Search Results (5)

To enhance robotic adaptability in dynamic environments, this study proposes a multimodal framework for skill transfer. The framework integrates vision-based kinesthetic teaching with surface electromyography (sEMG) signals to estimate human impedance. We establish a Cartesian-space model of upper-limb stiffness, linearly mapping sEMG signals to end-point stiffness. For flexible task execution, dynamic movement primitives (DMPs) generalize learned skills across varying scenarios. An adaptive admittance controller, incorporating sEMG-modulated stiffness, is developed and validated on a UR5 robot. Experiments involving elastic-band stretching demonstrate that the system successfully transfers human impedance characteristics to the robot, enhancing stability, environmental adaptability, and safety during physical interaction. Full article

Background: Arterial stiffness is a crucial factor in the pathogenesis of cardiovascular disease, often associated with aging. However, the impact of smoking on arterial stiffness is frequently underestimated. This study aims to investigate the intricate relationship between smoking and arterial stiffness to advance our understanding of and therapeutic approaches to cardiovascular health. Methods: A prospective analysis was conducted from January to July 2024, focusing on arterial stiffness parameters in a cohort of students from the Carol Davila University of Medicine and Pharmacy. Participants were categorized as smokers or non-smokers based on self-reported smoking status. The study endpoints included correlations between high pulse wave velocity, elevated peripheral and central systolic blood pressure, increased peripheral and central pulse pressure, and smoking status. These markers were assessed using an arteriograph device measuring the time difference between the initial forward pulse wave and the reflected pulse wave in the brachial artery to indirectly estimate the PWV using oscillometric pulsations. Results: Our investigation, involving 102 young individuals aged 20 to 26 (69 females, 33 males), revealed that smokers exhibited significantly higher average values of arterial stiffness indicators compared to non-smokers. Current smokers had higher mean systolic blood pressure (130.65 vs. 123.05 mmHg), higher mean peripheral pulse pressure (53.19 vs. 45.64 mmHg), higher mean central pulse pressure (33.66 vs. 29.69 mmHg), and higher mean pulse wave velocity (5.27 vs. 5.03 m/s). Conclusions: The utilization of arterial stiffness markers as predictive tools offers opportunities for personalized treatment strategies, potentially enhancing cardiovascular health outcomes. Full article

The implementation of a progressive rehabilitation training model to promote patients’ motivation efforts can greatly restore damaged central nervous system function in patients. Patients’ active engagement can be effectively stimulated by assist-as-needed (AAN) robot rehabilitation training. However, its application in robotic therapy has been hindered by a simple determination method of robot-assisted torque which focuses on the evaluation of only the affected limb’s movement ability. Moreover, the expected effect of assistance depends on the designer and deviates from the patient’s expectations, and its applicability to different patients is deficient. In this study, we propose a control method with personalized treatment features based on the idea of estimating and mapping the stiffness of the patient’s healthy limb. This control method comprises an interactive control module in the task-oriented space based on the quantitative evaluation of motion needs and an inner-loop position control module for the pneumatic swing cylinder in the joint space. An upper-limb endpoint stiffness estimation model was constructed, and a parameter identification algorithm was designed. The upper limb endpoint stiffness which characterizes the patient’s ability to complete training movements was obtained by collecting surface electromyographic (sEMG) signals and human–robot interaction forces during patient movement. Then, the motor needs of the affected limb when completing the same movement were quantified based on the performance of the healthy limb. A stiffness-mapping algorithm was designed to dynamically adjust the rehabilitation training trajectory and auxiliary force of the robot based on the actual movement ability of the affected limb, achieving AAN control. Experimental studies were conducted on a self-developed pneumatic upper limb rehabilitation robot, and the results showed that the proposed AAN control method could effectively estimate the patient’s movement needs and achieve progressive rehabilitation training. This rehabilitation training robot that simulates the movement characteristics of the patient’s healthy limb drives the affected limb, making the intensity of the rehabilitation training task more in line with the patient’s pre-morbid limb-use habits and also beneficial for the consistency of bilateral limb movements. Full article

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations. Full article

A framework to model and analyze the coupled nonlinear aeroelasticity and flight dynamics of highly flexible aircrafts is presented. The methodology is based on the dynamics of 3D co-rotational beams. The coupling of axial, bending and torsional effects is added to the stiffness and mass matrices of Euler–Bernoulli beam to capture the most relevant characteristics of a real wing structure. The finite-state aerodynamic model is coupled with the structural model to simulate the unsteady aerodynamics. A scheme of mixed end-point and mid-point time-marching algorithms is proposed and applied into the implicit predictor–corrector integration, where the end-point algorithm is used in the predictor step for efficiency and mid-point algorithm in corrector step for accuracy. The ground, body and airflow axes for flight dynamics are re-defined by the global and elemental ones for structural dynamics, followed by the redefinitions of local Euler angles and airflow angles of each element. The framework can be used for quick analyses of flexible aircrafts in conceptual and preliminary design phases, including linear and nonlinear trim, aerodynamic load estimation, stability assessment, time-domain simulations and flight performance evaluations. The results show the payload mass and its distributions will significantly affect the trim state and longitudinal stability of highly flexible aircrafts. Full article