Walking is not like reaching: evidence from periodic mechanical perturbations

Parkinsonian Tremor as Unstable Feedback in a Physiologically Consistent Control Framework

Parkinson's disease (PD) is characterized by decreased dopamine in the basal ganglia that causes excessive tonic inhibition of the thalamus. This excessive inhibition seems to explain inhibitory motor symptoms in PD, but the source of tremor remains unclear. This paper investigates how neural inhibition may change the closed-loop characteristics of the human motor control system to determine how this established pathophysiology could produce tremor. The rate-coding model of neural signals suggests increased inhibition decreases signal amplitude, which could create a mismatch between the closed-loop dynamics and the internal models that overcome proprioceptive feedback delays. This paper aims to identify a candidate model structure with decreased-amplitude-induced tremor in PD that also agrees with previously recorded movements of healthy and cerebellar patients. The optimal feedback control theory of human motor control forms the basis of the model. Key additional elements include gating of undesired movements via the basal ganglia-thalamus-motor cortex circuit and the treatment of the efferent copy of the control input as a measurement in the state estimator. Simulations confirm the model's ability to capture tremor in PD and also demonstrate how disease progression could affect tremor and other motor symptoms, providing insight into the existence of tremor and non-tremor phenotypes. Altogether, the physiological underpinnings of the model structure and the agreement of model predictions with clinical observations provides support for the hypothesis that unstable feedback produces parkinsonian tremor. Consequently, these results also support the associated framework for the neuroanatomy of human motor control.

Continuous neural control of a bionic limb restores biomimetic gait after amputation

For centuries scientists and technologists have sought artificial leg replacements that fully capture the versatility of their intact biological counterparts. However, biological gait requires coordinated volitional and reflexive motor control by complex afferent and efferent neural interplay, making its neuroprosthetic emulation challenging after limb amputation. Here we hypothesize that continuous neural control of a bionic limb can restore biomimetic gait after below-knee amputation when residual muscle afferents are augmented. To test this hypothesis, we present a neuroprosthetic interface consisting of surgically connected, agonist-antagonist muscles including muscle-sensing electrodes. In a cohort of seven leg amputees, the interface is shown to augment residual muscle afferents by 18% of biologically intact values. Compared with a matched amputee cohort without the afferent augmentation, the maximum neuroprosthetic walking speed is increased by 41%, enabling equivalent peak speeds to persons without leg amputation. Further, this level of afferent augmentation enables biomimetic adaptation to various walking speeds and real-world environments, including slopes, stairs and obstructed pathways. Our results suggest that even a small augmentation of residual muscle afferents restores biomimetic gait under continuous neuromodulation in individuals with leg amputation.

Temporal organization of stride-to-stride variations contradicts predictive models for sensorimotor control of footfalls during walking

Walking exhibits stride-to-stride variations. Given ongoing perturbations, these variations critically support continuous adaptations between the goal-directed organism and its surroundings. Here, we report that stride-to-stride variations during self-paced overground walking show cascade-like intermittency-stride intervals become uneven because stride intervals of different sizes interact and do not simply balance each other. Moreover, even when synchronizing footfalls with visual cues with variable timing of presentation, asynchrony in the timings of the cue and footfall shows cascade-like intermittency. This evidence conflicts with theories about the sensorimotor control of walking, according to which internal predictive models correct asynchrony in the timings of the cue and footfall from one stride to the next on crossing thresholds leading to the risk of falling. Hence, models of the sensorimotor control of walking must account for stride-to-stride variations beyond the constraints of threshold-dependent predictive internal models.

Generating an Adaptive and Robust Walking Pattern for a Prosthetic Ankle-Foot by Utilizing a Nonlinear Autoregressive Network With Exogenous Inputs

One of the major challenges in developing powered lower limb prostheses is emulating the behavior of an intact lower limb with different walking speeds over diverse terrains. Numerous studies have been conducted on control algorithms in the field of rehabilitation robotics to achieve this overarching goal. Recent studies on powered prostheses have frequently used a hierarchical control scheme consisting of three control levels. Most control structures have at least one element of discrete transition properties that requires numerous sensors to improve classification accuracy, consequently increasing computational load and costs. In this study, we proposed a user-independent and free-mode method for eliminating the need to switch among different controllers. We constructed a database by using four OPAL wearable devices (Mobility Lab, APDM Inc., USA) for seven able-bodied subjects. We recorded the gait of each subject at three ambulation speeds during ground-level walking to train a nonlinear autoregressive network with an exogenous input recurrent neural network (NARX RNN) to estimate foot orientation (angular position) in the sagittal plane using shank angular velocity as external input. The trained NARX RNN estimated the foot orientation of all the subjects at different walking speeds over flat terrain with an average root-mean-square error (RMSE) of 2.1° ± 1.7°. The minimum correlation between the estimated and measured values was 86%. Moreover, a t-test showed that the error was normally distributed with a high certainty level (0.88 minimum p -value).

