Article
Robotics
Hao Lee, Jacob Rosen
Summary: Humans use more energy to walk compared to other limb-based locomotion animals, mainly due to heel strikes and negative work during human gait. This study focuses on utilizing a lower limb exoskeleton to absorb and store energy at one phase of the gait cycle, and release it later, aiming to improve energy efficiency during walking. The simulation results indicate that wearing a backward-knee exoskeleton can reduce the cost of transport (CoT) by 15% while carrying external loads, and further reduction to 35% can be achieved when the exoskeleton incorporates energy recycling principles. Animals with reversed knees, such as ostriches, demonstrate improved energy efficiency in gait.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Engineering, Mechanical
Jingshuai Liu, Yong He, Jiantao Yang, Wujing Cao, Xinyu Wu
Summary: This study presents a novel mechanism for a self-balancing lower extremity exoskeleton, which is fully actuated with 12 DOFs and structurally consistent with human anatomy. The mechanism is designed based on a bio-inspired design methodology and achieves self-balancing walking ability, demonstrating its feasibility for rehabilitation purposes.
MECHANISM AND MACHINE THEORY
(2022)
Article
Engineering, Electrical & Electronic
Lingzhou Yu, Harun Leto, Shaoping Bai
Summary: This paper introduces an assistive lower-limb exoskeleton (ALEXO) for active walking assistance. The development of the ALEXO including mechanical design, sensors and gait control is described. The effectiveness of the developed exoskeleton with the proposed control method for walking assistance is demonstrated through simulations and system tests.
Article
Computer Science, Artificial Intelligence
Matteo Laffranchi, Stefano D'Angella, Christian Vassallo, Chiara Piezzo, Michele Canepa, Samuele De Giuseppe, Mirco Di Salvo, Antonio Succi, Samuele Cappa, Giulio Cerruti, Silvia Scarpetta, Lorenzo Cavallaro, Nicolo Boccardo, Marialaura D'Angelo, Claudia Marchese, Jody A. Saglia, Eleonora Guanziroli, Giacinto Barresi, Marianna Semprini, Simone Traverso, Stefano Maludrottu, Franco Molteni, Rinaldo Sacchetti, Emanuele Gruppioni, Lorenzo De Michieli
Summary: The paper introduces TWIN, a modular lower limb exoskeleton designed for spinal-cord injury (SCI) patients, developed through participatory investigations and user-centered design methods. The approach proved to be effective in adapting design goals towards user needs, resulting in an exoskeleton with modular mechatronics and novel lateral quick release systems with high potential for usability in its intended use.
FRONTIERS IN NEUROROBOTICS
(2021)
Article
Robotics
Wujing Cao, Chunjie Chen, Dashuai Wang, Xinyu Wu, Lingxing Chen, Tiantian Xu, Jingshuai Liu
Summary: A rigid-soft lower limb exoskeleton for loaded walking assistance was proposed and its motion flexibility, load transfer ability, and metabolic cost were investigated.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Multidisciplinary Sciences
Qiaoling Meng, Bolei Kong, Qingxin Zeng, Cuizhi Fei, Hongliu Yu
Summary: This paper proposes a conceptual design method for a hybrid-actuated lower limb exoskeleton based on energy consumption simulation. It establishes a human-machine coupling model in OpenSim based on three proposed passive assistance schemes. The method of simulating muscle driving is used to find the scheme that can reduce the metabolic rate the most, and an active-passive cooperative control strategy is designed to improve the wearer's mobility.
