Modeling Neuromotor Adaptation to Pulsed Torque Assistance During Walking.

Multiple mechanisms of motor learning contribute to the response of individuals to robot-aided gait training, including error-based learning and use-dependent learning. Previous models described either of these mechanisms, but not both, and their relevance to gait training is unknown. In this paper, we establish the validity of existing models to describe the response of healthy individuals to robot-aided training of propulsion via a robotic exoskeleton, and propose a new model that accounts for both use-dependent and error-based learning. We formulated five state-space models to describe the stride-by-stride evolution of metrics of propulsion mechanics during and after robot-assisted training, applied by a hip/knee robotic exoskeleton for 200 consecutive strides. The five models included a single-state, a two-state, a two-state fast and slow, a use-dependent learning (UDL), and a newly-developed modified UDL model, requiring 4, 9, 5, 3, and 4 parameters, respectively. The coefficient of determination (R 2) and Akaike information criterion (AIC) values were calculated to quantify the goodness of fit of each model. Model fit was conducted both at the group and at the individual participant level. At the group level, the modified UDL model shows the best goodness-of-fit compared to other models in AIC values in 15/16 conditions. At the participant level, both the modified UDL model and the two-state model have significantly better goodness-of-fit compared to the other models. In summary, the modified UDL model is a simple 4-parameter model that achieves similar goodness-of-fit compared to a two-state model requiring 9 parameters. As such, the modified UDL model is a promising model to describe the effects of robot-aided gait training on propulsion mechanics.

Development of an MRI-compatible robotic perturbation system for studying the task-dependent contribution of the brainstem to long-latency responses.

Methodological constraints have hindered direct in vivo measurement of reticulospinal tract (RST) function. The RST is thought to contribute to the increase in the amplitude of a long latency response (LLR), a stereotypical response evoked in stretched muscles, that arises when participants are asked to "resist" a perturbation. Thus, functional magnetic resonance imaging (fMRI) during robot-evoked LLRs under different task goals may be a method to measure motor-related RST function. We have developed the Dual Motor StretchWrist (DMSW), a new MR-compatible robotic perturbation system, and validated its functionality via experiments that used surface electromyography (sEMG) and fMRI. A first study was conducted outside the MRI scanner on six participants using sEMG to measure wrist flexor muscle activity associated with LLRs under different task instructions. Participants were given a Yield or Resist instruction before each trial and performance feedback based on the measured resistive torque was provided after every "Resist" trial to standardize LLR amplitude (LLRa). In a second study, ten participants completed two sessions of blocked perturbations under 1) Yield, 2) Resist, and 3) Yield Slow task conditions (control) during whole-brain fMRI. Statistical analysis of sEMG data shows significantly greater LLRa in Resist relative to Yield. Analysis of functional images shows increased activation primarily in the bilateral medulla and midbrain, and contralateral pons and primary motor cortex in the Resist condition. The results validate the capability of the DMSW to elicit LLRs of wrist muscles with different amplitudes as a function of task instruction, and its capability of simultaneous operation during fMRI.

Individual Muscle Force Estimation in the Human Forearm Using Multi-Muscle MR Elastography (MM-MRE).

OBJECTIVE: To establish the sensitivity of magnetic resonance elastography (MRE) to active muscle contraction in multiple muscles of the forearm. METHODS: We combined MRE of forearm muscles with an MRI-compatible device, the MREbot, to simultaneously measure the mechanical properties of tissues in the forearm and the torque applied by the wrist joint during isometric tasks. We measured shear wave speed of thirteen forearm muscles via MRE in a series of contractile states and wrist postures and fit these outputs to a force estimation algorithm based on a musculoskeletal model. RESULTS: Shear wave speed changed significantly upon several factors, including whether the muscle was recruited as an agonist or antagonist (p = 0.0019), torque amplitude (p = <0.0001), and wrist posture (p = 0.0002). Shear wave speed increased significantly during both agonist (p = <0.0001) and antagonist (p = 0.0448) contraction. Additionally, there was a greater increase in shear wave speed at greater levels of loading. The variations due to these factors indicate the sensitivity to functional loading of muscle. Under the assumption of a quadratic relationship between shear wave speed and muscle force, MRE measurements accounted for an average of 70% of the variance in the measured joint torque. CONCLUSION: This study shows the ability of MM-MRE to capture variations in individual muscle shear wave speed due to muscle activation and presents a method to estimate individual muscle force through MM-MRE derived measurements of shear wave speed. SIGNIFICANCE: MM-MRE could be used to establish normal and abnormal muscle co-contraction patterns in muscles of the forearm controlling hand and wrist function.