Integrating wearables and modelling for monitoring rehabilitation following total knee joint replacement

BACKGROUND AND OBJECTIVE

Wearable inertial devices integrated with modelling and cloud computing have been widely adopted in the sports sector, however, their use in the health and medical field has yet to be fully realised. To date, there have been no reported studies concerning the use of wearables as a surrogate tool to monitor knee joint loading during recovery following a total knee joint replacement. The objective of this study is to firstly evaluate if peak tibial acceleration from wearables during gait is a good surrogate metric for computer modelling predicted functional knee loading; and secondly evaluate if traditional clinical patient related outcomes measures are consistent with wearable predictions.

METHODS

Following ethical approval, four healthy participants were used to establish the relationship between computer modelling predicted knee joint loading and wearable measured tibial acceleration. Following this, ten patients who had total knee joint replacements were then followed during their 6-week rehabilitation. Gait analysis, wearable acceleration, computer models of knee joint loading, and patient related outcomes measures including the Oxford knee score and range of motion were recorded.

RESULTS

A linear correlation (R² of 0.7-0.97) was observed between peak tibial acceleration (from wearables) and musculoskeletal model predicted knee joint loading during gait in healthy participants first. Whilst patient related outcome measures (Oxford knee score and patient range of motion) were observed to improve consistently during rehabilitation, this was not consistent with all patient's tibial acceleration. Only those patients that exhibited increasing peak tibial acceleration over 6-weeks rehabilitation were positively correlated with the Oxford knee score (R² of 0.51 to 0.97). Wearable predicted tibial acceleration revealed three patients with a consistent knee loading, five patients with improving knee loading, and two patients with declining knee loading during recovery. Hence, 20% of patients did not present with satisfactory joint loading following total knee joint replacement and this was not detected with current patient related outcome measures.

CONCLUSIONS

The use of inertial measurement units or wearables in this study provided additional insight into patients who were not exhibiting functional improvements in joint loading, and offers clinicians an 'off-site' early warning metric to identify potential complications during recovery and provide the opportunity for early intervention. This study has important implications for improving patient outcomes, equity, and for those who live in rural regions.

Gait parameters when walking with or without rollator on different surface characteristics: a pilot study among healthy individuals

Objectives

Gait parameters can measure risks of falling and mortality and identify early stages of frailty. The use of walking aid changes gait parameters. The aim of this study was to describe differences in gait parameters among healthy adults when walking on different surfaces and under different conditions, with and without a rollator.

Results

Ten healthy participants walked first without and then with a rollator upslope, downslope and on flat surface, on bitumen and gravel respectively. Step length, walking speed and sideway deviation was measured using an inertial measurement unit. Walking up a slope using a rollator generated the longest step length and walking down a slope using a rollator the shortest. Fastest walking speed was used when walking up a slope with rollator and slowest when walking down a slope with rollator. Sideway deviation was highest when walking down a slope and lowest when walking on gravel, both without rollator. Highest walk ratio was found when walk up a slope without rollator and lowest when walking down a slope with rollator. Data from this study provides valuable knowledge regarding gait parameters among healthy individuals, useful for future clinical research relevant for rehabilitation and public health.

Simulation of Electromagnetic Generator as Biomechanical Energy Harvester

Portable electronic devices are dependent on batteries as the ultimate source of power. Irrefutably, batteries only have a limited operating period as they need to be regularly replaced or recharged. In many situations, the power grid infrastructure is not easily accessible to recharge the batteries and the recharging duration is also not convenient for the user to wait. Enhancement of a reliable electronic system by preventing power interruptions in remote areas is essential. Similarly, modern medical instruments and implant devices need reliable, almost maintenance-free power to ensure they are able to operate in all situations without any power interruptions. In this paper, the small-sized electromagnetic generator was designed to produce higher power by utilizing the knee angle transition involved during the walking phase as the input rotary force. The proposed generator design was investigated through COMSOL Multiphysics simulation. The achieved output RMS power was in the range of 3.31 W to 14.95 W based on the RPM range between 360 RPM to 800 RPM.

