Admittance Control Based on EMG-Driven Musculoskeletal Model Improves the Human–Robot Synchronization

Zhuang, Yu; Yao, Shaowei; Ma, Chenming; Song, Rong

doi:10.1109/tii.2018.2875729

Cited by 71 publications

(26 citation statements)

References 28 publications

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“…In this method, generally the calculated torque is directly applied to the joint [ 96 , 116 , 232 – 234 , 234 – 236 ], but in some papers the torque is fed to an admittance model to generate position commands for the low-level controller [ 237 , 238 ]. In terms of the approach to calculating the intended torque from muscle activity, several variants can be distinguished: The amplification of independent muscles activities is typically implemented with one artificial muscle per biologic muscle [ 239 ].…”

Section: Assistive Strategiesmentioning

confidence: 99%

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

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

194

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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: Assistive Strategiesmentioning

confidence: 99%

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

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

194

View full text Add to dashboard Cite

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“…Steady EMG signals can be obtained with data collection for less time than using metabolic cost in each control law of HIL optimization. Nowadays, EMG signals have been widely used to control wearable robot devices [15] [18], [27], [28], [30].…”

Section: Introductionmentioning

confidence: 99%

Selection of Muscle-Activity-Based Cost Function in Human-in-the-Loop Optimization of Multi-Gait Ankle Exoskeleton Assistance

Han

Wang

Zhang

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Using "human-in-the-loop" (HIL) optimization can obtain suitable exoskeleton assistance patterns to improve walking economy. However, there are differences in these patterns under different gait conditions, and currently most HIL optimizations use metabolic cost, which requires long periods to be estimated for each control law, as the physiological objective to minimize. We aimed to construct a muscle-activity-based cost function and to find the appropriate initial assistance patterns in HIL optimization of multi-gait ankle exoskeleton assistance. One healthy subject walked assisted by an ankle exoskeleton under nine gait conditions and each condition was the combination of different walking speeds, ground slopes and load weights. Ten assistance patterns were provided for the subject under each gait condition. Then we constructed a cost function based on surface electromyography signals of four lower leg muscles and select the muscle weight combination by using particle swarm optimization algorithm to compose the cost function with maximum differences between different assistance patterns. The mean weights of medial gastrocnemius, lateral gastrocnemius, soleus and tibialis anterior activity under all gait conditions are 0.153, 0.104, 0.953 and 0.145, respectively. Then we verified the effectiveness of this cost function by optimization and validation experiments conducted on four subjects. Our results are expected to guide the selection of muscle-activitybased cost functions and improve the time efficiency of HIL optimization.

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“…Admittance control acts in favor of this change of position, facilitating the user's interaction with the robotic structure. This method softens the stiffness of the structure [23], usually taking position or speed into account as control parameters.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Impedance-Admittance Control for Upper Limb Exoskeleton Using Electromyography

et al. 2020

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Exoskeletons are wearable mobile robots that combine various technologies to enable limb movement with greater strength and endurance, being used in several application areas, such as industry and medicine. In this context, this paper presents the development of a hybrid control method for exoskeletons, combining admission and impedance control based on electromyographic input signals. A proof of concept of a robotic arm with two degrees of freedom, mimicking the functions of a human’s upper limb, was built to evaluate the proposed control system. Through tests that measured the discrepancy between the angles of the human joint and the joint of the exoskeleton, it was possible to determine that the system remained within an acceptable error range. The average error is lower than 4.3%, and the robotic arm manages to mimic the movements of the upper limbs of a human in real-time.

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Admittance Control Based on EMG-Driven Musculoskeletal Model Improves the Human–Robot Synchronization

Cited by 71 publications

References 28 publications

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

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

Selection of Muscle-Activity-Based Cost Function in Human-in-the-Loop Optimization of Multi-Gait Ankle Exoskeleton Assistance

Hybrid Impedance-Admittance Control for Upper Limb Exoskeleton Using Electromyography

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