Collaborative Research: NRI: INT: Customizable Lower-Limb Wearable Robot using Soft-Wearable Sensor to Assist Occupational Workers

该奖项支持一个综合性的合作项目，该项目旨在开发一种个性化的下肢辅助可穿戴机器人，以减少在搬运等体力密集型活动中的人力。该机器人的工作原理是通过使用软可穿戴电子设备感知用户的身体努力，并做出相应的反应来减少这种努力。这项工作在涉及重量的工厂工人中有重要的应用，因为过度劳累伤害既昂贵，又经常使人丧失能力。这项研究调查了这种可穿戴机器人策略在减少人类劳动方面的有效性，并开发了提高可穿戴机器人和软可穿戴电子产品利用率的策略。对每个人类佩戴者的机器人辅助是使用基于各种度量的估计方法来定制的。该估计方法也可用于设计可穿戴机器人的训练方法。这种软可穿戴传感器将在机器人以及与诊断、监测和治疗相关的医疗应用中发挥作用。拟议的项目将研究和教育结合在一起，开发了一门基于项目的可穿戴机器人课程，并支持研究生和本科生在独立研究和论文研究方面的指导。该项目通过帮助维护可穿戴机器人试验床来加强教育和研究的基础设施。研究成果将通过出版物、软件和数据集广泛传播。研究团队成员有三个目标，这三个目标有助于实现可穿戴机器人个性化辅助的定制化目标。首先，将通过确定替代优化标准来改进定制过程，以有效地估计用户在体力密集型活动期间的体力努力。这将通过使用传统的生理传感器(如肌肉活动传感器)对用户的努力进行快速而稳健的估计，然后使用新的软可穿戴电子设备进行估计来实现。其次，这项工作将增强软可穿戴电子设备，目标是改进和取代传统传感器。相关任务将探索使用现有的软可穿戴电子设备作为传感器的可行性，然后迭代改进电子设备和估计方法，以准确地感知和估计生理状态。第三，这项研究将整合和评估在体力密集型活动中使用软可穿戴传感器测量实现的个性化辅助，例如使用脚踝外骨骼举起。这项任务将使用适当的衡量标准，如任务的能量消耗率和肌肉活动。这项工作将导致可穿戴机器人为体力密集型活动提供定制(个性化)帮助，以及软可穿戴传感器系统来评估用户的身体状态并提供实时反馈。评估结果可以应用于减轻或预防现有危险和对工人造成的伤害的干预措施；因此，这项研究的结果将使工厂、仓库和其他工业工作场所的人类劳动者受益。这项提议由疾病控制和预防中心(CDC)的国家职业安全与健康研究所(NIOSH)资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award supports an integrative, collaborative project to develop a personalized lower-limb assistive wearable robot that reduces human effort during physically intensive activities, such as lifting. The robot works by sensing a user’s physical effort using soft-wearable electronics and responding accordingly to reduce this effort. This work has significant applications in factory labor involving weights, as overexertion injuries are both costly and frequently disabling. This research investigates the effectiveness of this wearable robot strategy in reducing human effort and develops strategies to improve the utilization of wearable robots and soft wearable electronics. The robot assistance to each individual human wearer is customized using an estimation method based on various metrics. The estimation method can also be used to design a training method using a wearable robot. The soft wearable sensors will be useful in robotics as well as medical applications related to diagnosis, monitoring, and therapeutics. The proposed project integrates research and education by developing a project-based course on wearable robotics and supporting graduate and undergraduate student mentoring in independent research and thesis studies. The project strengthens the infrastructure for education and research by helping maintain wearable robot testbeds. The research results will be broadly disseminated through publications, software, and data sets. The research team members have three objectives that contribute to the goal of customizability in wearable robot personalized assistance. First, the customization process will be improved by identifying alternative optimization criteria to efficiently estimate the user’s physical effort during physically intensive activities. This will be accomplished through a rapid and robust estimate of the user effort using a conventional physiological sensor, such as a muscle activity sensor, followed by an estimate using new soft wearable electronics. Second, the work will enhance soft-wearable electronics with the goal of improving on and replacing conventional sensors. Associated tasks will explore the feasibility of using existing soft wearable electronics as sensors and then iteratively improve the electronics and estimation method to accurately sense and estimate physiological status. Third, the study will integrate and evaluate the personalized assistance achieved using soft wearable sensor measurements in a physically intensive activity, such as lifting using an ankle exoskeleton. This task will use appropriate metrics such as energy expenditure rate of the task and muscle activity. The work will result in customized (personalized) assistance available from a wearable robot for physically intensive activities and a soft wearable sensor system to evaluate the physical status of the user and provide real-time feedback. The evaluation outcomes can be applied in interventions to mitigate or prevent existing hazards and resulting injuries to workers; thus, the results of this research will benefit human laborers in factories, warehouses, and other industrial workplaces.This proposal was funded with the National Institute for Occupational Safety and Health (NIOSH) in the Center for Disease Control and Prevention (CDC).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.