Effects of overground gait training assisted by a wearable exoskeleton in patients with Parkinson's disease.

BACKGROUND: In the recent past, wearable devices have been used for gait rehabilitation in patients with Parkinson's disease. The objective of this paper is to analyze the outcome of a wearable hip orthosis whose assistance adapts in real time to the patient's gait kinematics via adaptive oscillators. In particular, this study focuses on a metric characterizing natural gait variability, i.e., the level of long-range autocorrelations (LRA) in series of stride durations. METHODS: Eight patients with Parkinson's disease (Hoehn and Yahr stages 1[Formula: see text]2.5) performed overground gait training three times per week for four consecutive weeks, assisted by a wearable hip orthosis. Gait was assessed based on performance metrics such as the hip range of motion, speed, stride length and duration, and the level of LRA in inter-stride time series assessed using the Adaptive Fractal Analysis. These metrics were measured before, directly after, and 1 month after training. RESULTS: After training, patients increased their hip range of motion, their gait speed and stride length, and decreased their stride duration. These improvements were maintained 1 month after training. Regarding long-range autocorrelations, the population's behavior was standardized towards a metric closer to the one of healthy individuals after training, but with no retention after 1 month. CONCLUSION: This study showed that an overground gait training with adaptive robotic assistance has the potential to improve key gait metrics that are typically affected by Parkinson's disease and that lead to higher prevalence of fall. TRIAL REGISTRATION: ClinicalTrials.gov Identifer NCT04314973. Registered on 11 April 2020.

On the Usability of Polymer-Based Artificial Tendons for Elastic Energy Storage in Active Ankle Prostheses.

In the recent past, the development of lower-limb prostheses has taken a new turn with the emergence of active systems. However, their intrinsic wearable nature induces strict requirements regarding weight and encumbrance. In order to reduce the load - and thus the bulkiness - of their active part, several prototypes leverage the concept of compliant actuation, consisting in including an elastic element in parallel and/or in series with the actuator. In this paper, we explore the usability of polymer compliant ropes placed in parallel with the actuator of an ankle prosthesis. Ropes are intrinsically light and compact, and thus offer several advantages as compared to more traditional coil or leaf springs. Polymer materials were selected for their high energy density and yield strength. We conducted a set of experimental tests with several ropes, pretension levels, and periodic loading profiles. Results show that polymer-based ropes have a high potential for ankle assistance devices, since they can store the required energy in a low volume. However, further research should be conducted to improve their efficiency, since we estimated that only about 50% of the stored energy can be released, with few variations as a function of the rope preconditioning and loading profile.

Adaptive walking assistance does not impact long-range stride-to-stride autocorrelations in healthy people.

Many studies have demonstrated in the past that the level of long-range autocorrelations in series of stride durations, characterizing natural gait variability, is impacted by external constraints, such as treadmill or metronome, or by pathologies, such as Parkinson's or Huntington's disease. Nevertheless, no one has analyzed the effects on this metric of a gait constrained by a robot-mediated walking assistance, which intrinsically tends to normalize the gait pattern. This paper focuses on the influence of a wearable active pelvis orthosis on the level of long-range autocorrelations in series of stride durations. Ten healthy participants, aged between 55 and 77 yr, performed four overground walking sessions, wearing this orthosis, and with different assistive parameters. This study showed that the adaptive assistance provided by this device has the potential of improving gait metrics that are typically affected by aging, such as the hip range of motion, walking speed, stride length, and stride duration, without impacting natural gait variability, i.e., the level of long-range autocorrelations in series of stride durations. This combination is virtuous toward the design of an assistive device for people with locomotion disorders resulting in deteriorated levels of long-range autocorrelations, such as patients with Parkinson's disease.NEW & NOTEWORTHY This study is the first that investigates the effects of a wearable active pelvis orthosis using an oscillator-based adaptive assistance on the level of long-range autocorrelations in series of stride durations during overground walking. It is also the first to compare the effects of different assistance settings on spatiotemporal gait metrics.

Numerical assessment of wake-based estimation of instantaneous lift in flapping flight of large birds.

Experimental characterization of bird flight without instrumenting the animal requires measuring the flow behind the bird in a wind tunnel. Models are used to link the measured velocities to the corresponding aerodynamic forces. Widely-used models can, however, prove inconsistent when evaluating the instantaneous lift. Yet, accurately estimating variations of lift is critical in order to reverse-engineer flapping flight. In this work, we revisit mathematical models of lift based on the conservation of momentum in a control volume around a bird. Using a numerical framework to represent a flapping bird wing and compute the flow around it, we mimic the conditions of a wind tunnel and produce realistic wakes, which we compare to experimental data. Providing ground truth measurements of the flow everywhere around the simulated bird, we assess the validity of several lift estimation techniques. We observe that the circulation-based component of the instantaneous lift can be retrieved from measurements of velocity in a single plane behind a bird, with a latency that is found to depend directly on the free-stream velocity. We further show that the lift contribution of the added-mass effect cannot be retrieved from such measurements and quantify the level of approximation due to ignoring this contribution in instantaneous lift estimation.

