scholarly journals Analysis of the Human Interaction with a Wearable Lower-Limb Exoskeleton

2009 ◽  
Vol 6 (2) ◽  
pp. 245-256 ◽  
Author(s):  
Juan C. Moreno ◽  
Fernando Brunetti ◽  
Enrique Navarro ◽  
Arturo Forner-Cordero ◽  
José L. Pons
Keyword(s):  
Lower Limb ◽  
Healthy Subjects ◽  
Testing Procedure ◽  
Mechanical Tests ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Two Phase ◽  
Motion Patterns ◽  
Lower Limb Exoskeleton ◽  
Wearable Exoskeleton

The design of a wearable robotic exoskeleton needs to consider the interaction, either physical or cognitive, between the human user and the robotic device. This paper presents a method to analyse the interaction between the human user and a unilateral, wearable lower-limb exoskeleton. The lower-limb exoskeleton function was to compensate for muscle weakness around the knee joint. It is shown that the cognitive interaction is bidirectional; on the one hand, the robot gathered information from the sensors in order to detect human actions, such as the gait phases, but the subjects also modified their gait patterns to obtain the desired responses from the exoskeleton. The results of the two-phase evaluation of learning with healthy subjects and experiments with a patient case are presented, regarding the analysis of the interaction, assessed in terms of kinematics, kinetics and/or muscle recruitment. Human-driven response of the exoskeleton after training revealed the improvements in the use of the device, while particular modifications of motion patterns were observed in healthy subjects. Also, endurance (mechanical) tests provided criteria to perform experiments with one post-polio patient. The results with the post-polio patient demonstrate the feasibility of providing gait compensation by means of the presented wearable exoskeleton, designed with a testing procedure that involves the human users to assess the human-robot interaction.

Analyzing Motor Primitives of Healthy Subjects Wearing a Lower Limb Exoskeleton

2017 ◽  
Author(s):  
Wilian dos Santos ◽  
Samuel Lourenco ◽  
Adriano Siqueira ◽  
Polyana Ferreira Nunes
Keyword(s):  
Lower Limb ◽  
Healthy Subjects ◽  
Motor Primitives ◽  
Lower Limb Exoskeleton

scholarly journals Analysis of the human interaction with a wearable lower-limb exoskeleton

2009 ◽  
Vol 6 (2) ◽  
pp. 245-256 ◽  
Author(s):  
Juan C. Moreno ◽  
Fernando Brunetti ◽  
Enrique Navarro ◽  
Arturo Forner-Cordero ◽  
José L. Pons
Keyword(s):  
Lower Limb ◽  
Human Interaction ◽  
Lower Limb Exoskeleton

scholarly journals Control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhenlei Chen ◽  
Qing Guo ◽  
Huiyu Xiong ◽  
Dan Jiang ◽  
Yao Yan
Keyword(s):  
Lower Limb ◽  
Degrees Of Freedom ◽  
Position Control ◽  
Interaction Force ◽  
Human Robot Interaction ◽  
Detection Accuracy ◽  
Robot Interaction ◽  
Experiment Platform ◽  
Lower Limb Exoskeleton

AbstractIn this study, a humanoid prototype of 2-DOF (degrees of freedom) lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton. To improve the detection accuracy of the human-robot interaction torque, a BPNN (backpropagation neural networks) is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor. Meanwhile, the backstepping controller is designed to realize the exoskeleton's passive position control, which means that the person passively adapts to the exoskeleton. On the other hand, a variable admittance controller is used to implement the exoskeleton's active follow-up control, which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance. To improve the wearable comfortable effect, serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters. Finally, the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

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

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 789 ◽  
Author(s):  
Manuel Cardona ◽  
Cecilia E. García Cena ◽  
Fernando Serrano ◽  
Roque Saltaren
Keyword(s):  
Lower Limb ◽  
Conceptual Development ◽  
Human Gait ◽  
Lower Limb Exoskeleton ◽  
Gait Parameters ◽  
Measurement Units ◽  
Mechanical Sensor ◽  
Wearable Exoskeleton ◽  
Novel Concept ◽  
Real Time Information

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.

scholarly journals Novel Design and Adaptive Fuzzy Control of a Lower-Limb Elderly Rehabilitation

