RISE-based adaptive control for EICoSI exoskeleton to assist knee joint mobility

Sherwani, Kashif I.K.; Kumar, Neelesh; Chemori, Ahmed; Khan, Munna; Mohammed, Samer

doi:10.1016/j.robot.2019.103354

Cited by 34 publications

(30 citation statements)

References 54 publications

(46 reference statements)

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“…(2) Control methods. As can be seen from the ''control strategy'' and ''Equipment test data & results'' column in the Table 1, researchers have used many different control methods, such as feedback control, 8,28,65 feed-forward control, 34,36 Speed-adaptive proportional myoelectric The maximum torque output is 12 Nm Sit-to-Stand Knee Exoskeleton 23 A single male adult Trajectory prediction Control based on joint Angle…”

Section: Discussionmentioning

confidence: 99%

“…Control methods. As can be seen from the “control strategy” and “Equipment test data & results” column in the Table 1, researchers have used many different control methods, such as feedback control, 8,28,65 feed-forward control, 34,36 Speed-adaptive proportional myoelectric control, 10 3 M control method 11 PID control, 12 Directed torque control. 16 The assistance types, data and metabolic reduction rate provided by these devices are different.…”

Section: Discussionmentioning

confidence: 99%

“…The exoskeleton designed by Sherwani et al 28 applied an adaptive RISE (Robust Integral of Sign Error) controller, which has good robustness and the efficiency of tracking the reference trajectory. It can calculate the patient's intention to control the walking trajectory or movement according to the electromyogram signal, and can assist users to achieve knee flexion/extension movement.…”

Section: Knee Exoskeleton Robots (Kers)mentioning

confidence: 99%

See 2 more Smart Citations

Lower limb rehabilitation exoskeleton robot: A review

Zhou

Yang

Xue

2021

Advances in Mechanical Engineering

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Lower limb rehabilitation exoskeleton robots (LLRERs) play a positive role in lower limb rehabilitation and assistance for patients with lower limb disorders, and they are helpful to improve patients’ physical status. More and more experiments pay more attention to the kinematic and dynamic data characteristics of different patient groups. However, it is not clear whether these devices have broad adaptability and their clinical significance, so it is necessary to summarize and analyze these research results. This paper summarizes the LLRERs prototype and product in recent years, also compares the advantages and disadvantages of the theory and technology used in these research, and compares the functional characteristics of the devices, finally summarizes the aspects of the LLRERs to be improved. These devices apply advanced theories, techniques or structures, as well as human kinematics and dynamics data. However, due to the complexity of human body characteristics and movement rules, the theory or technology applied in the study design of LLRERs remains to be further studied, which can be improved in many aspects, such as improve the human-computer cooperation of equipment or carry out clinical trials. This paper can provide reference for researchers and designers in the future study, as well as understanding and selecting LLRERs for all kinds of therapist and patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Knee Exoskeleton Robots (Kers)mentioning

confidence: 99%

See 1 more Smart Citation

Lower limb rehabilitation exoskeleton robot: A review

Zhou

Yang

Xue

2021

Advances in Mechanical Engineering

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“…In the future, our adaptive control strategy may be improved by adding automatic updates of the stiffness values using knee moments estimated from prior gait cycles while walking with the exoskeleton and by extending the adaptive model to include the swing phase. Another approach is to ensure accurate tracking of the knee joint desired trajectory while allowing limited errors (Sherwani et al, 2020). Although not evaluated here, we have implemented a knee trajectory-based strategy in P.REX (impedance mode).…”

Section: Discussionmentioning

confidence: 99%

“…In addition to recent advances in hardware, a variety of control strategies have recently been reported for use in ambulatory individuals that aim to provide adaptive or real-time adjustable assistance to the knee and/or ankle joint during walking. For example, an adaptive robust integral of sign error (or adaptive RISE) controller has been developed and implemented for a knee exoskeleton that achieves excellent trajectory tracking while also providing asymptotic stability (Sherwani et al, 2020). A feature-based knee moment estimation algorithm was developed for the NIH pediatric exoskeleton to provide real-time assistance that is proportional to user effort (Lerner et al, 2016b).…”