Model of gait control in Parkinson's disease and prediction of robotic assistance.

Gait variability of healthy adults exhibits Long-Range Autocorrelations (LRA), meaning that the stride interval at any time statistically depends on previous gait cycles; and this dependency spans over several hundreds of strides. Previous works have shown that this property is altered in patients with Parkinson's disease, such that their gait pattern corresponds to a more random process. Here, we adapted a model of gait control to interpret the reduction in LRA that characterized patients in a computational framework. Gait regulation was modeled as a Linear-Quadratic-Gaussian control problem where the objective was to maintain a fixed velocity through the coordinated regulation of stride duration and length. This objective offers a degree of redundancy in the way the controller can maintain a given velocity, resulting in the emergence of LRA. In this framework, the model suggested that patients exploited less the task redundancy, likely to compensate for an increased stride-to-stride variability. Furthermore, we used this model to predict the potential benefit of an active orthosis on the gait pattern of patients. The orthosis was embedded in the model as a low-pass filter on the series of stride parameters. We show in simulations that, with a suitable level of assistance, the orthosis could help patients recovering a gait pattern with LRA comparable to that of healthy controls. Assuming that the presence of LRA in a stride series is a marker of healthy gait control, our study provides a rationale for developing gait assistance technology to reduce the fall risk associated with Parkinson's disease.

On the role of tail in stability and energetic cost of bird flapping flight.

Migratory birds travel over impressively long distances. Consequently, they have to adopt flight regimes being both efficient-in order to spare their metabolic resources-and robust to perturbations. This paper investigates the relationship between both aspects, i.e., energetic performance and stability, in flapping flight of migratory birds. Relying on a poly-articulated wing morphing model and a tail-like surface, several families of steady flight regime have been identified and analysed. These families differ by their wing kinematics and tail opening. A systematic parametric search analysis has been carried out, in order to evaluate power consumption and cost of transport. A framework tailored for assessing limit cycles, namely Floquet theory, is used to numerically study flight stability. Our results show that under certain conditions, an inherent passive stability of steady and level flight can be achieved. In particular, we find that progressively opening the tail leads to passively stable flight regimes. Within these passively stable regimes, the tail can produce either upward or downward lift. However, these configurations entail an increase of cost of transport at high velocities penalizing fast forward flight regimes. Our model-based predictions suggest that long range flights require a furled tail configuration, as confirmed by field observations, and consequently need to rely on alternative mechanisms to stabilize the flight.

Model coupling biomechanics and fluid dynamics for the simulation of controlled flapping flight.

This paper proposes a multiphysics computational framework coupling biomechanics and aerodynamics for the simulation of bird flight. It features a biomechanical model based on the anatomy of a bird, which models the bones and feathers of the wing. The aerodynamic solver relies on a vortex particle-mesh method and represents the wing through an immersed lifting line, acting as a source of vorticity in the flow. An application of the numerical tool is presented in the modeling of the flight of a northern bald ibis (Geronticus eremita). The wing kinematics are imposed based on biological observations and controllers are developed to enable stable flight in a closed loop. Their design is based on a linearized model of flapping flight dynamics. The controller solves an underdetermination in the control parameters through minimization. The tool and the controllers are used in two simulations: one where the bird has to trim itself at a given flight speed, and another where it has to accelerate from a trimmed state to another at a higher speed. The bird wake is accurately represented. It is analyzed and compared to the widespread frozen-wake assumption, highlighting phenomena that the latter cannot capture. The method also allows the computation of the aerodynamic forces experienced by the flier, either through the lifting line method or through control-volume analysis. The computed power requirements at several flight speeds exhibit an order of magnitude and dependency on velocity in agreement with the literature.

Bio-inspired design and validation of the Efficient Lockable Spring Ankle (ELSA) prosthesis.

