Walking with perturbations: a guide for biped humans and robots

Design of Low-Cost Modular Bio-Inspired Electric-Pneumatic Actuator (EPA)-Driven Legged Robots

Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in electric-pneumatic actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monoped robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, (1) provide opportunities to study different locomotor subfunctions-stance, swing, and balance; (2) help investigate the role of actuation schemes in tasks such as hopping and walking; and (3) allow testing hypotheses regarding biological locomotors in real-world physical test benches.

Design of a Bio-Inspired Gait Phase Decoder Based on Temporal Convolution Network Architecture With Contralateral Surface Electromyography Toward Hip Prosthesis Control

Inter-leg coordination is of great importance to guarantee the safety of the prostheses wearers, especially for the subjects at high amputation levels. The mainstream of current controllers for lower-limb prostheses is based on the next motion state estimation by the past motion signals at the prosthetic side, which lacks immediate responses and increases falling risks. A bio-inspired gait pattern generation architecture was proposed to provide a possible solution to the bilateral coordination issue. The artificial movement pattern generator (MPG) based on the temporal convolution network, fusing with the motion intention decoded from the surface electromyography (sEMG) measured at the impaired leg and the motion status from the kinematic modality of the prosthetic leg, can predict four sub gait phases. Experiment results suggested that the gait phase decoder exhibited a relatively high intra-subject consistency in the gait phase inference, adapted to various walking speeds with mean decoding accuracy ranging from 89.27 to 91.16% across subjects, and achieved an accuracy of 90.30% in estimating the gait phase of the prosthetic leg in the hip disarticulation amputee at the self-selected pace. With the proof of concept and the offline experiment results, the proposed architecture improves the walking coordination with prostheses for the amputees at hip level amputation.

Effects of Immediate Aversive Stimulation on Haloperidol-Induced Catalepsy in Rats

In animal models, the administration of the dopaminergic D2 antagonist haloperidol affects the nigrostriatal pathway, inducing catalepsy, a state of immobility similar to Parkinson’s disease (PD) bradykinesia and akinesia. In PD, the motor impairments are due to difficulties in selecting and executing motor actions, associated with dopamine loss in basal ganglia and cortical targets. Motor and affective limbic networks seem to be integrated via a striato-nigro-striatal network, therefore, it is not surprising that the motor impairments in PD can be influenced by the patient’s emotional state. Indeed, when exposed to aversive stimuli or life-threatening events, immobile patients are capable of performing sudden movements, a phenomenon known as paradoxical kinesia. Thus, the present study investigated the effects of unconditioned and conditioned aversive stimulation on haloperidol-induced catalepsy in rats. First, male Wistar rats received intraperitoneal administration of saline or haloperidol (1 or 2 mg/kg) and were evaluated in the catalepsy bar test to assess the cataleptic state induced by the different doses of haloperidol over time. Next, we evaluated the effects of two types of unconditioned aversive stimuli–100 lux light (1 and 20 s) or 0.6 mA footshock (1 s)–on the catalepsy. Finally, we evaluated the effects of light conditioned stimuli (Light-CS), previously paired with footshocks, on the cataleptic state. Catalepsy was observed following haloperidol 1 and 2 mg/kg administration. Exposure to footshocks, but not to light, significantly reduced step-down latency during the catalepsy test. Although unconditioned light did not affect catalepsy, paired Light-CS did reduce step-down latency. Here, we have provided evidence of face validity for the study of paradoxical kinesia. In addition to demonstrating that immediate exposure to an aversive stimulus is capable of disrupting the cataleptic state, our findings show that haloperidol-induced catalepsy seems to be differently influenced depending on the modality of aversive stimulation. Our data suggest that the selective recruitment of threat response systems may bypass the dysfunctional motor circuit leading to the activation of alternative routes to drive movement.

