Design and Implementation of an Intelligent Control System for a Lower-Limb Exoskeleton to Reduce Human Energy Consumption

Talatian, Hamidreza; Karami, Mohammad Reza; Moradi, Hamed; Vossoughi, Gholamreza

doi:10.1109/mocast52088.2021.9493401

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…Plaza et al [35] used a pivotal pattern generator (CPG) based on an adaptive oscillator, and used the Hebbian learning algorithm for CPG for training and simulated the walking trajectory of human hip and knee joints based on the gait data of healthy subjects to achieve the prediction of gait trajectory. Talatian et al [36] were able to continuously modify the moment output and adjust the motion state in real time to identify different motion phases based on the EMG signals of different motion phases.…”

Section: Recognition Imitation Learning Identificationmentioning

confidence: 99%

Review of Human-exoskeleton Control Strategy for Lower Limb Rehabilitation Exoskeleton

Long

Guo

Chi

et al. 2023

J. Phys.: Conf. Ser.

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The research on exoskeleton robots has been widely carried out for many years around the world, especially the development of new-style lower limb exoskeletons for rehabilitation and assistance is one of the key research directions. The focus on the control system of lower limb exoskeletons for rehabilitation is discussed. Based on the public literature in recent years, it is summarized from three aspects, i.e., movement mode switching, human gait recognition and human-exoskeleton interaction control. Finally, the technical issues of the current lower limb rehabilitation exoskeleton control strategy are discussed. The future development prospects and research directions of the lower limb rehabilitation exoskeleton are prospected, and some suggestions on how to achieve a more efficient and accurate control are given.

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Section: Recognition Imitation Learning Identificationmentioning

confidence: 99%

Review of Human-exoskeleton Control Strategy for Lower Limb Rehabilitation Exoskeleton

Long

Guo

Chi

et al. 2023

J. Phys.: Conf. Ser.

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show abstract

“…The information provided by the AO could be used only for assistance timing, considering the phase and frequency of the gait ( Lenzi et al, 2013 ; Aguirre-Ollinger, 2015 ; Yan et al, 2015b ; Cempini et al, 2015 ; Giovacchini et al, 2015 ; Ruiz Garate et al, 2016 ; Seo et al, 2016 ; Parri et al, 2017 ; Ruiz Garate et al, 2017 ; Sanz-Morere et al, 2018 ; Aguirre-Ollinger et al, 2019 ; Ishmael et al, 2019 ; Aguirre-Ollinger and Yu, 2021 ; Talatian et al, 2021 ; Tricomi et al, 2021 ), or it could also be used to reconstruct the source signal to use it directly as a reference for the low-level controller ( Zanotto et al, 2014 ) or as filtered information to generate an assistive reference ( Ronsse et al, 2011 ).…”

Section: State Of the Artmentioning

confidence: 99%

Coordination Between Partial Robotic Exoskeletons and Human Gait: A Comprehensive Review on Control Strategies

Lora-Millán

Moreno

Rocón

2022

Front. Bioeng. Biotechnol.

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Lower-limb robotic exoskeletons have become powerful tools to assist or rehabilitate the gait of subjects with impaired walking, even when they are designed to act only partially over the locomotor system, as in the case of unilateral or single-joint exoskeletons. These partial exoskeletons require a proper method to synchronize their assistive actions and ensure correct inter-joint coordination with the user’s gait. This review analyzes the state of the art of control strategies to coordinate the assistance provided by these partial devices with the actual gait of the wearers. We have analyzed and classified the different approaches independently of the hardware implementation, describing their basis and principles. We have also reviewed the experimental validations of these devices for impaired and unimpaired walking subjects to provide the reader with a clear view of their technology readiness level. Eventually, the current state of the art and necessary future steps in the field are summarized and discussed.

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“…Lower-limb exoskeletons typically comprise a frame, actuators, sensors, and control systems that enable them to mimic human locomotion (Bhardwaj et al, 2021). Batteries or other energy sources can power them, and they can be controlled by a person's actions, by a software-based controller, or by a combination of both (Talatian et al, 2021). Lower-limb exoskeletons are composed of actuators disposed on multiple joints, in particular the hips, ankles, or knees of the users.…”

Section: Introductionmentioning

confidence: 99%

AI-based methodologies for exoskeleton-assisted rehabilitation of the lower limb: a review

Coser,

Tamantini,

Soda

et al. 2024

Front. Robot. AI

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Over the past few years, there has been a noticeable surge in efforts to design novel tools and approaches that incorporate Artificial Intelligence (AI) into rehabilitation of persons with lower-limb impairments, using robotic exoskeletons. The potential benefits include the ability to implement personalized rehabilitation therapies by leveraging AI for robot control and data analysis, facilitating personalized feedback and guidance. Despite this, there is a current lack of literature review specifically focusing on AI applications in lower-limb rehabilitative robotics. To address this gap, our work aims at performing a review of 37 peer-reviewed papers. This review categorizes selected papers based on robotic application scenarios or AI methodologies. Additionally, it uniquely contributes by providing a detailed summary of input features, AI model performance, enrolled populations, exoskeletal systems used in the validation process, and specific tasks for each paper. The innovative aspect lies in offering a clear understanding of the suitability of different algorithms for specific tasks, intending to guide future developments and support informed decision-making in the realm of lower-limb exoskeleton and AI applications.

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Design and Implementation of an Intelligent Control System for a Lower-Limb Exoskeleton to Reduce Human Energy Consumption

Cited by 5 publications

References 13 publications

Review of Human-exoskeleton Control Strategy for Lower Limb Rehabilitation Exoskeleton

Review of Human-exoskeleton Control Strategy for Lower Limb Rehabilitation Exoskeleton

Coordination Between Partial Robotic Exoskeletons and Human Gait: A Comprehensive Review on Control Strategies

AI-based methodologies for exoskeleton-assisted rehabilitation of the lower limb: a review

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