Over the last decade, active lower-limb prostheses demonstrated their ability to restore a physiological gait for transfemoral amputees by supplying the required positive energy balance during daily life locomotion activities. However, the added-value of such devices is significantly impacted by their limited energetic autonomy, excessive weight and cost, thus preventing their full appropriation by the users. There is thus a strong incentive to produce active yet affordable, lightweight and energy efficient devices. To address these issues, we developed the ELSA (Efficient Lockable Spring Ankle) prosthesis embedding both a lockable parallel spring and a series elastic actuator, tailored to the walking dynamics of a sound ankle. The first contribution of this paper concerns the developement of a bio-inspired, lightweight and stiffness-adjustable parallel spring, comprising an energy efficient ratchet and pawl mechanism with servo actuation. The second contribution is the addition of a complementary rope-driven series elastic actuator to generate the active push-off. The system produces a sound ankle torque pattern during flat ground walking. Up to 50% of the peak torque is generated passively at a negligible energetic cost (0.1 J/stride). By design, the total system is lightweight (1.2kg) and low cost.

Rhythmic robotic training enhances motor skills of both rhythmic and discrete upper-limb movements after stroke: a longitudinal pilot study.

Discrete and rhythmic movements are two fundamental motor primitives being, at least partially, controlled by separate neural circuitries. After a stroke, both primitives may be impaired in the upper limb. Currently, intensive functional movement therapy is recommended after stroke, but it is mainly composed of discrete movements. No recommendation is made for the specific training of rhythmic movements. However, if they form two different primitives, both should receive a specific training to recover the complete motor repertoire, as many daily live movements integrate both of them. This paper reports the effects of a pure unilateral rhythmic movement therapy on motor performance, after stroke. Thirteen patients with chronic stroke participated in this longitudinal pilot study. They were assessed twice before the therapy to validate their chronic state, and twice after the last session to establish the short-term and long-term effects of the therapy. The therapy itself was composed of 12 sessions spread over 1 month. The exercises consisted in performing straight or circular rhythmic movements, while receiving assistance as need through a robotic device. Short-term and long-term improvements were observed in rhythmic movements regarding smoothness, velocity, and harmonicity. More surprisingly, some transfer occurred to the untrained discrete movements. This finding disputes previous studies that reported no transfer from rhythmic to discrete movements with healthy participants.

Modeling and control of a transfemoral prosthesis embedding two infinitely variable transmissions.

In this paper, we report the model of an original actuation concept for a transfemoral prosthesis, relying on the combination of a single power motor, a compliant element (a spring), a mechanical differential, and two infinitely variable transmissions. It allows to manage the mechanical power flows through the device in both directions (i.e. when energy should be produced or dissipated by the knee and ankle), so that the power motor does not face the sharp load power fluctuations. The paper further reports a preliminary approach to synthesize a closed-loop controller for this device, and simulation results of this closed-loop behavior for three locomotion tasks: level-ground walking and stair ascent/descent. These results illustrate the capacity of this actuation principle to filter the load power profile, and further highlight the necessity to maximize the mechanical efficiency of each part of this actuation scheme.

Design of an energy efficient transfemoral prosthesis using lockable parallel springs and electrical energy transfer.

Over the last decade, active lower-limb prostheses demonstrated their ability to restore a normal gait for transfemoral amputees by supplying the required positive energy balance [1]. However, the added-value of such devices is significantly impacted by their limited energetic autonomy preventing their full appropriation by the patients. There is thus a strong incentive to reduce the overall power consumption of active prostheses. Addressing this need requires to revisit the electromechanical design. For both the ankle and the knee, the present paper demonstrates that both the use of a lockable parallel spring and the transfer of electrical energy between joints can significantly improve the energetic performance for overground walking. A simulation model of such a prosthesis was implemented in order to quantify the energy gain being achievable when augmenting a classical series elastic actuator (SEA) with different parallel spring topologies. Simulations predict that adding a lockable parallel spring (LPS) to the SEA reduces the ankle motor consumption by 24% and allows the knee (naturally dissipative) to produce 38% more electrical energy. Moreover, the total energy consumption of the device is reduced to 22J/stride when the harvested electrical energy from the knee is stored and transfered to the ankle.

Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks.

An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificial primitives results in a set of virtual muscle stimulations. These stimulations then activate a virtual musculoskeletal model producing reference assistive torque profiles for different locomotion tasks (i.e., walking, ascending stairs, and descending stairs). The paper reports the validation of the controller through a set of experiments conducted with healthy participants. The proposed controller was tested for the first time with a unilateral leg exoskeleton assisting hip, knee, and ankle joints by delivering a fraction of the computed reference torques. Importantly, subjects performed a track involving ground-level walking, ascending stairs, and descending stairs and several transitions between these tasks. These experiments highlighted the capability of the controller to provide relevant assistive torques and to effectively handle transitions between the tasks. Subjects displayed a natural interaction with the device. Moreover, they significantly decreased the time needed to complete the track when the assistance was provided, as compared to wearing the device with no assistance.