Gait Entrainment to Torque Pulses from a Hip Exoskeleton Robot

Robot-aided locomotor rehabilitation has proven challenging. To facilitate progress, it is important to first understand the neuro-mechanical dynamics and control of unimpaired human locomotion. Our previous studies found that human gait entrained to periodic torque pulses at the ankle when the pulse period was close to preferred stride duration. Moreover, synchronized gait exhibited constant phase relation with the pulses so that the robot provided mechanical assistance. To test the generality of mechanical gait entrainment, this study characterized unimpaired human subjects' responses to periodic torque pulses during overground walking. The intervention was applied by a hip exoskeleton robot, Samsung GEMS-H. Gait entrainment was assessed based on the time-course of the phase at which torque pulses occurred within each stride. Experiments were conducted for two consecutive days to evaluate whether the second day elicited more entrainment. Whether entrainment was affected by the difference between pulse period and preferred stride duration was also assessed. Results indicated that the intervention evoked gait entrainment that occurred more often when the period of perturbation was closer to subjects' preferred stride duration, but the difference between consecutive days was insignificant. Entrainment was accompanied by convergence of pulse phase to a similar value across all conditions, where the robot maximized mechanical assistance. Clear evidence of motor adaptation indicated the potential of the intervention for rehabilitation. This study quantified important aspects of the nonlinear neuro-mechanical dynamics underlying unimpaired human walking, which will inform the development of effective approaches to robot-aided locomotor rehabilitation, exploiting natural dynamics in a minimally-encumbering way.

Applying Hip Stiffness With an Exoskeleton to Compensate Gait Kinematics

Neurological disorders and aging induce impaired gait kinematics. Despite recent advances, effective methods using lower-limb exoskeleton robots to restore gait kinematics are as yet limited. In this study, applying virtual stiffness using a hip exoskeleton was investigated as a possible method to guide users to change their gait kinematics. With a view to applications in locomotor rehabilitation, either to provide assistance or promote recovery, this study assessed whether imposed stiffness induced changes in the gait pattern during walking; and whether any changes persisted upon removal of the intervention, which would indicate changes in central neuro-motor control. Both positive and negative stiffness induced immediate and persistent changes of gait kinematics. However, the results showed little behavioral evidence of persistent changes in neuro-motor control, not even short-lived aftereffects. In addition, stride duration was little affected, suggesting that at least two dissociable layers exist in the neuro-motor control of human walking. The lack of neuro-motor adaptation suggests that, within broad limits, the central nervous system is surprisingly indifferent to the details of lower limb kinematics. The lack of neuro-motor adaptation also suggests that alternative methods may be required to implement a therapeutic technology to promote recovery. However, the immediate, significant, and reproducible changes in kinematics suggest that applying hip stiffness with an exoskeleton may be an effective assistive technology for compensation.

Evaluating the energetics of entrainment in a human-machine coupled oscillator system

During locomotion, humans sometimes entrain (i.e. synchronize) their steps to external oscillations: e.g. swaying bridges, tandem walking, bouncy harnesses, vibrating treadmills, exoskeletons. Previous studies have discussed the role of nonlinear oscillators (e.g. central pattern generators) in facilitating entrainment. However, the energetics of such interactions are unknown. Given substantial evidence that humans prioritize economy during locomotion, we tested whether reduced metabolic expenditure is associated with human entrainment to vertical force oscillations, where frequency and amplitude were prescribed via a custom mechatronics system during walking. Although metabolic cost was not significantly reduced during entrainment, individuals expended less energy when the oscillation forces did net positive work on the body and roughly selected phase relationships that maximize positive work. It is possible that individuals use mechanical cues to infer energy cost and inform effective gait strategies. If so, an accurate prediction may rely on the relative stability of interactions with the environment. Our results suggest that entrainment occurs over a wide range of oscillation parameters, though not as a direct priority for minimizing metabolic cost. Instead, entrainment may act to stabilize interactions with the environment, thus increasing predictability for the effective implementation of internal models that guide energy minimization.

