Human-Exoskeleton System Dynamics Identification Using Affordable Sensors

Mallat, Randa; Bonnet, Vincent; Huo, Weiguang; Karasinski, Patrick; Amirat, Yacine; Khalil, Mohamad

doi:10.1109/icra.2018.8463178

Cited by 9 publications

(6 citation statements)

References 22 publications

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“…The robustness analysis detailed in Section IV-C shows that an accurate wearer-exoskeleton system model can enable not only a desired assistance but also a large assistive ratio (see (39)). In our previous work [41], an identification method was proposed to identify a human-exoskeleton system composed of 20-DoF and 11 rigid segments. In this study, a simplified 3-DoF model ( 1) is considered to reproduce STS movements.…”

Section: Parametric Identification Of Human-exoskeleton Systemmentioning

confidence: 99%

Impedance Modulation Control of a Lower-Limb Exoskeleton to Assist Sit-to-Stand Movements

et al. 2022

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As an important movement of the daily living activities, sit-to-stand (STS) movement is usually a difficult task facing elderly and dependent people. In this article, a novel impedance modulation strategy of a lower limb exoskeleton is proposed to provide appropriate power and balance assistance during STS movements while preserving the wearer's control priority. The impedance modulation control strategy ensures adaptation of the mechanical impedance of the human-exoskeleton system towards a desired one requiring less wearer's effect while reinforcing the wearer's balance control ability during STS movements. A human joint torque observer is designed to estimate the joint torques developed by the wearer using joint position kinematics instead of electromyography (EMG) or force sensors; a time-varying desired impedance model is proposed according to the wearer's lower limb motion ability. A virtual environmental force is designed for the balance reinforcement control. Stability and robustness of the proposed method are theoretically analyzed. Simulations were implemented to illustrate the characteristics and performance of the proposed approach. Experiments with four healthy subjects were carried out to evaluate the effectiveness of the proposed method and show satisfactory results in terms of appropriate power assist and balance reinforcement.

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Section: Parametric Identification Of Human-exoskeleton Systemmentioning

confidence: 99%

Impedance Modulation Control of a Lower-Limb Exoskeleton to Assist Sit-to-Stand Movements

et al. 2022

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“…The proposed control scheme requires knowledge of the subject's limb inertial parameters as well as the exoskeleton's link parameters. The latter can be easily acquired via Solidworks, while the former can be estimated following the method introduced in [38], i.e., estimating the limb's inertial parameters in proportion to the overall body mass, or through system identification by conducting the series of experiments presented in [48]. Model uncertainties and parametric errors may result in torques with different magnitudes, but they can still be assistive or resistive as intended.…”

Section: Limitation Of the Studymentioning

confidence: 99%

Trajectory-Free Control of Lower-Limb Exoskeletons Through Underactuated Total Energy Shaping

Lin

Gregg

2021

IEEE Access

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Kinematic control approaches for exoskeletons replicate normative joint kinematics associated with one specific task and user at a time, which makes it difficult to adjust to continuously-varying activities during gait training. These approaches also overly constrain individuals who have partial or full volitional control of their limbs, preventing these individuals from choosing their own preferred gait patterns. To address these issues, we proposed a matching framework for underactuated total energy shaping (i.e., shaping both the potential and kinetic energies) with human and environmental interaction to provide taskinvariant, energetic assistance. In our prior work, we designed assistive strategies to compensate for lowerlimb inertia in the actuated part of the mass matrix while leaving mass related terms unshaped. While these strategies have demonstrated potentia l gait benefits, shaping mass related terms in addition to lower-limb inertia can produce greater benefits as they are more dominant in determining human dynamics during locomotion. Moreover, previous definitions of closed-loop mass matrix with reduced inertial parameters cannot guarantee its positive definiteness. Having a non-positive definite mass matrix in the closed loop can render chaotic behaviors such as unbounded exoskeleton torques that are dangerous to human users. In this paper, we generalize our prior work to shape all inertial terms in the actuated part of the mass matrix while ensuring its positive definiteness in the closed loop. In addition, given a positive-definite, closed-loop mass matrix, we prove passivity from human input to joint velocity and highlight two Lyapunov stability results based on common assumptions of human joint control policies. We then show beneficial effects of the proposed assistive strategies such as reduced metabolic cost in simulations of a human-like model. We also show that the corresponding assistive torques closely match the human torques of an able-bodied subject.