Performance-based robotic assistance during rhythmic arm exercises.

BACKGROUND: Rhythmic and discrete upper-limb movements are two fundamental motor primitives controlled by different neural pathways, at least partially. After stroke, both primitives can be impaired. Both conventional and robot-assisted therapies mainly train discrete functional movements like reaching and grasping. However, if the movements form two distinct neural and functional primitives, both should be trained to recover the complete motor repertoire. Recent studies show that rhythmic movements tend to be less impaired than discrete ones, so combining both movement types in therapy could support the execution of movements with a higher degree of impairment by movements that are performed more stably. METHODS: A new performance-based assistance method was developed to train rhythmic movements with a rehabilitation robot. The algorithm uses the assist-as-needed paradigm by independently assessing and assisting movement features of smoothness, velocity, and amplitude. The method relies on different building blocks: (i) an adaptive oscillator captures the main movement harmonic in state variables, (ii) custom metrics measure the movement performance regarding the three features, and (iii) adaptive forces assist the patient. The patient is encouraged to improve performance regarding these three features with assistance forces computed in parallel to each other. The method was tested with simulated jerky signals and a pilot experiment with two stroke patients, who were instructed to make circular movements with an end-effector robot with assistance during half of the trials. RESULTS: Simulation data reveal sensitivity of the metrics for assessing the features while limiting interference between them. The assistance's effectiveness with stroke patients is established since it (i) adapts to the patient's real-time performance, (ii) improves patient motor performance, and (iii) does not lead the patient to slack. The smoothness assistance was by far the most used by both patients, while it provided no active mechanical work to the patient on average. CONCLUSION: Our performance-based assistance method for training rhythmic movements is a viable candidate to complement robot-assisted upper-limb therapies for training a larger motor repertoire.

Rhythmic arm movements are less affected than discrete ones after a stroke.

Recent reports indicate that rhythmic and discrete upper-limb movements are two different motor primitives which recruit, at least partially, distinct neural circuitries. In particular, rhythmic movements recruit a smaller cortical network than discrete movements. The goal of this paper is to compare the levels of disability in performing rhythmic and discrete movements after a stroke. More precisely, we tested the hypothesis that rhythmic movements should be less affected than discrete ones, because they recruit neural circuitries that are less likely to be damaged by the stroke. Eleven stroke patients and eleven age-matched control subjects performed discrete and rhythmic movements using an end-effector robot (REAplan). The rhythmic movement condition was performed with and without visual targets to further decrease cortical recruitment. Movement kinematics was analyzed through specific metrics, capturing the degree of smoothness and harmonicity. We reported three main observations: (1) the movement smoothness of the paretic arm was more severely degraded for discrete movements than rhythmic movements; (2) most of the patients performed rhythmic movements with a lower harmonicity than controls; and (3) visually guided rhythmic movements were more altered than non-visually guided rhythmic movements. These results suggest a hierarchy in the levels of impairment: Discrete movements are more affected than rhythmic ones, which are more affected if they are visually guided. These results are a new illustration that discrete and rhythmic movements are two fundamental primitives in upper-limb movements. Moreover, this hierarchy of impairment opens new post-stroke rehabilitation perspectives.

Adaptive position anticipation in a support robot for overground gait training enhances transparency.

Rehabilitation robots being developed nowadays rely on force and/or impedance control. This is guided by clinical evidence showing better performance if the patient is left with the capacity to influence the robot trajectory. The simplest, yet fundamental, mode of force control is when the robot has to be transparent, i.e. to apply no forces/torques on the patient. This mode is useful both in scenarios where the robot has to apply pinpointed support during some training phases and be transparent otherwise, and for any force controller in general, to avoid the reference forces to be polluted by the robot own dynamics. This contribution proposes a method to improve transparency on a support robot for overground training. The method consists in learning the patient's movement by using adaptive oscillators and then anticipate its future evolution in order to synchronize the robot movement. In experiments with human subjects walking in the gait support robot FLOAT, this method can decrease the undesired oscillations of the support force applied to the human user by up to 50%.

Oscillator-based assistance of cyclical movements: model-based and model-free approaches.

