Abstract
In exoskeletal robots, the quantification of the user’s muscular effort is important to recognize the user’s motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users’ muscular efforts accurately using joint torque sensor which contains the measurements of dynamic effect of human body such as the inertial, Coriolis, and gravitational torques as well as torque by active muscular effort. It is important to extract the dynamic effects of the user’s limb accurately from the measured torque. The user’s limb dynamics are formulated and a convenient method of identifying user-specific parameters is suggested for estimating the user’s muscular torque in robotic exoskeletons. Experiments were carried out on a wheelchair-integrated lower limb exoskeleton, EXOwheel, which was equipped with torque sensors in the hip and knee joints. The proposed methods were evaluated by 10 healthy participants during body weight-supported gait training. The experimental results show that the torque sensors are to estimate the muscular torque accurately in cases of relaxed and activated muscle conditions.
Highlights
In recent years, there has been increasing interest in using robotic devices to assist in the rehabilitative training of people with motion impairments
There are two widely used methods for quantifying the user’s muscular effort in a rehabilitation robot: by measuring electromyography (EMG) using surface electrodes attached to the user’s skin; and by estimating muscular torque based on inverse-dynamics analysis
This study presents a method for estimating users’ active muscular torque measured by sensor systems typically used in exoskeletal rehabilitation robots
Summary
There has been increasing interest in using robotic devices to assist in the rehabilitative training of people with motion impairments. There are two widely used methods for quantifying the user’s muscular effort in a rehabilitation robot: by measuring electromyography (EMG) using surface electrodes attached to the user’s skin; and by estimating muscular torque based on inverse-dynamics analysis. The muscular torque of the human user can be estimated by measuring the applied external torque at each joint of the exoskeletal robot, and by removing the inertial, Coriolis, and gravitational torques of the user’s limb (referred to as “passive torque” throughout the paper to distinguish it from the torque generated by muscle). We focus on the identification of user-specific inertial parameters rather than using typical anthropometric models This approach is important because the isolation of active muscular effort from joint torque measurements critically relies on the accuracy of the dynamic model of the user’s limb. The performance of the proposed method was verified by experiments on body-weight-supported gait training
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