Article
Automation & Control Systems
Lukas Bergmann, Oliver Lueck, Daniel Voss, Philipp Buschermoehle, Lin Liu, Steffen Leonhardt, Chuong Ngo
Summary: This study presents the design of a new lower limb exoskeleton with variable stiffness actuators for compliant coupling. By using a nonlinear state estimation method, the subject's motion intention can be accurately estimated, providing more robust results.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Arthicha Srisuchinnawong, Chaicharn Akkawutvanich, Poramate Manoonpong
Summary: This study proposes an adaptive modular neural control (AMNC) algorithm for online gait synchronization and the adaptation of a lower-limb exoskeleton. The AMNC comprises several distributed and interpretable neural modules that interact with each other to effectively exploit neural dynamics and adopt feedback signals to quickly reduce the tracking error, thereby smoothly synchronizing the exoskeleton movement with the user's movement on the fly. The proposed AMNC provides further improvements in the locomotion phase, frequency, and shape adaptation compared to state-of-the-art control algorithms.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Du-Xin Liu, Jing Xu, Chunjie Chen, Xingguo Long, Dacheng Tao, Xinyu Wu
Summary: In this article, a vision-assisted autonomous lower-limb exoskeleton robot (VALOR) is developed to improve adaptability to complex walking environments. Through environmental information acquisition and autonomous decision-making, the robot can significantly enhance its adaptability. The feasibility of the proposed method is verified in a controlled indoor environment.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Jonathan Casas, Chen-Hao Chang, Victor H. Duenas
Summary: This article presents a learning-based strategy for interaction with a hybrid exoskeleton during treadmill walking. An adaptive control approach and functional electrical stimulation (FES) are used to provide joint assistance and activate muscles. Experimental results demonstrate that the learning controller outperforms classical adaptive control in terms of performance and parameter convergence speed.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Biomedical
Wujing Cao, Yue Ma, Chunjie Chen, Jingmin Zhang, Xinyu Wu
Summary: Soft lower limb exoskeletons (LLEs) are wearable devices that have the potential to improve walking efficiency. This study presented a new LLE for hip flexion assistance and introduced its hardware circuits design. Experimental tests showed that the designed hardware circuits can be applied to the LLE and it can improve walking efficiency by reducing muscle activity and metabolic cost.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
(2022)
Article
Automation & Control Systems
Chaobin Zou, Rui Huang, Jing Qiu, Qiming Chen, Hong Cheng
Summary: Lower limb exoskeletons have gained significant interest in assisting walking for paraplegic patients, especially on terrains with different gradients. An adaptive gait planning approach can help generate appropriate gaits for various slopes, providing flexibility and efficiency in locomotion. The proposed slope gradient estimator and dynamic gait generator offer a promising solution for exoskeletons and humanoid robots to adapt to sloped terrains, potentially inspiring further advancements in gait planning strategies for different terrains.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Moyao Gao, Zhanli Wang, Zaixiang Pang, Jianwei Sun, Jing Li, Shuang Li, Hansi Zhang
Summary: This study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot to assist people with impairments in standing and walking. The robot has good comfort and flexibility, matching the human movement freedom. It provides effective assistance for patients' rehabilitation training.
Article
Chemistry, Multidisciplinary
Ibrahim Tijjani, Shivesh Kumar, Melya Boukheddimi
Summary: This paper presents a survey on the design and control of lower extremity exoskeletons for bipedal walking. The historical development of walking exoskeletons is reviewed, and various designs are categorized in different application areas. The designs are then studied from design, modeling, and control viewpoints. Finally, future research directions are discussed.
APPLIED SCIENCES-BASEL
(2022)
Article
Multidisciplinary Sciences
Mario Ortiz, Luis de la Ossa, Javier Juan, Eduardo Ianez, Diego Torricelli, Jesus Tornero, Jose M. Azorin
Summary: One important aspect of developing a brain-machine interface (BMI) for controlling an exoskeleton is assessing the subject's cognitive engagement during motor imagery tasks. However, there are limited databases that provide electroencephalography (EEG) data during the use of lower-limb exoskeletons. This study presents a database designed to assess motor imagery and attention to gait during exoskeleton control on flat and inclined surfaces, offering a valuable resource for researchers interested in EEG-based BMI development and testing.
