Walking rehabilitation using exoskeletons is of high importance to maximize independence and improve the general well-being of spinal cord injured subjects. We present the design and control of a lightweight and modular robotic exoskeleton to assist walking in spinal cord injured subjects who can control hip flexion, but lack control of knee and ankle muscles. The developed prototype consists of two robotic orthoses, which are powered by a motor-harmonic drive actuation system that controls knee flexion–extension. This actuation module is assembled on standard passive orthoses. Regarding the control, the stance-to-swing transition is detected using two inertial measurement units mounted on the tibial supports, and then the corresponding motor performs a predefined flexion–extension cycle that is personalized to the specific patient’s motor function. The system is portable by means of a backpack that contains an embedded computer board, the motor drivers, and the battery. A preliminary biomechanical evaluation of the gait-assistive device used by a female patient with incomplete spinal cord injury at T11 is presented. Results show an increase of gait speed (+24.11%), stride length (+7.41%), and cadence (+15.56%) when wearing the robotic orthoses compared with the case with passive orthoses. Conversely, a decrease of lateral displacement of the center of mass (−19.31%) and step width (−13.37% right step, −8.81% left step) are also observed, indicating gain of balance. The biomechanical assessment also reports an overall increase of gait symmetry when wearing the developed assistive device.

Optical motion capture is an essential tool for the study and analysis of human movement. Currently, most manufacturers of motion-capture systems provide software applications for reconstructing the movement in real time, thus allowing for on-the-fly visualization. The captured kinematics can be later used as input data for a further musculoskeletal analysis. However, in advanced biofeedback applications, the results of said analysis, such as joint torques, ground-reaction forces, muscle efforts, and joint-reaction forces, are also required in real time.In this work, an extended Kalman filter (EKF) previously developed by the authors for real-time, whole-body motion capture and reconstruction is augmented with inverse dynamics and muscle-efforts optimization, enabling the calculation and visualization of the latter, along with joint-reaction forces, while capturing the motion.A modified version of the existing motion-capture algorithm provides the positions, velocities, and accelerations at every time step. Then, the joint torques are calculated by solving the inverse-dynamics problem, using force-plate measurements along with previously estimated body-segment parameters. Once the joint torques are obtained, an optimization problem is solved, in order to obtain the muscle forces that provide said torques while minimizing an objective function. This is achieved by a very efficient quadratic programming algorithm, thoroughly tuned for this specific problem.With this procedure, it is possible to capture and label the optical markers, reconstruct the motion of the model, solve the inverse dynamics, and estimate the individual muscle forces, all while providing real-time visualization of the results.

A formulation developed at the Laboratory of Mechanical Engineering allows robust and efficient simulation of large and complex multibody systems. Simulators of cars, excavators and other systems have been developed showing that real-time simulations are possible even when facing demanding manoeuvres. Hydraulic actuators are present in many industrial applications of multibody systems, like in the case of the heavy machinery field. When simulating the dynamics of this kind of problems that combine multibody dynamics and hydraulics, two different approaches are common: to resort to kinematically guide the variable length of the actuator, thus avoiding the need to consider the dynamics of the hydraulic system; or to perform a multi-rate integration of both subsystems if a more detailed description of the problem is required, for example, when the objective of the study is to optimize the pump control. This work addresses the inclusion of hydraulic actuators dynamics in the abovementioned self-developed multibody formulation, thus leading to a unified approach. An academic example serves to compare the efficiency, accuracy and ease of implementation of the simplified (kinematic guidance), multi-rate and unified approaches. Such a comparison is the main contribution of the paper, as it may serve to provide guidelines on which approach to select depending on the problem characteristics.

Optical motion capture is currently the most popular method for acquiring motion data in biomechanical applications. However, it presents a number of problems that make the process difficult and inefficient, such as marker occlusions and unwanted reflections. In addition, the obtained trajectories must be numerically differentiated twice in time in order to get the accelerations. Since the trajectories are normally noisy, they need to be filtered first, and the selection of the optimal amount of filtering is not trivial. In this work, an extended Kalman filter (EKF) that manages marker occlusions and undesired reflections in a robust way is presented. A preliminary test with inertial measurement units (IMUs) is carried out to determine their local reference frames. Then, the gait analysis of a healthy subject is performed using optical markers and IMUs simultaneously. The filtering parameters used in the optical motion capture process are tuned in order to achieve good correlation between the obtained accelerations and those measured by the IMUs. The results show that the EKF provides a robust and efficient method for optical system-based motion analysis, and that the availability of accelerations measured by inertial sensors can be very helpful for the adjustment of the filters.