Wu Wen, Fong Justin, Crocher Vincent, Lee Peter V S, Oetomo Denny, Tan Ying, Ackland David C
Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia.
Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia.
J Biomech. 2018 Apr 27;72:7-16. doi: 10.1016/j.jbiomech.2018.02.019. Epub 2018 Feb 21.
Robotic-assistive exoskeletons can enable frequent repetitive movements without the presence of a full-time therapist; however, human-machine interaction and the capacity of powered exoskeletons to attenuate shoulder muscle and joint loading is poorly understood. This study aimed to quantify shoulder muscle and joint force during assisted activities of daily living using a powered robotic upper limb exoskeleton (ArmeoPower, Hocoma). Six healthy male subjects performed abduction, flexion, horizontal flexion, reaching and nose touching activities. These tasks were repeated under two conditions: (i) the exoskeleton compensating only for its own weight, and (ii) the exoskeleton providing full upper limb gravity compensation (i.e., weightlessness). Muscle EMG, joint kinematics and joint torques were simultaneously recorded, and shoulder muscle and joint forces calculated using personalized musculoskeletal models of each subject's upper limb. The exoskeleton reduced peak joint torques, muscle forces and joint loading by up to 74.8% (0.113 Nm/kg), 88.8% (5.8%BW) and 68.4% (75.6%BW), respectively, with the degree of load attenuation strongly task dependent. The peak compressive, anterior and superior glenohumeral joint force during assisted nose touching was 36.4% (24.6%BW), 72.4% (13.1%BW) and 85.0% (17.2%BW) lower than that during unassisted nose touching, respectively. The present study showed that upper limb weight compensation using an assistive exoskeleton may increase glenohumeral joint stability, since deltoid muscle force, which is the primary contributor to superior glenohumeral joint shear, is attenuated; however, prominent exoskeleton interaction moments are required to position and control the upper limb in space, even under full gravity compensation conditions. The modeling framework and results may be useful in planning targeted upper limb robotic rehabilitation tasks.
机器人辅助外骨骼能够在没有专职治疗师在场的情况下实现频繁的重复运动;然而,人机交互以及动力外骨骼减轻肩部肌肉和关节负荷的能力却鲜为人知。本研究旨在使用动力机器人上肢外骨骼(ArmeoPower,Hocoma)量化日常生活辅助活动期间的肩部肌肉和关节力。六名健康男性受试者进行了外展、屈曲、水平屈曲、伸展和触摸鼻子的活动。这些任务在两种条件下重复进行:(i)外骨骼仅补偿自身重量,以及(ii)外骨骼提供完全的上肢重力补偿(即失重)。同时记录肌肉肌电图、关节运动学和关节扭矩,并使用每个受试者上肢的个性化肌肉骨骼模型计算肩部肌肉和关节力。外骨骼分别将峰值关节扭矩、肌肉力和关节负荷降低了高达74.8%(0.113 Nm/kg)、88.8%(5.8%BW)和68.4%(75.6%BW),负荷衰减程度强烈依赖于任务。辅助触摸鼻子期间,肱盂关节的峰值压缩力、前向力和上向力分别比无辅助触摸鼻子期间低36.4%(24.6%BW)、72.4%(13.1%BW)和85.0%(17.2%BW)。本研究表明,使用辅助外骨骼进行上肢重量补偿可能会增加肱盂关节的稳定性,因为作为肱盂关节上向剪切力主要贡献者的三角肌力量会减弱;然而,即使在完全重力补偿条件下,也需要显著的外骨骼相互作用力矩来在空间中定位和控制上肢。该建模框架和结果可能有助于规划有针对性的上肢机器人康复任务。