OPTIMAL PROSTHESES, ORTHOSES AND EXOSKELETONS FOR PHYSICAL ACTIVITY

Wearable physical assistive devices, such as prostheses, orthoses and exoskeletons are great inventions to enable a large range of subjects with very different disabilities, injuries or diseases to perform physical activity who would not be able to do so otherwise. The purpose of this paper is to present the benefits of model-based optimization methods to analyze and improve these devices such that they are best adapted to address the need of different pathologies or even individual subjects. Using detailed multibody system models of the human and the wearable devices, it is possible to tune parameters related to the kinematics, dynamics and control of the devices or even test completely new design ideas or setups. Optimization problems are formulated and solved in order to fit simulated motions of the combined system of human and wearable device to desired behaviour e.g. coming from motion recordings of healthy subjects or to generate motions that optimize particular performance criteria. The presented approach also allows to study the frequently asked question if certain prosthetic devices create and advantage of the wearer over able-bodies subjects

CENTER OF PRESSURE AND JOINT TORQUE ESTIMATION FOR SINGLE LEG SLACKLINE BALANCING USING MODEL-BASED OPTIMIZATION

Being similar to tightrope walking, slacklining has become very popular among athletes and physiotherapists to practice and improve balancing capabilities. For flat ground static balance the center of pressure is often used to quantify how stable a subject is. In this work we present a method to reconstruct the center of pressure and the joint torques from pure motion capture data for motions that don’t allow for force plate measurements. We demonstrate the application to a subject balancing on a slackline. We create a subject-specific 3D-model and perform a least-squares fit to the recorded reference motion by formulation and solution of an optimal control problem. From the resulting forces we can reconstruct the center of pressure dynamics and quantify how stable the subject is on a slackline. The joint torques allow for further insight into the balancing strategies applied

Estimating speaker direction on a humanoid robot with binaural acoustic signals

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to binaural sound source localization framework on a humanoid robotic head. Real data is collected and annotated for this work. Optimizations are performed via a brute force method and a Bayesian model based method, results are validated and discussed, and effects on latency for real-time use are also explored

Predicting the motions and forces of wearable robotic systems using optimal control

Wearable robotic systems are being developed to prevent injury to the low back. Designing a wearable robotic system is challenging because it is difficult to predict how the exoskeleton will affect the movement of the wearer. To aid the design of exoskeletons, we formulate and numerically solve an optimal control problem (OCP) to predict the movements and forces of a person as they lift a 15 kg box from the ground both without (human-only OCP) and with (with-exo OCP) the aid of an exoskeleton. We model the human body as a sagittal-plane multibody system that is actuated by agonist and antagonist pairs of muscle torque generators (MTGs) at each joint. Using the literature as a guide, we have derived a set of MTGs that capture the active torque–angle, passive torque–angle, and torque–velocity characteristics of the flexor and extensor groups surrounding the hip, knee, ankle, lumbar spine, shoulder, elbow, and wrist. Uniquely, these MTGs are continuous to the second derivative and so are compatible with gradient-based optimization. The exoskeleton is modeled as a rigid-body mechanism that is actuated by a motor at the hip and the lumbar spine and is coupled to the wearer through kinematic constraints. We evaluate our results by comparing our predictions with experimental recordings of a human subject. Our results indicate that the predicted peak lumbar-flexion angles and extension torques of the human-only OCP are within the range reported in the literature. The results of the with-exo OCP indicate that the exoskeleton motors should provide relatively little support during the descent to the box but apply a substantial amount of support during the ascent phase. The support provided by the lumbar motor is similar in shape to the net moment generated at the L5/S1 joint by the body; however, the support of the hip motor is more complex because it is coupled to the passive forces that are being generated by the hip extensors of the human subject. The simulations developed in this study are specific to lifting motion and a lower back exoskeleton. However, the framework is applicable for simulating a large range of robotic-assisted human motions

Motion optimization and parameter identification for a human and lower-back exoskeleton model