Closing the Loop on Exoskeleton Motor Controllers: Benefits of Regression-Based Open-Loop Control

Lower-limb exoskeletons are widely researched to improve walking performance and mobility. Low-level sensor-less exoskeleton motor control is attractive for consumer applications due to reduced device complexity and cost, but complex and variable transmission system configurations make the development of effective open-loop motor controllers that are responsive to user input challenging. The objective of this study was to develop and validate an open-loop motor control framework resulting in similar or greater performance vs. closed-loop torque control. We used generalized linear regression to develop two open-loop controllers by modeling motor current during exoskeleton-assisted walking; a "complex" model used desired torque and estimated ankle angular velocity as inputs, while a "simple" model used desired torque alone. Five participants walked at 1.0-1.3 m/s on a treadmill with closed-loop and both open-loop controllers providing ankle exoskeleton assistance. Both open-loop current controllers had similar root-mean-squared torque tracking error (p=0.23) compared to the closed-loop torque-feedback controller. Both open-loop controllers had improved relative average torque production (p<0.001 complex, p=0.022 simple), lower power consumption (p<0.001 for both), and reduced operating noise (p=0.002 complex, p<0.001 simple) over the closed-loop controller. New control models developed for a different ankle exoskeleton configuration showed similar improvements (lower torque error, greater average and peak torque production, lower power consumption) over closed-loop control during over-ground walking. These results demonstrate that our framework can produce open-loop motor controllers that match closed-loop control performance during exoskeleton operation.

Functional Resistance Training to Improve Knee Strength and Function After Acute Anterior Cruciate Ligament Reconstruction: A Case Study

BACKGROUND

Thigh muscle weakness after anterior cruciate ligament reconstruction (ACLR) can persist after returning to activity. While resistance training can improve muscle function, "nonfunctional" training methods are not optimal for inducing transfer of benefits to activities such as walking. Here, we tested the feasibility of a novel functional resistance training (FRT) approach to restore strength and function in an individual with ACLR.

HYPOTHESIS

FRT would improve knee strength and function after ACLR.

STUDY DESIGN

Case report.

LEVEL OF EVIDENCE

Level 5.

METHODS

A 15-year-old male patient volunteered for an 8-week intervention where he performed 30 minutes of treadmill walking, 3 times per week, while wearing a custom-designed knee brace that provided resistance to the thigh muscles of his ACLR leg. Thigh strength, gait mechanics, and corticospinal and spinal excitability were assessed before and immediately after the 8-week intervention. Voluntary muscle activation was evaluated immediately after the intervention.

RESULTS

Knee extensor and flexor strength increased in the ACLR leg from pre- to posttraining (130 to 225 N·m [+74%] and 44 to 88 N·m [+99%], respectively) and increases in between-limb extensor and flexor strength symmetry (45% to 92% [+74%] and 47% to 72% [+65%], respectively) were also noted. After the intervention, voluntary muscle activation in the ACLR leg was 72%, compared with the non-ACLR leg at 75%. Knee angle and moment during late stance phase decreased (ie, improved) in the ACLR leg and appeared more similar to the non-ACLR leg after FRT training (18° to 14° [-23.4] and 0.07 to -0.02 N·m·kg^-1·m^-1 [-122.8%], respectively). Corticospinal and spinal excitability in the ACLR leg decreased (3511 to 2511 [-28.5%] and 0.42 to 0.24 [-43.7%], respectively) from pre- to posttraining.

CONCLUSION

A full 8 weeks of FRT that targeted both quadriceps and hamstring muscles lead to improvements in strength and gait, suggesting that FRT may constitute a promising and practical alternative to traditional methods of resistance training.

CLINICAL RELEVANCE

FRT may serve as a viable approach to improve knee strength and function after ACL reconstruction.

Mechanisms of gait phase entrainment in healthy subjects during rhythmic electrical stimulation of the medial gastrocnemius

Studies have shown that human gait entrains to rhythmic bursts of ankle torque for perturbation intervals both slightly shorter and slightly longer than the natural stride period while walking on a treadmill and during overground walking, with phase alignment such that the torque adds to ankle push-off. This study investigated whether human gait also entrains to align the phase of rhythmic electrical stimulation of the gastrocnemius muscle with the timing of ankle push-off. In addition, this study investigated the muscle response to electrical stimulation at different phases of the gait cycle. We found that for both treadmill and overground walking entrainment was observed with phasing that aligned the stimuli with ankle push-off or just before foot contact. Achilles tendon wave speed measurements showed a significant difference (increase) in tendon load when electrical stimulation was applied just after foot contact and during swing phase, with a greater increase for higher amplitudes of electrical stimulation. However, stimulation did not increase tendon load when the timing coincided with push-off. Stride period measurements also suggest the effect of electrical stimulation is sensitive to the gait phase it is applied. These results confirmed that timing aligned with push-off is an attractor for electrical stimulation-induced perturbations of the medial gastrocnemius, and that the muscle response to stimulation is sensitive to timing and amplitude. Future research should investigate other muscles and timings and separate sensory vs. motor contributions to these phenomena.

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.