Concurrent Contribution of Co-contraction to Error Reduction during Dynamic Adaptation of the Wrist.

MRI-compatible robots provide a means of studying brain function involved in complex sensorimotor learning processes, such as adaptation. To properly interpret the neural correlates of behavior measured using MRI-compatible robots, it is critical to validate the measurements of motor performance obtained via such devices. Previously, we characterized adaptation of the wrist in response to a force field applied via an MRI-compatible robot, the MR-SoftWrist. Compared to arm reaching tasks, we observed lower end magnitude of adaptation, and reductions in trajectory errors beyond those explained by adaptation. Thus, we formed two hypotheses: that the observed differences were due to measurement errors of the MR-SoftWrist; or that impedance control plays a significant role in control of wrist movements during dynamic perturbations. To test both hypotheses, we performed a two-session counterbalanced crossover study. In both sessions, participants performed wrist pointing in three force field conditions (zero force, constant, random). Participants used either the MR-SoftWrist or the UDiffWrist, a non-MRI-compatible wrist robot, for task execution in session one, and the other device in session two. To measure anticipatory co-contraction associated with impedance control, we collected surface EMG of four forearm muscles. We found no significant effect of device on behavior, validating the measurements of adaptation obtained with the MR-SoftWrist. EMG measures of co-contraction explained a significant portion of the variance in excess error reduction not attributable to adaptation. These results support the hypothesis that for the wrist, impedance control significantly contributes to reductions in trajectory errors in excess of those explained by adaptation.

Changes in Resting State Functional Connectivity Associated with Dynamic Adaptation of Wrist Movements.

Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics (Shadmehr, 2017). Adapted motor plans are consolidated into memories that contribute to better performance on re-exposure. Consolidation begins within 15 min following training (Criscimagna-Hemminger and Shadmehr, 2008), and can be measured via changes in resting state functional connectivity (rsFC). For dynamic adaptation, rsFC has not been quantified on this timescale, nor has its relationship to adaptative behavior been established. We used a functional magnetic resonance imaging (fMRI)-compatible robot, the MR-SoftWrist (Erwin et al., 2017), to quantify rsFC specific to dynamic adaptation of wrist movements and subsequent memory formation in a mixed-sex cohort of human participants. We acquired fMRI during a motor execution and a dynamic adaptation task to localize brain networks of interest, and quantified rsFC within these networks in three 10-min windows occurring immediately before and after each task. The next day, we assessed behavioral retention. We used a mixed model of rsFC measured in each time window to identify changes in rsFC with task performance, and linear regression to identify the relationship between rsFC and behavior. Following the dynamic adaptation task, rsFC increased within the cortico-cerebellar network and decreased interhemispherically within the cortical sensorimotor network. Increases within the cortico-cerebellar network were specific to dynamic adaptation, as they were associated with behavioral measures of adaptation and retention, indicating that this network has a functional role in consolidation. Instead, decreases in rsFC within the cortical sensorimotor network were associated with motor control processes independent from adaptation and retention.SIGNIFICANCE STATEMENT Motor memory consolidation processes have been studied via functional magnetic resonance imaging (fMRI) by analyzing changes in resting state functional connectivity (rsFC) occurring more than 30 min after adaptation. However, it is unknown whether consolidation processes are detectable immediately (<15 min) following dynamic adaptation. We used an fMRI-compatible wrist robot to localize brain regions involved in dynamic adaptation in the cortico-thalamic-cerebellar (CTC) and cortical sensorimotor networks and quantified changes in rsFC within each network immediately after adaptation. Different patterns of change in rsFC were observed compared with studies conducted at longer latencies. Increases in rsFC in the cortico-cerebellar network were specific to adaptation and retention, while interhemispheric decreases in the cortical sensorimotor network were associated with alternate motor control processes but not with memory formation.

Measurement of stretch-evoked brainstem function using fMRI.

Knowledge on the organization of motor function in the reticulospinal tract (RST) is limited by the lack of methods for measuring RST function in humans. Behavioral studies suggest the involvement of the RST in long latency responses (LLRs). LLRs, elicited by precisely controlled perturbations, can therefore act as a viable paradigm to measure motor-related RST activity using functional Magnetic Resonance Imaging (fMRI). Here we present StretchfMRI, a novel technique developed to study RST function associated with LLRs. StretchfMRI combines robotic perturbations with electromyography and fMRI to simultaneously quantify muscular and neural activity during stretch-evoked LLRs without loss of reliability. Using StretchfMRI, we established the muscle-specific organization of LLR activity in the brainstem. The observed organization is partially consistent with animal models, with activity primarily in the ipsilateral medulla for flexors and in the contralateral pons for extensors, but also includes other areas, such as the midbrain and bilateral pontomedullary contributions.