Designing an exoskeleton to reduce the risk of low-back injury during lifting is challenging. Computational models of the human-robot system coupled with predictive movement simulations can help to simplify this design process. Here, we present a study that models the interaction between a human model actuated by muscles and a lower-back exoskeleton. We provide a computational framework for identifying the spring parameters of the exoskeleton using an optimal control approach and forward-dynamics simulations. This is applied to generate dynamically consistent bending and lifting movements in the sagittal plane. Our computations are able to predict motions and forces of the human and exoskeleton that are within the torque limits of a subject. The identified exoskeleton could also yield a considerable reduction of the peak lower-back torques as well as the cumulative lower-back load during the movements. This work is relevant to the research communities working on human-robot interaction, and can be used as a basis for a better human-centered design process

Walking Paths to and from a Goal Differ: On the Role of Bearing Angle in the Formation of Human Locomotion Paths

The path that humans take while walking to a goal is the result of a cognitive process modulated by the perception of the environment and physiological constraints. The path shape and timing implicitly embeds aspects of the architecture behind this process. Here, locomotion paths were investigated during a simple task of walking to and from a goal, by looking at the evolution of the position of the human on a horizontal (x,y) plane. We found that the path while walking to a goal was not the same as that while returning from it. Forward-return paths were systematically separated by 0.5-1.9m, or about 5% of the goal distance. We show that this path separation occurs as a consequence of anticipating the desired body orientation at the goal while keeping the target in view. The magnitude of this separation was strongly influenced by the bearing angle (difference between body orientation and angle to goal) and the final orientation imposed at the goal. This phenomenon highlights the impact of a trade-off between a directional perceptual apparatus-eyes in the head on the shoulders-and and physiological limitations, in the formation of human locomotion paths. Our results give an insight into the influence of environmental and perceptual variables on human locomotion and provide a basis for further mathematical study of these mechanisms

Robust foot clearance estimation based on the integration of foot-mounted IMU acceleration data

This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject's foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking conditions: normal, fast and with obstacles. Foot clearance estimation results were compared to measurements from an optical motion capture system. The mean error between them is significantly less than 15 % under the various walking conditions

MODELING AND OPTIMAL CONTROL OF ABLE-BODIED AND UNILATERAL AMPUTEE RUNNING

The remarkable performances of amputee athletes in sprint competitions aroused media and scientific interest and led to the question whether running-specific prostheses can be an advantage with respect to able-bodied running. The aim of this study was to bring together motion capture data and Scientific Computing methods to analyze the running motions of an able-bodied and a unilateral transtibial amputee athlete. For each of them a rigid multibody system model was created. By application of optimal control techniques, the dynamics of reference running movements from motion capture data was reconstructed for both models. The able-bodied and the transtibial amputee sprinters rely on dissimilar actuation strategies to perform similar running motions

Predicting the influence of hip and lumbar flexibility on lifting motions using optimal control

Computational models of the human body coupled with optimization can be used to predict the influence of variables that cannot be experimentally manipulated. Here, we present a study that predicts the motion of the human body while lifting a box, as a function of flexibility of the hip and lumbar joints in the sagittal plane. We modeled the human body in the sagittal plane with joints actuated by pairs of agonist-antagonist muscle torque generators, and a passive hamstring muscle. The characteristics of a stiff, average and flexible person were represented by co-varying the lumbar range-of-motion, lumbar passive extensor-torque and the hamstring passive muscle-force. We used optimal control to solve for motions that simulated lifting a 10 kg box from a 0.3 m height. The solution minimized the total sum of the normalized squared active and passive muscle torques and the normalized passive hamstring muscle forces, over the duration of the motion. The predicted motion of the average lifter agreed well with experimental data in the literature. The change in model flexibility affected the predicted joint angles, with the stiffer models flexing more at the hip and knee, and less at the lumbar joint, to complete the lift. Stiffer models produced similar passive lumbar torque and higher hamstring muscle force components than the more flexible models. The variation between the motion characteristics of the models suggest that flexibility may play an important role in determining lifting technique