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“…Perform affordable dynamic identification of a human-exoskeleton system based on the proposed MCS. [18] • C4. Develop a new framework for dynamics assessment and optimal model selection of a human-knee joint orthosis system.…”

Section: Thesis Contributions and Outlinementioning

confidence: 99%

“…Section 5.1 presents a further experimental validation of the previous Motion Capture System (MCS) for BSIPs identification of the human body wearing a full lowerlimbs exoskeleton robot. This study was published in the IEEE International Conference on Robotics and Automation (ICRA) 2018 [18]. Whereas, section 5.2 proposes an assessment framework of the kinematic and dynamic inaccuracies within a human-orthosis dynamic model for knee joint flexion/extension movements.…”

Section: Kinematics and Kinetics Assessment Of A Human Augmented Motionmentioning

confidence: 99%

Toward an Affordable Multi-Modal Motion Capture System Framework for Human Kinematics and Kinetics Assessment

Mallat

Bonnet

Khalil

et al. 2018

Biosystems &Amp; Biorobotics

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Quantifying human motor act starts with measuring and estimating kinematics and dynamics variables as accurately as possible. Monitoring human motion has a wide array of applications in functional rehabilitation, orthopaedics, sports, assistive robotics or industrial ergonomics. Today's motion capture systems usually refer to stereophotogrammetric systems and laboratory-grade force-plate that are accurate but also costly, require expert skills, and are not portable. Recently, the use of affordable sensors for human motion estimation, such as Inertial Measurement Unit or RGB-Depth camera(s), has been the subject of numerous studies. Despite their great potential to be used outside of the laboratory, these systems still suffer from limited accuracy, mainly due to inherent IMU drift and visual occlusions, and the joint kinematics and kinetics estimates are still difficult to be estimated. These drawbacks might explain why such systems are rarely used in common clinical applications or for in-home rehabilitation programs. In this context, this thesis deals with the development of a new affordable motion capture system capable of estimating accurately human 3D joint state. Unlike previous studies based on either visual or inertial sensors, the proposed approach consists in combining data from newly designed visual-inertial sensors. The system is also making use of new practical calibration methods, which do not require any external equipment while remaining very affordable. All sensors data are fused into a constrained extended Kalman filter that takes advantage of the biomechanics of the human body and of the investigated tasks to improve significantly joint state estimate. This is done by incorporating different types of constraints, such as joint limits, rigid-body and soft joint constraints, as well as modelling the temporal evolution of joint trajectories and/or sensors random bias. The system's ability to estimate accurate 3D joint kinematics has been validated through various case studies of daily life activities for upper-arm and treadmill gait. Two different prototypes with different sensors count and configurations have been investigated. Experiments conducted with several healthy subjects showed very satisfactory results when compared to a gold standard motion capture system. Overall, the average RMS difference between the two systems was below 4deg. This was also the case when a reduced number of sensors was used for gait analysis. This system was also used for the dynamics identification of a viii lower-limbs human-exoskeleton system. As a result, an error below 6% was observed when comparing estimated and measured external ground reaction force and moments. Finally, beyond these validations, a dynamics assessment framework has been proposed with the aim of selecting an optimal human-exoskeleton dynamic model that is the best trade-off between the accuracy of kinetic estimation, i.e., joint torque, and simplicity of modelling. To this end, the proposed framework consists in quantifying the independent con...

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Human-Exoskeleton System Dynamics Identification Using Affordable Sensors

Cited by 9 publications

References 22 publications

Impedance Modulation Control of a Lower-Limb Exoskeleton to Assist Sit-to-Stand Movements

Impedance Modulation Control of a Lower-Limb Exoskeleton to Assist Sit-to-Stand Movements

Trajectory-Free Control of Lower-Limb Exoskeletons Through Underactuated Total Energy Shaping

Toward an Affordable Multi-Modal Motion Capture System Framework for Human Kinematics and Kinetics Assessment

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