Voluntary motion support by an upper limb support system based on bioelectrical signals for heavy overhead tasks

2016 
We have developed a wearable upper limb support system (ULSS) for support during heavy overhead tasks. The purpose of this study is to develop the voluntary motion support algorithm for the ULSS, and to confirm the effectiveness of the ULSS with the developed algorithm through dynamic evaluation experiments. The algorithm estimates the motor intention of the wearer based on a bioelectrical signal (BES). The ULSS measures the BES via electrodes attached onto the triceps brachii, deltoid, and clavicle. The BES changes in synchronization with the motion of the wearer's upper limbs. The algorithm changes a control phase by comparing the BES and threshold values. The algorithm achieves voluntary motion support for dynamic tasks by changing support torques of the ULSS in synchronization with the control phase. Five healthy adult males moved heavy loads vertically overhead in the evaluation experiments. In a random instruction experiment, the volunteers moved in synchronization with random instructions, and we confirmed that the control phase changes in synchronization with the random instructions. In a motion support experiment, we confirmed that the average number of the vertical motion with the ULSS increased 2.3 times compared to the average number without the ULSS. As a result, the ULSS with the algorithm supports the motion voluntarily, and it has a positive effect on the support. In conclusion, we could develop the novel voluntary motion support algorithm of the ULSS.
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