Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS) consisting of an admittance filter, inner position controller, and electromyography (EMG)-driven musculoskeletal model (EDMM). The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS) at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA) and gastrocnemius (GAS). For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation

Geometric error model and measuring method based on worktable for five-axis machine tools

This article presents a new integrated geometric model that takes worktable as reference for five-axis machine tools. It could simplify the description of different machine kinetic structures and uniform the measurement coordinate system and machining coordinate system. Based on this model, a new method of measuring geometric errors with conventional instruments is proposed. It could break through some existing limitations, such as special instrument, specific machine kinetic structures, or errors incompletion. In addition, some deviation errors in measuring process could be eliminated to improve accuracy further. Finally, a series of experiments are conducted on a five-axis machine tool with rotary worktable and tilting head. The results show that the error model and measuring method are effective and applicable

Advances in extracellular vesicle-based combination therapies for spinal cord injury

Spinal cord injury is a severe insult to the central nervous system that causes persisting neurological deficits. The currently available treatments involve surgical, medical, and rehabilitative strategies. However, none of these techniques can markedly reverse neurological deficits. Recently, extracellular vesicles from various cell sources have been applied to different models of spinal cord injury, thereby generating new cell-free therapies for the treatment of spinal cord injury. However, the use of extracellular vesicles alone is still associated with some notable shortcomings, such as their uncertainty in targeting damaged spinal cord tissues and inability to provide structural support to damaged axons. Therefore, this paper reviews the latest combined strategies for the use of extracellular vesicle-based technology for spinal cord injury, including the combination of extracellular vesicles with nanoparticles, exogenous drugs and/or biological scaffold materials, which facilitate the targeting ability of extracellular vesicles and the combinatorial effects with extracellular vesicles. We also highlight issues relating to the clinical transformation of these extracellular vesicle-based combination strategies for the treatment of spinal cord injury

Integrated geometric error modeling, identification and compensation of CNC machine tools

This paper presents an integrated geometric error modeling, identification and compensation method for machine tools. Regarding a machine tool as a rigid multi-body system (MBS), a geometric error model has been established. It supports the identification of the 21 translational geometric error parameters associated with linear-motion axes based on a laser interferometer, and 6 angular geometric error parameters for each rotation axis based on a ball-bar. Based on this model, a new identification method is proposed to recognize these geometric errors. Finally, the identified geometric errors are compensated by correcting corresponding NC codes. In order to validate our method, a prototype software system has been developed, which can be used for conducting tests on any type of CNC machine tool with not more than five axes. An experiment has been conducted on a five-axis machine center with rotary table and tilting head; the results show that the integrated geometric error modeling, identification and compensation method is effective and applicable in multi-axis machine tools

Chronic atrioventricular nodal vagal stimulation: first evidence for long-term ventricular rate control in canine atrial fibrillation model

BACKGROUND: We have previously demonstrated that selective atrioventricular nodal (AVN) vagal stimulation (AVN-VS) can be used to control ventricular rate during atrial fibrillation (AF) in acute experiments. However, it is not known whether this approach could provide a long-term treatment in conscious animals. Thus, this study reports the first observations on the long-term efficacy and safety of this novel approach to control ventricular rate during AF in chronically instrumented dogs. METHODS AND RESULTS: In 18 dogs, custom-made bipolar patch electrodes were sutured to the epicardial AVN fat pad for delivery of selective AVN-VS by a subcutaneously implanted nerve stimulator (pulse width 100 micros or 1 ms, frequency 20 or 160 Hz, amplitude 6 to 10 V). Fast-rate right atrial pacing (600 bpm) was used to induce and maintain AF. ECG, blood pressure, and body temperature were monitored telemetrically. One week after the induction of AF, AVN-VS was delivered and maintained for at least 5 weeks. It was found that AVN-VS had a consistent effect on ventricular rate slowing (on average 45+/-13 bpm) over the entire period of observation. Echocardiography showed improvement of cardiac indices with ventricular rate slowing. AVN-VS was well tolerated by the animals, causing no signs of distress or discomfort. CONCLUSIONS: Beneficial long-term ventricular rate slowing during AF can be achieved by implantation of a nerve stimulator attached to the epicardial AVN fat pad. This novel concept is an attractive alternative to other methods of rate control and may be applicable in a selected group of patients