Development and control of a robotic lower limb exoskeleton for paraplegic patients

Yang, Mingxing; Wang, Xingsong; Zhi-yong, Zhu; Xi, Ruru; Wu, Qingcong

doi:10.1177/0954406218761484

Cited by 17 publications

(11 citation statements)

References 32 publications

(30 reference statements)

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“…The user directly determines the mode of operation of the exoskeleton, using input devices such as buttons [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] or voice commands [35,36]. These methods are currently the most common due to their ease of implementation, higher predictability, and lower risk of errors.…”

Section: Explicit/manual User Input (Mui)mentioning

confidence: 99%

Review of control strategies for lower-limb exoskeletons to assist gait

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

161

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Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Methods In addition to covering the recent publications on the control of lower-limb exoskeletons for gait assistance, an effort has been made to review the controllers independently of the hardware and implementation aspects. The common 3-level structure (high, middle, and low levels) is first used to separate the continuous behavior (mid-level) from the implementation of position/torque control (low-level) and the detection of the terrain or user’s intention (high-level). Within these levels, different approaches (functional units) have been identified and combined to describe each considered controller. Results 291 references have been considered and sorted by the proposed classification. The methods identified in the high-level are manual user input, brain interfaces, or automatic mode detection based on the terrain or user’s movements. In the mid-level, the synchronization is most often based on manual triggers by the user, discrete events (followed by state machines or time-based progression), or continuous estimations using state variables. The desired action is determined based on position/torque profiles, model-based calculations, or other custom functions of the sensory signals. In the low-level, position or torque controllers are used to carry out the desired actions. In addition to a more detailed description of these methods, the variants of implementation within each one are also compared and discussed in the paper. Conclusions By listing and comparing the features of the reviewed controllers, this work can help in understanding the numerous techniques found in the literature. The main identified trends are the use of pre-defined trajectories for full-mobilization and event-triggered (or adaptive-frequency-oscillator-synchronized) torque profiles for partial assistance. More recently, advanced methods to adapt the position/torque profiles online and automatically detect terrains or locomotion modes have become more common, but these are largely still limited to laboratory settings. An analysis of the possible underlying reasons of the identified trends is also carried out and opportunities for further studies are discussed.

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Section: Explicit/manual User Input (Mui)mentioning

confidence: 99%

Review of control strategies for lower-limb exoskeletons to assist gait

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

161

View full text Add to dashboard Cite

show abstract

“…In order to comprehensively measure the degree of stability during robot motion, the ZMP stability margin J z was used to characterize the degree of stability in the horizontal direction, and the expression is shown in Eq. (8).…”

Section: Stability Criteriamentioning

confidence: 99%

“…With the development of research, there have been many mature lower limb rehabilitation robots, such as Rewalk [4], Mina exoskeleton robot [5], MindWalker [6], and Vanderbilt [7]. Since the exoskeleton robot drives wearers to move, the gait trajectory of the robot determines whether the wearer's rehabilitation training is practical [8]. Therefore, maintaining a stable and smooth gait trajectory is one of the critical technologies in rehabilitation robots.…”

Section: Introductionmentioning

confidence: 99%

Gait multi-objectives optimization of lower limb exoskeleton robot based on BSO-EOLLFF algorithm

Zhang

Elsabbagh

2022

Robotica

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Aiming at problems of low optimization accuracy and slow convergence speed in the gait optimization algorithm of lower limb exoskeleton robot, a novel gait multi-objectives optimization strategy based on beetle swarm optimization (BSO)-elite opposition-based learning (EOL) levy flight foraging (LFF) algorithm was proposed. In order to avoid the algorithm from falling into the local optimum, the EOL strategy with global search capability, the LFF strategy with local search capability and the dynamic mutation strategy with high population diversity were introduced to improve optimization performance. The optimization was performed by establishing a multi-objectives optimization function with the robot’s gait zero moment point (ZMP) stability margin and driving energy consumption. The joint comparative tests were carried out in SolidWorks, ADAMS and MATLAB software. The simulation results showed that compared with the particle swarm optimization algorithm and the BSO algorithm, the ZMP stability margin obtained by the BSO-EOLLFF algorithm was increased, and the average driving energy consumption was reduced by 25.82% and 17.26%, respectively. The human-machine experiments were conducted to verify the effectiveness and superiority. The robot could realize stable and smooth walking with less energy consumption. This research will provide support for the application of exoskeleton robot.

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“…In recent years, due to the development of science and technology and the expansion of human activity space, the research on mobile robots has received great attention, and there are more and more types of mobile robots, ranging from entertainment robot toys, household service robots, to engineering adventures ( Yang et al, 2019 ). Mobile robots can move to the goals set by people and complete the set operation tasks.…”

Section: Introductionmentioning

confidence: 99%

Detection and Analysis of Bionic Motion Pose of Single Leg and Hip Joint Based on Random Process

Zhang

Seung-Soo

2022

Front. Bioeng. Biotechnol.

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Based on the spectral representation method of random function and combined with memoryless nonlinear translation theory, this paper analyzes the transformation relationship between potential Gaussian random process and non-Gaussian random process, and successfully generates a stationary non-Gaussian random process that conforms to the target non-Gaussian random process. For the non-stationary non-Gaussian random process simulation, on the basis of the stationary Gaussian random process, the intensity non-stationary uniform modulation model is used to modulate it, and combined with the nonlinear translation theory, the non-stationary non-Gaussian random process conforming to the target non-Gaussian random process is obtained. Aiming at the single-leg bouncing model based on the flexible rotary hip joint, the stability of its bouncing motion under passive motion is studied, and the influence of the flexible hip rotary joint on the motion stability is analyzed by comparing the single-leg bouncing motion characteristics of the free rotary hip joint. Based on the inverse dynamic control of the air phase, the fixed point distribution of the single-leg bounce of the flexible rotary hip joint was improved, and the function of the flexible rotary hip joint in the energy conversion of the bouncing motion was studied by establishing the energy consumption evaluation function. The kinematic performance verification, dynamic performance verification, dynamic parameter identification verification, and modal experiment simulation analysis were carried out for the built experimental platform, and the comparison and analysis with its theoretical model were carried out. The results show that the theoretical motion trajectory of the test mobile platform is basically consistent with the actual motion trajectory in the X and Y directions, and there is a small error in the Z-axis direction, and the error is within an acceptable range, indicating that the experimental platform system can be used to simulate the human hip joint. There is a large error between the theoretical value of the driving torque calculated by the theoretical value of the dynamic parameters and the measured value, and the dynamic theoretical model cannot accurately predict the driving torque. The predicted value of the driving torque calculated by using the identification value of the dynamic parameters is in good agreement with the measured torque, and its confidence is increased by 10–16%, indicating that the dynamic parameter identification method in this paper has a high degree of confidence.

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Development and control of a robotic lower limb exoskeleton for paraplegic patients

Cited by 17 publications

References 32 publications

Review of control strategies for lower-limb exoskeletons to assist gait

Review of control strategies for lower-limb exoskeletons to assist gait

Gait multi-objectives optimization of lower limb exoskeleton robot based on BSO-EOLLFF algorithm

Detection and Analysis of Bionic Motion Pose of Single Leg and Hip Joint Based on Random Process

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