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爱丽丝：基于机载肌骨模拟器驱动的下肢外骨骼机器人的概念开发。

ALICE: Conceptual Development of a Lower Limb Exoskeleton Robot Driven by an On-Board Musculoskeletal Simulator.

机构信息

Centre for Automation and Robotics (CAR), Universidad Politécnica de Madrid (UPM), 28006 Madrid, Spain.

Faculty of Engineering, Universidad Don Bosco (UDB), San Salvador, El Salvador.

出版信息

Sensors (Basel). 2020 Jan 31;20(3):789. doi: 10.3390/s20030789.

DOI:10.3390/s20030789
PMID:32023988
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7038445/
Abstract

OBJECTIVE

In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user's kinetic parameters.

BACKGROUND

Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept.

METHODOLOGY

We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator.

SIGNIFICANCE

This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies.

CONCLUSION

ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.

摘要

目的

本文介绍了一个名为 ALICE（辅助下肢控制外骨骼）的机器人平台的概念开发，用于运动和运动学步态特征描述。ALICE 平台包括一个机器人可穿戴外骨骼和一个机载肌肉驱动模拟器，用于估计用户的动力学参数。

背景

即使人类步态的运动学模式在文献中得到了很好的研究和报道，但运动的动力学仍然存在相当大的个体内变异性。ALICE 旨在成为一种先进的机械传感器，使我们能够实时计算动力学和运动学数据的信息，开辟了一种新的个性化康复概念。

方法

我们在开源环境中开发了一个完整的肌肉驱动模拟器，并使用从多发性硬化症患者获得的真实步态数据对其进行了验证。之后，我们设计、建模和控制了一个 6 自由度下肢外骨骼，每个执行器都带有惯性测量单元和位置/速度传感器。

意义

这个新的概念旨在成为一种改善病理性步态诊断和设计个性化机器人康复治疗的工具。

结论

ALICE 是第一个自动适应每个患者动力学和运动学步态参数的机器人平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfe6/7038445/ae09183deb0d/sensors-20-00789-g013.jpg
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