Parameter identification and adaptive compliant control of rehabilitation exoskeleton based on multiple sensors

Chen, Jing; Huang, Yuping; Guo, Xiaojun; Zhou, Shitong; Long, Jiang

doi:10.1016/j.measurement.2020.107765

Cited by 24 publications

(14 citation statements)

References 12 publications

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“…54 Cheng et al 55 have designed a sitting and lying exoskeleton robot for lower limb rehabilitation, as shown in Figure 12, which can be used to improve the stability of patient rehabilitation training. The sitting and lying rehabilitation robot designed by Chen et al, 56 as shown in Figure 13, can realize adaptive and compliant control of reference trajectory. The robot can better protect patients and provide effective rehabilitation training for patients.…”

Section: Gait Rehabilitation Exoskeleton (Gres)mentioning

confidence: 99%

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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: Gait Rehabilitation Exoskeleton (Gres)mentioning

confidence: 99%

“…Figure13. Mechanical structure of rehabilitation exoskeleton 56. (1-Man-machine interactive display device; 2-Telescopic mechanical leg structure; 3-Patients; 4-Seat structure with adjustable backrest; 5-Mobile platform structure.…”

mentioning

confidence: 99%

Lower limb rehabilitation exoskeleton robot: A review

Zhou

Yang

Xue

2021

Advances in Mechanical Engineering

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“…Torque sensors are mainly used in LLE. Chen et al, in [ 114 ], developed a LLE in which each joint is fitted with an absolute encoder, incremental encoder and torque sensor that record the joint angle, angular velocity and torque, respectively, and he proposed a method to predict the human motion intention while walking based on an estimation of the active joint torque of human lower limbs.…”

Section: Analytical Reviewmentioning

confidence: 99%

Sensors and Actuation Technologies in Exoskeletons: A Review

Tiboni

Borboni

Vérité

et al. 2022

Sensors

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Exoskeletons are robots that closely interact with humans and that are increasingly used for different purposes, such as rehabilitation, assistance in the activities of daily living (ADLs), performance augmentation or as haptic devices. In the last few decades, the research activity on these robots has grown exponentially, and sensors and actuation technologies are two fundamental research themes for their development. In this review, an in-depth study of the works related to exoskeletons and specifically to these two main aspects is carried out. A preliminary phase investigates the temporal distribution of scientific publications to capture the interest in studying and developing novel ideas, methods or solutions for exoskeleton design, actuation and sensors. The distribution of the works is also analyzed with respect to the device purpose, body part to which the device is dedicated, operation mode and design methods. Subsequently, actuation and sensing solutions for the exoskeletons described by the studies in literature are analyzed in detail, highlighting the main trends in their development and spread. The results are presented with a schematic approach, and cross analyses among taxonomies are also proposed to emphasize emerging peculiarities.

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“…By adjusting the control parameters of the upper limb impedance model, the sensitivity of the model to human-robot interaction could be adjusted to achieve the smooth control [15][16][17]. Zhang et al proposed a force sensorbased motion intention detection and guidance control mode [18]. For exoskeleton robots, since there are more humanrobot force interaction positions than end-effector-base robots, additional force sensors are needed.…”

Section: Introductionmentioning

confidence: 99%

Human-Exoskeleton Coupling Dynamics of a Multi-Mode Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

et al. 2021

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The purpose of this study is to establish the human-exoskeleton coupling (HEC) dynamic model of the upper limb exoskeleton, overcome the difficulties of dynamic modeling caused by the differences of individual and disease conditions and the complexity of musculoskeletal system, to achieve early intervention and optimal assistance for stroke patients. This paper proposes a method of HEC dynamics modeling, and analyzes the HEC dynamics in the patient-active training (PAT) and patient-passive training (PPT) mode, and designs a step-by-step dynamic parameter identification method suitable for the PAT and PPT modes. Comparing the HEC torques obtained by the dynamic model with the real torques measured by torque sensors, the root mean square error (RMSE) can be kept within 13% in both PAT and PPT modes. A calibration experiment was intended to further verify the accuracy of dynamic parameter identification. The theoretical torque of the load calculated by the dynamic model, is compared with the difference calculated by parameter identification. The trends and peaks of the two curves are similar, and there are also errors caused by experimental measurements. Furthermore, this paper proposes a prediction model of the patient's height and weight and HEC dynamics parameters in the PPT mode. The RMSE of the elbow and shoulder joints of the prediction model is 9.5% and 13.3%. The proposed HEC dynamic model is helpful to provide different training effects in the PAT and PPT mode and optimal training and assistance for stroke patients.INDEX TERMS Human-exoskeleton coupling dynamics, parameter identification, rehabilitation training.

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Parameter identification and adaptive compliant control of rehabilitation exoskeleton based on multiple sensors

Cited by 24 publications

References 12 publications

Lower limb rehabilitation exoskeleton robot: A review

Lower limb rehabilitation exoskeleton robot: A review

Sensors and Actuation Technologies in Exoskeletons: A Review

Human-Exoskeleton Coupling Dynamics of a Multi-Mode Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

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