: Technological advancements have led to the development of numerous wearable robotic devices for the physical assistance and restoration of human locomotion. While many challenges remain with respect to the mechanical design of such devices, it is at least equally challenging and important to develop strategies to control them in concert with the intentions of the user.This work reviews the state-of-the-art techniques for controlling portable active lower limb prosthetic and orthotic (P/O) devices in the context of locomotive activities of daily living (ADL), and considers how these can be interfaced with the user's sensory-motor control system. This review underscores the practical challenges and opportunities associated with P/O control, which can be used to accelerate future developments in this field. Furthermore, this work provides a classification scheme for the comparison of the various control strategies.As a novel contribution, a general framework for the control of portable gait-assistance devices is proposed. This framework accounts for the physical and informatic interactions between the controller, the user, the environment, and the mechanical device itself. Such a treatment of P/Os--not as independent devices, but as actors within an ecosystem--is suggested to be necessary to structure the next generation of intelligent and multifunctional controllers.Each element of the proposed framework is discussed with respect to the role that it plays in the assistance of locomotion, along with how its states can be sensed as inputs to the controller. The reviewed controllers are shown to fit within different levels of a hierarchical scheme, which loosely resembles the structure and functionality of the nominal human central nervous system (CNS). Active and passive safety mechanisms are considered to be central aspects underlying all of P/O design and control, and are shown to be critical for regulatory approval of such devices for real-world use.The works discussed herein provide evidence that, while we are getting ever closer, significant challenges still exist for the development of controllers for portable powered P/O devices that can seamlessly integrate with the user's neuromusculoskeletal system and are practical for use in locomotive ADL.

This article discusses the pros and cons of compliant actuation for rehabilitation robots on the example of LOPES, focusing on the cons. After illustrating the bandwidth limitations, a new result has been derived: if stability in terms of passivity of the haptic device is desired, the renderable stiffness is bounded by the stiffness of the SEA's elastic component. In practical experiments with the VMC, the aforementioned limitations affected the control performance. Desired gait modifications were not tracked exactly, because the subjects were able to deviate from the prescribed pattern even in the stiffest possible configuration. Despite the limitations, the practical experiments also demonstrated the general effectiveness of the realization. Manipulation of selected gait parameters is possible, whereby other parameters are left unaffected. This high selectivity is made possible by the low level of undesired interaction torques, which is achieved by elastic decoupling of motor mass and a lightweight exoskeleton. The discrepancy between theoretical bounds and rendered stiffness indicated that healthy subjects might represent a stabilizing component of the coupled system, which could be different for patients. In light of the theoretical stability analysis and with the focus on patients, the LOPES actuation was slightly modified. The robot was equipped with stiffer springs to obtain sufficient stiffness and to ensure stability without relying on stabilizing effects of the human. For this application, the disadvantages of compliant actuation can thus be tolerated or dealt with, and they are small compared with the advantages. Given that a rehabilitation robot, in the first place, is supposed to imitate therapist action, the limitations of bandwidth and stiffness do not pose severe problems. In contrast, safety and backdrivability are highly relevant, and they can be ensured easier with a compliant actuator. Therefore, we conclude that compliant actuation and a lightweight exoskeleton provide effective means to accomplish the desired AAN behavior of a rehabilitation robot. The next step is to evaluate the robot behavior, control performance, and therapeutic effectiveness in patient studies.

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

Stroke is the most common cause of disability in the developed world and can severely degrade walking function. Robot-driven gait therapy can provide assistance to patients during training and offers a number of advantages over other forms of therapy. These potential benefits do not, however, seem to have been fully realised as of yet in clinical practice.

For gait rehabilitation robots, an important question is how to ensure stable gait, while avoiding any interaction forces between robot and human in case the patient walks correctly. To achieve this, the definition of ldquocorrectrdquo gait needs to adapted both to the individual patient and to the situation. Recently, we proposed a method for online trajectory generation that can be applied for hemiparetic subjects. Desired states for one (disabled) leg are generated online based on the movements of the other (sound) leg. An instantaneous mapping between legs is performed by exploiting physiological interjoint couplings. This way, the patient generates the reference motion for the affected leg autonomously. The approach, called Complementary Limb Motion Estimation (CLME), is implemented on the LOPES gait rehabilitation robot and evaluated with healthy subjects in two different experiments. In a previously described study, subjects walk only with one leg, while the robot's other leg acts as a fake prosthesis, to simulate complete loss of function in one leg. This study showed that CLME ensures stable gait. In a second study, to be presented in this paper, healthy subjects walk with both their own legs to assess the interference with self-determined walking. Evaluation criteria are: Power delivered to the joints by the robot, electromyography (EMG) distortions, and kinematic distortions, all compared to zero torque control, which is the baseline of minimum achievable interference. Results indicate that interference of the robot is lower with CLME than with a fixed reference trajectory, mainly in terms of lowered exchanged power and less alteration of EMG. This implies that subjects can walk more naturally with CLME, and they are assisted less by the robot when it is not needed. Future studies with patients are yet to show whether these properties of CLME transfer to the clinical domain.

Wheeled-legged robots have the potential for highly agile and versatile locomotion. The combination of legs and wheels might be a solution for any real-world application requiring rapid, and long-distance mobility skills on challenging terrain. In this paper, we present an online trajectory optimization framework for wheeled quadrupedal robots capable of executing hybrid walking-driving locomotion strategies. By breaking down the optimization problem into a wheel and base trajectory planning, locomotion planning for high dimensional wheeled-legged robots becomes more tractable, can be solved in real-time on-board in a model predictive control fashion, and becomes robust against unpredicted disturbances. The reference motions are tracked by a hierarchical whole-body controller that sends torque commands to the robot. Our approach is verified on a quadrupedal robot with non-steerable wheels attached to its legs. The robot performs hybrid locomotion with different gait sequences on flat and rough terrain. In addition, we validated the robotic platform at the Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge, where the robot rapidly maps, navigates, and explores dynamic underground environments.