Single-stride exposure to pulse torque assistance provided by a robotic exoskeleton at the hip and knee joints

Robot assisted gait retraining is an increasingly common method for supporting restoration of walking function after neurological injury. Gait speed, an indicator of walking function, is correlated with propulsive force, a measure modulated by the posture of the trailing limb at push-off. With the ultimate goal of improving efficacy of robot assisted gait retraining, we sought to directly target gait propulsion, by exposing subjects to pulses of joint torque applied at the hip and knee joints to modulate push-off posture. In this work, we utilized a robotic exoskeleton to apply pulses of torque to the hip and knee joints, during individual strides, of 16 healthy control subjects, and quantified the effects of this intervention on hip extension and propulsive impulse during and after application of these pulses. We observed significant effects in the outcome measures primarily at the stride of pulse application and generally no after effects in the following strides. Specifically, when pulses were applied at late stance, we observed a significant increase in propulsive impulse when knee and/or hip flexion pulses were applied and a significant increase in hip extension angle when hip extension torque pulses were applied. When pulses were applied at early stance, we observed a significant increase in propulsive impulse associated with hip extension torque.

Evidence of a "Clock" Determining Human Locomotion

The motor control of human locomotion is still an open issue, and it may be the leading cause of the low effectiveness of lower limbs rehabilitation therapies. Locomotion motor control has proved to be fundamentally different from the upper limbs reaching task strategies, which have been used for the development of current motor control computational models used to define rehabilitation protocols. The main difference between these two tasks is the relevance of the environmental dynamics in task planning and execution. Reaching movements are dominated by the intrinsic impedance of the human body. On the other hand, locomotion is determined by the interaction between the human body and Earth's gravity. The dynamic primitives have been recently proposed to explain how humans account for the environmental dynamics during motor control; however, it is not yet possible to explain how the nervous system combines the information. This paper proposes and validates with human data that the brain controls locomotion to have the centre of mass moving between the two legs as a harmonic oscillator. This finding has enabled us to propose a control architecture that can explain how the motor primitives can be described as a special type of dynamics primitives.

A Postural Model for Tracking the Base of Support

Mobility impairment is a major challenge for the healthcare systems of developed countries. Balance deterio-ration is a physiological consequence of the ageing process, which makes it an endemic problem in ageing societies. Despite the importance of this issue, the development of appropriate therapies and protocols is challenging due to our limited understanding of human locomotion and equilibrium. This paper presents a technique that can track the BoS geometry from the feet' posture and its validation with healthy subjects. The proposed model uses a posture dependent reference frame called Saddle Space, which is aligned to the principal direction of the potential energy surface. The target application for the model described in this paper is the development of sensors for the evaluation of balance during activity of daily living. However, the proposed methodology can also be applied to bipedal robots, and the saddle space can also be employed to describe other posture dependent variables.

The effect of stride length on lower extremity joint kinetics at various gait speeds

Robot-assisted training is a promising tool under development for improving walking function based on repetitive goal-oriented task practice. The challenges in developing the controllers for gait training devices that promote desired changes in gait is complicated by the limited understanding of the human response to robotic input. A possible method of controller formulation can be based on the principle of bio-inspiration, where a robot is controlled to apply the change in joint moment applied by human subjects when they achieve a gait feature of interest. However, it is currently unclear how lower extremity joint moments are modulated by even basic gait spatio-temporal parameters. In this study, we investigated how sagittal plane joint moments are affected by a factorial modulation of two important gait parameters: gait speed and stride length. We present the findings obtained from 20 healthy control subjects walking at various treadmill-imposed speeds and instructed to modulate stride length utilizing real-time visual feedback. Implementing a continuum analysis of inverse-dynamics derived joint moment profiles, we extracted the effects of gait speed and stride length on joint moment throughout the gait cycle. Moreover, we utilized a torque pulse approximation analysis to determine the timing and amplitude of torque pulses that approximate the difference in joint moment profiles between stride length conditions, at all gait speed conditions. Our results show that gait speed has a significant effect on the moment profiles in all joints considered, while stride length has more localized effects, with the main effect observed on the knee moment during stance, and smaller effects observed for the hip joint moment during swing and ankle moment during the loading response. Moreover, our study demonstrated that trailing limb angle, a parameter of interest in programs targeting propulsion at push-off, was significantly correlated with stride length. As such, our study has generated assistance strategies based on pulses of torque suitable for implementation via a wearable exoskeleton with the objective of modulating stride length, and other correlated variables such as trailing limb angle.

