Humans are favoured to conventional robotics for some tasks in industry due to their increased dexterity and fine motor skills, however, performance of these tasks can result in injury to the user at a cost to both the user and the employer. In this paper we describe a lightweight, upper-limb exosuit intended to assist the user during lifting tasks (up to 10kg) and while operating power tools, which are common activities for industrial workers. The exosuit assists elbow and shoulder flexion for both arms and allows for passive movements in the transverse plane. To achieve the design criteria an underactuated mechanism has been developed, where a single motor is used to assist two degrees of freedom per arm. In the intended application, the hands are generally busy and cannot be used to provide inputs to the robot, therefore, a voice-activated control has been developed that allows the user to give voice commands to operate the exosuit. Experiments were performed on 5 healthy subjects to assess the change in Muscular Activation (MA), inferred through Electromyography (EMG) signals, during three tasks: i) lifting and releasing a load; ii) holding a position and iii) manipulating a tool. The results showed that the exosuit is capable of reducing EMG activity (between 24.6% and 64.6%) and the recognition rate (94.8%) of the voice recognition module was evaluated.

由于人类增加了灵活性和精细的运动技能，他们在工业上的某些任务中偏向于传统的机器人技术，但是，执行这些任务会导致对用户的伤害，而这会给用户和用人单位带来损失。在本文中，我们介绍了一种轻巧的上肢外衣，旨在在起重任务（不超过10kg）和操作电动工具时为用户提供帮助，这是工业工人的常见活动。防护服有助于手臂的肘部和肩膀屈曲，并允许其在横向平面内被动运动。为了达到设计标准，开发了一种欠驱动机构，其中单个电动机用于辅助每个臂的两个自由度。在预期的应用中，手通常很忙，不能用于向机器人提供输入，因此，已经开发出语音激活控件，该控件允许用户发出语音命令来操作该防毒服。在5个健康受试者上进行了实验，以评估在以下三个任务中通过肌电图（EMG）信号推断出的肌肉激活（MA）的变化：i）抬起并释放负荷；ii）担任职位，并且iii）操纵工具。结果表明，该外装服能够降低EMG活性（在24.6％和64.6％之间），并且评估了语音识别模块的识别率（94.8％）。ii）担任职位，并且iii）操纵工具。结果表明，该外装服能够降低EMG活性（在24.6％和64.6％之间），并且评估了语音识别模块的识别率（94.8％）。ii）担任职位，并且iii）操纵工具。结果表明，该外装服能够降低EMG活性（在24.6％和64.6％之间），并且评估了语音识别模块的识别率（94.8％）。