌肉骨骼协同作用可能会改善机器人、假肢和外骨骼的神经控制。临床意义-在本文中,从日常生活活动中记录的运动学和肌肉活动的融合中提取了肌肉骨骼协同作用。这些新提出的肌肉骨骼协同作用可能会增强我们对机器人、假肢和外骨骼的神经控制的理解。