Dynamic stability and stepping strategies of young healthy adults walking on an oscillating treadmill

Understanding how people modify their stepping to maintain gait stability may provide information on fall risk and help to understand strategies used to reduce loss of balance. The purpose of this study was to identify the stepping strategies healthy young individuals select to maintain balance while walking on a destabilizing surface in various directions. A treadmill mounted on top of a 6 degree-of-freedom motion base was used to generate support surface oscillations in different degrees of freedom and amplitudes. Fifteen healthy young adults (21.3 ± 1.4 years) walked at self-selected speeds while continuous sinusoidal oscillations were imposed to the support surface in a one degree of freedom: rotation or translation in the mediolateral (ML) direction and rotation or translation in the anteroposterior (AP) direction, with each condition repeated at three different amplitudes. We compared step width, length, and frequency and the mean and variability of margin of stability (MoS) during each experimental walking condition with a control condition, in which the support surface was stationary. Subjects chose a common strategy of increasing step width (p < 0.001) and decreasing step length (p = 0.008) while increasing mediolateral MoS (p < 0.001), particularly during oscillations that challenged frontal plane control, with rotations of the walking surface producing the greatest changes to stepping.

Effects of periodic sensory perturbations during electrical stimulation on gait cycle period

The spinal cord contains the neural circuitry needed to generate rhythmic walking motions, and afferent sensory feedbacks are involved in the control of locomotion. In this study, we examined the influence of periodic electrical stimulation on the change in gait cycle period during treadmill walking. 40 subjects walked on a treadmill while receiving periodic bursts of electrical stimulation at various perturbation periods (-20, -40, -60, +20, +40 milliseconds from their initial gait cycle periods). Eleven subjects received electrical stimulation to the hamstring, and 29 received electrical stimulation to the calf. Each subject completed four trials; two trials were conducted using high amplitude stimulation causing a slight degree of joint motion, and the other two trials were conducted using reduced amplitude stimulation which did not cause observable motion. Through the trials, we sought to answer the following questions: 1) does the amplitude of electrical stimulation have an effect on the level of entrainment? 2) does the stimulation site effect the level of entrainment? Entrainment refers to the synchronization of gait cycle period to the period of electrical stimulation. The results showed that entrainment was observed when the perturbation periods were induced relatively close to the subject’s initial gait cycle period. For both stimulation sites, entrainment was shown in 59% of subjects at +/- 20 milliseconds from the initial gait cycle period. With reduced amplitude, entrainment was still observed (51% all stimulation site groups at +/- 20 milliseconds). In addition, after-effects following electrical perturbation were present as seen by changes in the mean gait cycle period. Our results suggest that human locomotor control is organized with a semi-autonomous peripheral oscillator influenced by afferent information, and that electrical stimulation has the potential to be a simpler, and cost-effective tool for locomotion rehabilitation.

Toward goal-oriented robotic gait training: The effect of gait speed and stride length on lower extremity joint torques

Robot-assisted gait training is becoming increasingly common to support recovery of walking function after neurological injury. How to formulate controllers capable of promoting desired features in gait, i.e. goals, is complicated by the limited understanding of the human response to robotic input. A possible method to formulate controllers for goal-oriented gait training is based on the analysis of the joint torques applied by healthy subjects to modulate such goals. The objective of this work is to understand how sagittal plane joint torque is affected by two important gait parameters: gait speed (GS) and stride length (SL). We here present the results obtained from healthy subjects walking on a treadmill at different speeds, and asked to modulate stride length via visual feedback. Via principal component analysis, we extracted the global effects of the two factors on the peak-to-peak amplitude of joint torques. Next, we used a torque pulse approximation analysis to determine optimal timing and amplitude of torque pulses that approximate the SL-specific difference in joint torque profiles measured at different values of GS. Our results show a strong effect of GS on the torque profiles in all joints considered. In contrast, SL mostly affects the torque produced at the knee joint at early and late stance, with smaller effects on the hip and ankle joints. Our analysis generated a set of torque assistance profiles that will be experimentally tested using gait training robots.

The critical phase for visual control of human walking over complex terrain

To walk efficiently over complex terrain, humans must use vision to tailor their gait to the upcoming ground surface without interfering with the exploitation of passive mechanical forces. We propose that walkers use visual information to initialize the mechanical state of the body before the beginning of each step so the resulting ballistic trajectory of the walker's center-of-mass will facilitate stepping on target footholds. Using a precision stepping task and synchronizing target visibility to the gait cycle, we empirically validated two predictions derived from this strategy: (1) Walkers must have information about upcoming footholds during the second half of the preceding step, and (2) foot placement is guided by information about the position of the target foothold relative to the preceding base of support. We conclude that active and passive modes of control work synergistically to allow walkers to negotiate complex terrain with efficiency, stability, and precision.