Section: Introductionmentioning

confidence: 99%

A Pediatric Knee Exoskeleton With Real-Time Adaptive Control for Overground Walking in Ambulatory Individuals With Cerebral Palsy

Hochstein

Kim

et al. 2021

Front. Robot. AI

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Gait training via a wearable device in children with cerebral palsy (CP) offers the potential to increase therapy dosage and intensity compared to current approaches. Here, we report the design and characterization of a pediatric knee exoskeleton (P.REX) with a microcontroller based multi-layered closed loop control system to provide individualized control capability. Exoskeleton performance was evaluated through benchtop and human subject testing. Step response tests show the averaged 90% rise was 26 ± 0.2 ms for 5 Nm, 22 ± 0.2 ms for 10 Nm, 32 ± 0.4 ms for 15 Nm. Torque bandwidth of P.REX was 12 Hz and output impedance was less than 1.8 Nm with control on (Zero mode). Three different control strategies can be deployed to apply assistance to knee extension: state-based assistance, impedance-based trajectory tracking, and real-time adaptive control. One participant with typical development (TD) and one participant with crouch gait from CP were recruited to evaluate P.REX in overground walking tests. Data from the participant with TD were used to validate control system performance. Kinematic and kinetic data were collected by motion capture and compared to exoskeleton on-board sensors to evaluate control system performance with results demonstrating that the control system functioned as intended. The data from the participant with CP are part of a larger ongoing study. Results for this participant compare walking with P.REX in two control modes: a state-based approach that provided constant knee extension assistance during early stance, mid-stance and late swing (Est+Mst+Lsw mode) and an Adaptive mode providing knee extension assistance proportional to estimated knee moment during stance. Both were well tolerated and significantly improved knee extension compared to walking without extension assistance (Zero mode). There was less reduction in gait speed during use of the adaptive controller, suggesting that it may be more intuitive than state-based constant assistance for this individual. Future work will investigate the effects of exoskeleton assistance during overground gait training in children with neurological disorders and will aim to identify the optimal individualized control strategy for exoskeleton prescription.

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Swift augmented human–robot dynamics modeling for rehabilitation planning analyses

Akbari,

Mahdizadeh,

Moosavian

et al. 2024

Multibody Syst Dyn

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With the widespread implementation of robotics exoskeletons in rehabilitation, modeling and dynamics analysis of such highly nonlinear coupled systems has become significantly important. In this paper, a swift numerical human-robot dynamics modeling has been developed to achieve accurate and realistic interpretation. This takes into consideration the separation and impact between multiple bodies for rehabilitation planning. To this end, first, a novel parallel algorithm combined with sequential interaction conditions is proposed based on the numerical Recursive Newton-Euler method. The approach begins by deriving separated numerical models for the complicated system: i.e. both the human and the robot. These models are then augmented, with a primary focus on reducing the error of the interaction conditions, including positions and forces. To evaluate the proposed model accuracy, the results are compared with a previously validated non-recursive analytical model. Additionally, the quality of the connection between the human and the robot is assessed to establish a suitable control objective and an effective interaction strategy for rehabilitation planning. The study employs a lower-limb walking assistive robot developed in the ARAS lab (RoboWalk) to validate the proposed method. The algorithm is empirically implemented on the RoboWalk test stand, ensuring the integrity of the proposed dynamics modeling. Finally, the effectiveness of the model-based controller is assessed by using the proposed method, providing valuable tools for the enhancement of overall performance of such a complex dynamics system.

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RISE-based adaptive control for EICoSI exoskeleton to assist knee joint mobility

Cited by 34 publications

References 54 publications

Lower limb rehabilitation exoskeleton robot: A review

Lower limb rehabilitation exoskeleton robot: A review

A Pediatric Knee Exoskeleton With Real-Time Adaptive Control for Overground Walking in Ambulatory Individuals With Cerebral Palsy

Swift augmented human–robot dynamics modeling for rehabilitation planning analyses

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