Sleep deprivation affects gait control

Different levels of sleep restriction affect human performance in multiple aspects. However, it is unclear how sleep deprivation affects gait control. We applied a paced gait paradigm that included subliminal rhythm changes to analyze the effects of different sleep restriction levels (acute, chronic and control) on performance. Acute sleep deprivation (one night) group exhibited impaired performance in the sensorimotor synchronization gait protocol, such as a decrease in the Period Error between the footfalls and the auditory stimulus as well as missing more frequently the auditory cues. The group with chronic sleep restriction also underperformed when compared to the control group with a tendency to a late footfall with respect to the RAC sound. Our results suggest that partial or total sleep deprivation leads to a decrease in the performance in the sensorimotor control of gait. The superior performance of the chronic sleep group when compared to the acute group suggests that there is a compensatory mechanism that helps to improve motor performance.

Effect of dual tasking on a dynamic balance task in children with and without DCD

The purpose of this study was to compare performance of children with Developmental Coordination Disorder (DCD) and typically developing (TD) children in a dual task paradigm with a dynamic balance task on the Wii Fit as primary task and a concurrent cognitive (counting) or a concurrent bimanual fine motor task as secondary tasks. Using a cross-sectional design, 25 children with DCD and 38 TD children were assessed with the Movement Assessment Battery for Children, 2nd edition (MABC-2) and Divided Attention (DA) task of the KiTAP. Next, the single- and dual-tasks were performed and the level of interference or facilitation of the dual tasks was calculated. Regression analysis determined the predictive value of the DA and MABC-2 component balance outcomes on the dual task performance. On the motor and attentional tasks, the group of children with DCD scored significantly below the level of the TD children. The dual task effect showed similar interference and facilitation of tasks in the different dual-task conditions in both groups. In the dual task-cognitive condition, the divided attention abilities and the MABC-2 balance score predicted 25% of the Wii Fit dynamic balance task performance, whereas in the dual task-motor condition this was higher (31.6%). In both conditions, DA was a stronger predictor than MABC balance score and appears to be an important factor to consider when developing motor task training for children with DCD.

On the Basis for Stumble Recovery Strategy Selection in Healthy Adults

Healthy adults employ one of three primary strategies to recover from stumble perturbations-elevating, lowering, or delayed lowering. The basis upon which each recovery strategy is selected is not known. Though strategy selection is often associated with swing percentage at which the perturbation occurs, swing percentage does not fully predict strategy selection; it is not a physical quantity; and it is not strictly a real-time measurement. The objective of this work is to better describe the basis of strategy selection in healthy individuals during stumble events, and in particular to identify a set of real-time measurable, physical quantities that better predict stumble recovery strategy selection, relative to swing percentage. To do this, data from a prior seven-participant stumble experiment were reanalyzed. A set of biomechanical measurements at/after the perturbation were taken and considered in a two-stage classification structure to find the set of measurements (i.e., features) that best explained the strategy selection process. For Stage 1 (decision between initially elevating or lowering of the leg), the proposed model correctly predicted 99.0% of the strategies used, compared to 93.6% with swing percentage. For Stage 2 (decision between elevating or delayed lowering of the leg), the model correctly predicted 94.0% of the strategies used, compared to 85.6% with swing percentage. This model uses dynamic factors of the human body to predict strategy with substantially improved accuracy relative to swing percentage, giving potential insight into human physiology as well as potentially better informing the design of fall-prevention interventions.