In this article, we propose a new method for providing assistance during cyclical movements. This method is trajectory-free, in the sense that it provides user assistance irrespective of the performed movement, and requires no other sensing than the assisting robot's own encoders. The approach is based on adaptive oscillators, i.e., mathematical tools that are capable of learning the high level features (frequency, envelope, etc.) of a periodic input signal. Here we present two experiments that we recently conducted to validate our approach: a simple sinusoidal movement of the elbow, that we designed as a proof-of-concept, and a walking experiment. In both cases, we collected evidence illustrating that our approach indeed assisted healthy subjects during movement execution. Owing to the intrinsic periodicity of daily life movements involving the lower-limbs, we postulate that our approach holds promise for the design of innovative rehabilitation and assistance protocols for the lower-limb, requiring little to no user-specific calibration.

Motor learning with augmented feedback: modality-dependent behavioral and neural consequences.

Sensory information is critical to correct performance errors online during the execution of complex tasks and can be complemented by augmented feedback (FB). Here, 2 groups of participants acquired a new bimanual coordination pattern under different augmented FB conditions: 1) visual input reflecting coordination between the 2 hands and 2) auditory pacing integrating the timing of both hands into a single temporal structure. Behavioral findings revealed that the visual group became dependent on this augmented FB for performance, whereas the auditory group performed equally well with or without augmented FB by the end of practice. Functional magnetic resonance imaging (fMRI) results corroborated these behavioral findings: the visual group showed neural activity increases in sensory-specific areas during practice, supporting increased reliance on augmented FB. Conversely, the auditory group showed a neural activity decrease, specifically in areas associated with cognitive/sensory monitoring of motor task performance, supporting the development of a control mode that was less reliant on augmented FB sources. Finally, some remnants of brain activity in sensory-specific areas in the absence of augmented FB were found for the visual group only, illustrating ongoing reliance on these areas. These findings provide the first neural account for the "guidance hypothesis of information FB," extensively supported by behavioral research.

Human-robot synchrony: flexible assistance using adaptive oscillators.

We propose a novel method for movement assistance that is based on adaptive oscillators, i.e., mathematical tools that are capable of extracting the high-level features (amplitude, frequency, and offset) of a periodic signal. Such an oscillator acts like a filter on these features, but keeps its output in phase with respect to the input signal. Using a simple inverse model, we predicted the torque produced by human participants during rhythmic flexion-extension of the elbow. Feeding back a fraction of this estimated torque to the participant through an elbow exoskeleton, we were able to prove the assistance efficiency through a marked decrease of the biceps and triceps electromyography. Importantly, since the oscillator adapted to the movement imposed by the user, the method flexibly allowed us to change the movement pattern and was still efficient during the nonstationary epochs. This method holds promise for the development of new robot-assisted rehabilitation protocols because it does not require prespecifying a reference trajectory and does not require complex signal sensing or single-user calibration: the only signal that is measured is the position of the augmented joint. In this paper, we further demonstrate that this assistance was very intuitive for the participants who adapted almost instantaneously.

Sensing pressure distribution on a lower-limb exoskeleton physical human-machine interface.

A sensory apparatus to monitor pressure distribution on the physical human-robot interface of lower-limb exoskeletons is presented. We propose a distributed measure of the interaction pressure over the whole contact area between the user and the machine as an alternative measurement method of human-robot interaction. To obtain this measure, an array of newly-developed soft silicone pressure sensors is inserted between the limb and the mechanical interface that connects the robot to the user, in direct contact with the wearer's skin. Compared to state-of-the-art measures, the advantage of this approach is that it allows for a distributed measure of the interaction pressure, which could be useful for the assessment of safety and comfort of human-robot interaction. This paper presents the new sensor and its characterization, and the development of an interaction measurement apparatus, which is applied to a lower-limb rehabilitation robot. The system is calibrated, and an example its use during a prototypical gait training task is presented.

Assistance using adaptive oscillators: robustness to errors in the identification of the limb parameters.

This paper provides a robustness analysis of the method we recently developed for rhythmic movement assistance using adaptive oscillators. An adaptive oscillator is a mathematical tool capable of extracting high-level features (i.e. amplitude, frequency, offset) of a quasi-sinusoidal measured movement, a rhythmic flexion-extension of the elbow in this case. By the use of a simple inverse dynamical model, the system can predict the torque produced by a human participant, such that a fraction of this estimated torque is fed back through a series elastic actuator to provide movement assistance. This paper objectives are twofold. First, we introduce a new 1 DOF assistive device developed in our lab. Second, we derive model-based predictions and conduct experimental validations to measure the variations in movement frequency as a function of the open parameters of the inverse dynamical model. As such, the paper provides an estimation of the robustness of our method due to model approximations. As main result, the paper reveals that the movement frequency is particularly robust to errors in the estimation of the damping coefficient. This is of high interest for the applicability of our approach, this parameter being in general the most difficult to identify.