Treadmill vs. overground walking: different response to physical interaction

Rehabilitation of human motor function is an issue of growing significance, and human-interactive robots offer promising potential to meet the need. For the lower extremity, however, robot-aided therapy has proven challenging. To inform effective approaches to robotic gait therapy, it is important to better understand unimpaired locomotor control: its sensitivity to different mechanical contexts and its response to perturbations. The present study evaluated the behavior of 14 healthy subjects who walked on a motorized treadmill and overground while wearing an exoskeletal ankle robot. Their response to a periodic series of ankle plantar flexion torque pulses, delivered at periods different from, but sufficiently close to, their preferred stride cadence, was assessed to determine whether gait entrainment occurred, how it differed across conditions, and if the adapted motor behavior persisted after perturbation. Certain aspects of locomotor control were exquisitely sensitive to walking context, while others were not. Gaits entrained more often and more rapidly during overground walking, yet, in all cases, entrained gaits synchronized the torque pulses with ankle push-off, where they provided assistance with propulsion. Furthermore, subjects entrained to perturbation periods that required an adaption toward slower cadence, even though the pulses acted to accelerate gait, indicating a neural adaptation of locomotor control. Lastly, during 15 post-perturbation strides, the entrained gait period was observed to persist more frequently during overground walking. This persistence was correlated with the number of strides walked at the entrained gait period (i.e., longer exposure), which also indicated a neural adaptation.NEW & NOTEWORTHY We show that the response of human locomotion to physical interaction differs between treadmill and overground walking. Subjects entrained to a periodic series of ankle plantar flexion torque pulses that shifted their gait cadence, synchronizing ankle push-off with the pulses (so that they assisted propulsion) even when gait cadence slowed. Entrainment was faster overground and, on removal of torque pulses, the entrained gait period persisted more prominently overground, indicating a neural adaptation of locomotor control.

Using a System Identification Approach to Investigate Subtask Control during Human Locomotion

Here we apply a control theoretic view of movement to the behavior of human locomotion with the goal of using perturbations to learn about subtask control. Controlling one's speed and maintaining upright posture are two critical subtasks, or underlying functions, of human locomotion. How the nervous system simultaneously controls these two subtasks was investigated in this study. Continuous visual and mechanical perturbations were applied concurrently to subjects (n = 20) as probes to investigate these two subtasks during treadmill walking. Novel application of harmonic transfer function (HTF) analysis to human motor behavior was used, and these HTFs were converted to the time-domain based representation of phase-dependent impulse response functions (ϕIRFs). These ϕIRFs were used to identify the mapping from perturbation inputs to kinematic and electromyographic (EMG) outputs throughout the phases of the gait cycle. Mechanical perturbations caused an initial, passive change in trunk orientation and, at some phases of stimulus presentation, a corrective trunk EMG and orientation response. Visual perturbations elicited a trunk EMG response prior to a trunk orientation response, which was subsequently followed by an anterior-posterior displacement response. This finding supports the notion that there is a temporal hierarchy of functional subtasks during locomotion in which the control of upper-body posture precedes other subtasks. Moreover, the novel analysis we apply has the potential to probe a broad range of rhythmic behaviors to better understand their neural control.

A Control Framework for Anthropomorphic Biped Walking Based on Stabilizing Feedforward Trajectories

Although dynamic walking methods have had notable successes in control of bipedal robots in the recent years, still most of the humanoid robots rely on quasi-static Zero Moment Point controllers. This work is an attempt to design a highly stable controller for dynamic walking of a human-like model which can be used both for control of humanoid robots and prosthetic legs. The method is based on using time-based trajectories that can induce a highly stable limit cycle to the bipedal robot. The time-based nature of the controller motivates its use to entrain a model of an amputee walking, which can potentially lead to a better coordination of the interaction between the prosthesis and the human. The simulations demonstrate the stability of the controller and its robustness against external perturbations.