Standing on unstable surface challenges postural control of tracking tasks and modulates neuromuscular adjustments specific to task complexity

Understanding the modulations of motor control in the presence of perturbations in task conditions of varying complexity is a key element towards the design of effective perturbation-based balance exercise programs. In this study we investigated the effect of mechanical perturbations, induced by an unstable surface, on muscle activation and visuo-postural coupling, when actively tracking target motion cues of different complexity. Four postural tasks following a visual oscillating target of varying target complexity (periodic-sinusoidal vs. chaotic-Lorenz) and surface (stable-floor vs. unstable-foam) were performed. The electromyographic activity of the main plantarflexor and dorsiflexor muscles was captured. The coupling between sway and target was assessed through spectral analysis and the system's local dynamic stability through the short-term maximum Lyapunov exponent. We found that external perturbations increased local instability and deteriorated visuo-motor coupling. Visuo-motor deterioration was greater for the chaotic target, implying that the effect of the induced perturbations depends on target complexity. There was a modulation of the neuromotor system towards amplification of muscle activity and coactivation to compensate surface-related perturbations and to ensure robust motor control. Our findings provide evidence that, in the presence of perturbations, target complexity induces specific modulations in the neuromotor system while controlling balance and posture.

Multiple strategies to correct errors in foot placement and control speed in human walking

Neural feedback plays a key role in maintaining locomotor stability in the face of perturbations. In this study, we systematically identified properties of neural feedback that contribute to stabilizing human walking by examining how the nervous system responds to small kinematic deviations away from the desired gait pattern. We collected data from 20 participants (9 men and 11 women). We simultaneously applied (1) small continuous mechanical perturbations, forces at the ankles that affected foot placement, and (2) small continuous sensory perturbations, movement of a virtual visual scene that produced the illusion of change in walking speed, to compare how neural feedback responds to actual and illusory kinematic deviations. We computed phase-dependent impulse response functions that describe kinematic and muscular responses to small brief perturbations to identify critical phases of the gait cycle when the nervous system modulates muscle activity. In addition to the known foot-placement strategies that counteract kinematic displacement, such as the modulation of the hamstring muscle group during swing, we identified phase-specific muscle modulations that compensated for the perturbations. In particular, our results suggested that an early-stance modulation of anterior leg muscles (i.e., dorsiflexors and quadriceps) is a general control mechanism that serves to control forward body propulsion and compensates for errors in foot placement. Another detected general compensatory strategy was the late-stance modulation of the rectus femoris and gastrocnemius muscles, which controls walking speed in the next cycle.

Interactions Between Different Age-Related Factors Affecting Balance Control in Walking

Maintaining balance during walking is a continuous sensorimotor control problem. Throughout the movement, the central nervous system has to collect sensory data about the current state of the body in space, use this information to detect possible threats to balance and adapt the movement pattern to ensure stability. Failure of this sensorimotor loop can lead to dire consequences in the form of falls, injury and death. Such failures tend to become more prevalent as people get older. While research has established a number of factors associated with higher risk of falls, we know relatively little about age-related changes of the underlying sensorimotor control loop and how such changes are related to empirically established risk factors. This paper approaches the problem of age-related fall risk from a neural control perspective. We begin by summarizing recent empirical findings about the neural control laws mapping sensory input to motor output for balance control during walking. These findings were established in young, neurotypical study populations and establish a baseline of sensorimotor control of balance. We then review correlates for deteriorating balance control in older adults, of muscle weakness, slow walking, cognitive decline, and increased visual dependency. While empirical associations between these factors and fall risk have been established reasonably well, we know relatively little about the underlying causal relationships. Establishing such causal relationships is hard, because the different factors all co-vary with age and are difficult to isolate empirically. One option to analyze the role of an individual factor for balance control is to use computational models of walking comprising all levels of the sensorimotor control loop. We introduce one such model that generates walking movement patterns from a short list of spinal reflex modules with limited supraspinal modulation for balance. We show how this model can be used to simulate empirical studies, and how comparison between the model and empirical results can indicate gaps in our current understanding of balance control. We also show how different aspects of aging can be added to this model to study their effect on balance control in isolation.