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 343 ◽  
Author(s):  
Xin Zhang ◽  
Jiehao Li ◽  
Salih Ertug Ovur ◽  
Ziyang Chen ◽  
Xiangnan Li ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Lower Limb ◽  
Adaptive Fuzzy Control ◽  
The Elderly ◽  
Human Interaction ◽  
Stable Operation ◽  
Adaptive Fuzzy ◽  
Lower Limb Exoskeleton ◽  
And Control ◽  
Novel Design

Design and control of a lower-limb exoskeleton rehabilitation of the elderly are the main challenge for health care in the past decades. In order to satisfy the requirements of the elderly or disabled users, this paper presents a novel design and adaptive fuzzy control of lower-limb empowered rehabilitation, namely MOVING UP. Different from other rehabilitation devices, this article considers active rehabilitation training devices. Firstly, a novel product design method based on user experience is proposed for the lower-limb elderly exoskeleton rehabilitation. At the same time, in order to achieve a stable operation control for the assistant rehabilitation system, an adaptive fuzzy control scheme is discussed. Finally, the feasibility of the design and control method is validated with a detailed simulation study and the human-interaction test. With the booming demand in the global market for the assistive lower-limb exoskeleton, the methodology developed in this paper will bring more research and manufacturing interests.

scholarly journals Single Leg Gait Tracking of Lower Limb Exoskeleton Based on Adaptive Iterative Learning Control

2019 ◽  
Vol 9 (11) ◽  
pp. 2251 ◽  
Author(s):  
Bin Ren ◽  
Xurong Luo ◽  
Jiayu Chen
Keyword(s):  
Lower Limb ◽  
Iterative Learning Control ◽  
Tracking Error ◽  
Learning Control ◽  
Iterative Learning ◽  
Human Robot Interaction ◽  
Adaptive Iterative Learning Control ◽  
Interaction Torque ◽  
Lower Limb Exoskeleton ◽  
The Impact

The lower limb exoskeleton is a wearable human–robot interactive equipment, which is tied to human legs and moves synchronously with the human gait. Gait tracking accuracy greatly affects the performance and safety of the lower limb exoskeletons. As the human–robot coupling systems are usually nonlinear and generate unpredictive errors, a conventional iterative controller is regarded as not suitable for safe implementation. Therefore, this study proposed an adaptive control mechanism based on the iterative learning model to track the single leg gait for lower limb exoskeleton control. To assess the performance of the proposed method, this study implemented the real lower limb gait trajectory that was acquired with an optical motion capturing system as the control inputs and assessment benchmark. Then the impact of the human–robot interaction torque on the tracking error was investigated. The results show that the interaction torque has an inevitable impact on the tracking error and the proposed adaptive iterative learning control (AILC) method can effectively reduce such error without sacrificing the iteration efficiency.

Variable Geometry Stair Ascent and Descent Controller for a Powered Lower Limb Exoskeleton

2018 ◽  
Vol 12 (3) ◽  
Author(s):  
Andrew Ekelem ◽  
Gerasimos Bastas ◽  
Christina M. Durrough ◽  
Michael Goldfarb
Keyword(s):  
Lower Limb ◽  
Healthy Subjects ◽  
Perceived Exertion ◽  
Time Consistency ◽  
Variable Geometry ◽  
Joint Torques ◽  
Control Approach ◽  
Lower Limb Exoskeleton ◽  
Stair Ascent ◽  
Cord Injury

This paper describes a control approach for a lower limb exoskeleton intended to enable stair ascent and descent of variable geometry staircases for individuals with paraplegia resulting from spinal cord injury (SCI). To assess the efficacy of ascent and descent functionality provided by the control approach, the controller was implemented in a lower limb exoskeleton and tested in experimental trials on three subjects with motor-complete SCI on three staircases of varying geometry. Results from the assessments indicate that subjects were able to capably ascend and descend step heights varying from 7.6 to 16.5 cm without changing control settings; the controller provided for step time consistency highly representative of healthy subjects (9.2% variation in exoskeleton step time, relative to 7.7% variation in healthy subjects); and the exoskeleton provided peak joint torques on average 110% and 74% of the healthy-subject peak joint torques during stair ascent and descent, respectively. Subject perceived exertion during the stair ascent and descent activities was rated between “light” and “very light.”

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