Implicit guidance to stable performance in a rhythmic perceptual-motor skill

Feedback about error or reward is regarded essential for aiding learners to acquire a perceptual-motor skill. Yet, when a task has redundancy and the mapping between execution and performance outcome is unknown, simple error feedback does not suffice in guiding the learner toward the optimal solutions. The present study developed and tested a new means of implicitly guiding learners to acquire a perceptual-motor skill, rhythmically bouncing a ball on a racket. Due to its rhythmic nature, this task affords dynamically stable solutions that are robust to small errors and noise, a strategy that is independent from actively correcting error. Based on the task model implemented in a virtual environment, a time-shift manipulation was designed to shift the range of ball-racket contacts that achieved dynamically stable solutions. In two experiments, subjects practiced with this manipulation that guided them to impact the ball with more negative racket accelerations, the indicator for the strategy with dynamic stability. Subjects who practiced under normal conditions took longer time to acquire this strategy, although error measures were identical between the control and experimental groups. Unlike in many other haptic guidance or adaptation studies, the experimental groups not only learned, but also maintained the stable solution after the manipulation was removed. These results are a first demonstration that more subtle ways to guide the learner to better performance are needed especially in tasks with redundancy, where error feedback may not be sufficient.

Walking on a moving surface: energy-optimal walking motions on a shaky bridge and a shaking treadmill can reduce energy costs below normal

Understanding how humans walk on a surface that can move might provide insights into, for instance, whether walking humans prioritize energy use or stability. Here, motivated by the famous human-driven oscillations observed in the London Millennium Bridge, we introduce a minimal mathematical model of a biped, walking on a platform (bridge or treadmill) capable of lateral movement. This biped model consists of a point-mass upper body with legs that can exert force and perform mechanical work on the upper body. Using numerical optimization, we obtain energy-optimal walking motions for this biped, deriving the periodic body and platform motions that minimize a simple metabolic energy cost. When the platform has an externally imposed sinusoidal displacement of appropriate frequency and amplitude, we predict that body motion entrained to platform motion consumes less energy than walking on a fixed surface. When the platform has finite inertia, a mass- spring-damper with similar parameters to the Millennium Bridge, we show that the optimal biped walking motion sustains a large lateral platform oscillation when sufficiently many people walk on the bridge. Here, the biped model reduces walking metabolic cost by storing and recovering energy from the platform, demonstrating energy benefits for two features observed for walking on the Millennium Bridge: crowd synchrony and large lateral oscillations.

Perspectives on human-human sensorimotor interactions for the design of rehabilitation robots

Physical interactions between patients and therapists during rehabilitation have served as motivation for the design of rehabilitation robots, yet we lack a fundamental understanding of the principles governing such human-human interactions (HHI). Here we review the literature and pose important open questions regarding sensorimotor interaction during HHI that could facilitate the design of human-robot interactions (HRI) and haptic interfaces for rehabilitation. Based on the goals of physical rehabilitation, three subcategories of sensorimotor interaction are identified: sensorimotor collaboration, sensorimotor assistance, and sensorimotor education. Prior research has focused primarily on sensorimotor collaboration and is generally limited to relatively constrained visuomotor tasks. Moreover, the mechanisms by which performance improvements are achieved during sensorimotor cooperation with haptic interaction remains unknown. We propose that the effects of role assignment, motor redundancy, and skill level in sensorimotor cooperation should be explicitly studied. Additionally, the importance of haptic interactions may be better revealed in tasks that do not require visual feedback. Finally, cooperative motor tasks that allow for motor improvement during solo performance to be examined may be particularly relevant for rehabilitation robotics. Identifying principles that guide human-human sensorimotor interactions may lead to the development of robots that can physically interact with humans in more intuitive and biologically inspired ways, thereby enhancing rehabilitation outcomes.

Dynamic primitives in the control of locomotion

Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered.

A simple state-determined model reproduces entrainment and phase-locking of human walking

Theoretical studies and robotic experiments have shown that asymptotically stable periodic walking may emerge from nonlinear limit-cycle oscillators in the neuro-mechanical periphery. We recently reported entrainment of human gait to periodic mechanical perturbations with two essential features: 1) entrainment occurred only when the perturbation period was close to the original (preferred) walking period, and 2) entrainment was always accompanied by phase locking so that the perturbation occurred at the end of the double-stance phase. In this study, we show that a highly-simplified state-determined walking model can reproduce several salient nonlinear limit-cycle behaviors of human walking: 1) periodic gait that is 2) asymptotically stable; 3) entrainment to periodic mechanical perturbations only when the perturbation period is close to the model's unperturbed period; and 4) phase-locking to locate the perturbation at the end of double stance. Importantly, this model requires neither supra-spinal control nor an intrinsic self-sustaining neural oscillator such as a rhythmic central pattern generator. Our results suggest that several prominent limit-cycle features of human walking may stem from simple afferent feedback processes without significant involvement of supra-spinal control or a self-sustaining oscillatory neural network.