Plantarflexion force is amplified with sensory stimulation during ramping submaximal isometric contractions

Stimulating cutaneous nerves, causing tactile sensations, reduces the perceived heaviness of an object, suggesting that either descending commands are facilitated or the perception of effort is reduced when tactile sensation is enhanced. Sensory stimulation can also mitigate decrements in motor output and spinal cord excitability that occur with fatigue. The effects of sensory stimulation applied with coincident timing of voluntary force output, however, are yet to be examined. Therefore, the purpose of this study was to examine effects of sensory enhancement to nerves innervating opposed skin areas of the foot (top or bottom) on force production during voluntary plantarflexion or dorsiflexion contractions. Stimulation trains were applied for 2 s at either a uniform 150 Hz or a modulated frequency that increased linearly from 50 to 150 Hz and were delivered at the initiation of the contraction. Participants were instructed to perform a ramp contraction [~10% maximal voluntary contraction (MVC)/s] to ~20% MVC and then to hold ~20% MVC for 2 s while receiving real-time visual feedback. Cutaneous reflexes were evoked 75 ms after initiating the hold (75 ms after sensory enhancement ended). Force output was greater for all sensory-enhanced conditions compared with control during plantarflexion; however, force output was not amplified during dorsiflexion. Cutaneous reflexes evoked after sensory enhancement were unaltered. These results indicate that sensory enhancement can amplify plantarflexion but not dorsiflexion, likely as a result of differences in neuroanatomical projections to the flexor and extensor motor pools. Further work is required to elucidate the mechanisms of enhanced force during cutaneous stimulation.NEW & NOTEWORTHY The efficacy of behaviorally timed sensory stimulation to enhance sensations and amplify force output has not been examined. Here we show cutaneous nerve sensory stimulation can amplify plantarflexion force output. This amplification in force occurs irrespective of whether the cutaneous field that is stimulated resides on the surface that is producing the force or the opposing surface. This information may provide insights for the development of technologies to improve performance and/or rehabilitation training.

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques to approximate these sequences are based on reinforcement learning (RL). In this work we propose a multi-level system, where the same RL method is used first to learn the configuration of robot joints (poses) that allow it to stand with stability, and then in the second level, we find the sequence of poses that let it reach the furthest distance in the shortest time, while avoiding falling down and keeping a straight path. In order to evaluate this, we focus on measuring the time it takes for the robot to travel a certain distance. To our knowledge, this is the first work focusing both on speed and precision of the trajectory at the same time. We implement our model in a simulated environment using q-learning. We compare with the built-in walking modes of an NAO robot by improving normal-speed and enhancing robustness in fast-speed. The proposed model can be extended to other tasks and is independent of a particular robot model.

Swing Velocity Profiles of Small Limbs Can Arise from Transient Passive Torques of the Antagonist Muscle Alone

In large limbs, changing motor neuron activity typically controls within-movement velocity. For example, sequential agonist-antagonist-agonist motor neuron firing typically underlies the slowing often present at the end of human reaches. In physiological movements of large limbs, antagonistic muscle passive torque is generally negligible. In small limbs, alternatively, passive torques can determine limb rest position, generate restoring movements to it, and decrease agonist-generated movement amplitude and velocity maxima. These observations suggest that, in small limbs, passive forces might also control velocity changes within movements. We investigated this issue in stick insect middle leg femur-tibia (FT) joint. During swing, the FT joint extensor muscle actively shortens and the flexor muscle passively lengthens. As in human reaching, after its initial acceleration, FT joint velocity continuously decreases. We measured flexor passive forces during imposed stretches spanning the ranges of FT joint angles, angular velocities, and movement amplitudes present in leg swings. The viscoelastic "transient" passive force that occurs during and soon after stretch depended on all three variables and could be tens of times larger than the "steady-state" passive force commonly measured long after stretch end. We combined these data, the flexor and extensor moment arms, and an existing extensor model to simulate FT joint swing. To measure only passive (flexor) muscle-dependent effects, we used constant extensor activations in these simulations. In simulations using data from ten flexor muscles, flexor passive torque could always produce swings with, after swing initiation, continuously decreasing velocities. Antagonist muscle passive torques alone can thus control within-movement velocity.