Improving the parameters of neural oscillators to generate joint trajectories of an exoskeleton for lower limbs

Gomes, Marciel A.; Siqueira, Adriano A. G.; Gobbo, Rafael Gomes

doi:10.1109/icca.2011.6138064

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…The Matsuoka neural oscillator has been fully investigated in some literature. [ 25 26 27 28 ] A single Matsuoka neural oscillator is composed of two coupled neurons with self-inhibition. [ 27 ] The mathematical description is given below.…”

Section: Methodsmentioning

confidence: 99%

“…[ 27 ] In addition, the output frequency of an oscillator is roughly proportional to 1/ T 1 . [ 28 ]…”

Section: Methodsmentioning

confidence: 99%

“…The range of the obtained frequency related to 10 different tremor bursts and the generated artificial tremors related to a healthy subject was from 3.9 Hz to 4 Hz. Therefore, the parameters of the oscillator were chosen in away[ 26 27 28 ] that the frequency of the neural oscillators was 4 Hz [ Table 1 and Figure 4 ].…”

Section: Methodsmentioning

confidence: 99%

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Prediction of the wrist joint position during a postural tremor using neural oscillators and an adaptive controller

et al. 2016

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The prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. Thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter-burst intervals. Since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underlie the proposed model. Two neural oscillators were adopted. Electromyogram (EMG) signals were recorded from the extensor carpi radialis and flexor carpi radialis muscles concurrent with the joint angle signals of a stroke subject in an arm constant-posture. The output frequency of each oscillator was equal to the frequency corresponding to the maximum value of power spectrum related to the rhythmic wrist joint angle signals which had been recorded during a postural tremor. The phase shift between the outputs of the two oscillators was equal to the phase shift between the muscle activation of the wrist flexor and extensor muscles. The difference between the two oscillators’ output signals was considered the main pattern. Along with a proportional compensator, an adaptive neural controller has adjusted the amplitude of the main pattern in such a way so as to minimize the wrist joint prediction error during a stroke patient's tremor burst and a healthy subject's generated artificial tremor. In regard to the range of wrist joint movement during the observed rhythmic motions, a calculated prediction error is deemed acceptable.

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Section: Methodsmentioning

confidence: 99%

“…[ 27 ] In addition, the output frequency of an oscillator is roughly proportional to 1/ T 1 . [ 28 ]…”

Section: Methodsmentioning

confidence: 99%

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Prediction of the wrist joint position during a postural tremor using neural oscillators and an adaptive controller

et al. 2016

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“…With the development of intelligent algorithms, more advanced methods have been proposed in optimizing gait trajectory recently. In Gomes et al, 30 the researchers improved the parameters of neural oscillators to generate joint trajectories. This work with an optimizing system developed to find optimal parameter of neural network.…”

Section: Introductionmentioning

confidence: 99%

Simulating human–machine coupled model for gait trajectory optimization of the lower limb exoskeleton system based on genetic algorithm

Ren

Liu

Chen

2020

International Journal of Advanced Robotic Systems

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The lower limb exoskeleton robot is capable of providing assisted walking and enhancing exercise ability of humans. The coupling human–machine model has attracted a lot of research efforts to solve the complex dynamics and nonlinearity within the system. This study focuses on an approach of gait trajectory optimization of lower limb exoskeleton coupled with human through genetic algorithm. The human–machine coupling system is studied in this article through multibody virtual simulation environment. Planning of the motion trajectory is carried out by the genetic algorithm, which is iteratively generated under optimization of a set of specially designed fitness functions. Human motion captured data are used to guide the evolution of gait trajectory generation method based on genetic algorithm. Experiments are carried out using the MATLAB/Simulink Multibody physical simulation engine and genetic algorithm-toolbox to generate a more natural gait trajectory, the results show that the proposed gait trajectory generation method can provide an anthropomorphic gait for lower limb exoskeleton device.

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“…With parameters tuned, it is verified in simulations that a 3-DOF planar robotic arm traces a given trajectory precisely, adapting to uneven external disturbances. Recently, although parameter optimization methods [18,19]…”

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confidence: 99%

Task-Oriented Parameter Tuning Based on Priority Condition for Biologically Inspired Robot Application

Kwon

Park

Yang

2015

Mathematical Problems in Engineering

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This work gives a biologically inspired control scheme for controlling a robotic system. Novel adaptive behaviors are observed from humans or animals even in unexpected disturbances or environment changes. This is why they have neural oscillator networks in the spinal cord to yield rhythmic-motor primitives robustly under a changing task. Hence, this work focuses on rhythmic arm movements that can be accomplished in terms of employing a control approach based on an artificial neural oscillator model. The main challenge is to determine various parameters for applying a neural feedback to robotic systems with performing a desired behavior and self-maintaining the entrainment effect. Hence, this work proposes a task-oriented parameter tuning algorithm based on the simulated annealing (SA). This work also illustrates how to technically implement the proposed control scheme exploiting a virtual force and neural feedback. With parameters tuned, it is verified in simulations that a 3-DOF planar robotic arm traces a given trajectory precisely, adapting to uneven external disturbances.

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Improving the parameters of neural oscillators to generate joint trajectories of an exoskeleton for lower limbs

Cited by 9 publications

References 13 publications

Prediction of the wrist joint position during a postural tremor using neural oscillators and an adaptive controller

Prediction of the wrist joint position during a postural tremor using neural oscillators and an adaptive controller

Simulating human–machine coupled model for gait trajectory optimization of the lower limb exoskeleton system based on genetic algorithm

Task-Oriented Parameter Tuning Based on Priority Condition for Biologically Inspired Robot Application

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