Effects of Perturbation Velocity, Direction, Background Muscle Activation, and Task Instruction on Long-Latency Responses Measured From Forearm Muscles.

The central nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. The long-latency response (LLR) is the fastest process that directly involves cortical areas, with a motoneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interactions among many of these factors had not been systematically studied before. We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors - background muscle torque, perturbation direction, perturbation velocity, and task instruction - on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles after velocity-controlled wrist displacements. The effects of the four factors were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals. All factors significantly modulated LLRa, and their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations was greater than the one observed when subjects yielded to the perturbations (p < 0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (p < 0.001), but no effects of velocity were measured in absence of background torque. Also, our analysis identified significant modulations of LLRa in muscles shortened by the perturbation, including an interaction between torque and velocity, and an effect of both torque and velocity. The time-series analysis indicated the significance of additional transient effects in the LLR region for muscles undergoing shortening.

Robot-Aided Training of Propulsion During Walking: Effects of Torque Pulses Applied to the Hip and Knee Joints During Stance.

We sought to evaluate the effects of the application of torque pulses to the hip and knee joint via a robotic exoskeleton in the context of training propulsion during walking. Based on our previous study, we formulated a set of conditions of torque pulses applied to the hip and knee joint associated with changes in push-off posture, a component of propulsion. In this work, we quantified the effects of hip/knee torque pulses on metrics of propulsion, specifically hip extension (HE) and normalized propulsive impulse (NPI), in two experiments. In the first experiment, we exposed 16 participants to sixteen conditions of torque pulses during single strides to observe the immediate effects of pulse application. In the second experiment, we exposed 16 participants to a subset of those conditions for 200 strides to quantify short-term adaptation effects. During pulse application, NPI aligned with the expected modulation of push-off posture, while HE was modulated in the opposite direction. The timing of the applied pulses, early or late stance, was crucial, as the effects were often in the opposite direction when changing timing condition. Extension torque applied at late stance increased HE in both experiments - range of change in HE: (2.9 ± 0.4 deg, 7.7 ± 1.0 deg), . The same conditions resulted in a negative change in NPI only in the single pulse experiment - change in NPI for knee torque: -3.0 ± 0.4 ms, - and no significant change for hip torque. Also, knee extension and flexion torque during early and late stance, respectively, increased NPI during single pulse application - range of change in NPI: (3.8, 4.6) ± 0.8 ms, . During repeated pulse application, NPI increased for late stance flexion torque - range of change in NPI: (4.5 ± 0.7 ms, 4.8 ± 0.8 ms), , but not late stance extension torque. After exposure, we observed positive after-effects in HE in three conditions - range of change in HE: (2.0 ± 0.3 deg, 3.7 ± 0.7 deg) - and significant positive after-effects in NPI for early stance flexion torques - change in NPI: (2.7 ± 0.6 ms, ). These results indicate that positive propulsive after-effects can be achieved through repeated exposure to torque pulses.

Training Propulsion via Acceleration of the Trailing Limb.

Walking function, which is critical to performing many activities of daily living, is commonly assessed by walking speed. Walking speed is dependent on propulsion, which is governed by ankle moment and the posture of the trailing limb during push-off. Here, we present a new gait training paradigm that utilizes a dual belt treadmill to train both components of propulsion by accelerating the belt of the trailing limb during push-off. Accelerations require participants to produce greater propulsive force to counteract inertial effects, and increases extension of the trailing limb through increased belt velocity. We hypothesized that one session of training in this paradigm would produce after effects in propulsion mechanics and, consequently, walking speed. We tested the training paradigm on healthy young adults at two acceleration magnitudes-7 m/s2 (HA) and 2 m/s2 (LA)-and compared their results to a third control group (VC) that walked at a higher velocity during training. Results show that the HA group significantly increased walking speed following training (mean ± s.e.m: 0.073 ± 0.013 m/s, p < 0.001). The change in walking speed in the LA and VC groups was not significant (LA: 0.032 ± 0.013 m/s, VC: -0.003 ± 0.013 m/s). Responder analysis showed that changes in push-off posture and in activation of ankle plantar-flexor muscles contributed to the greater increases in gait speed measured in the HA group compared to the LA and VC groups. The duration of after effects post training suggest that the measured changes in neuromotor coordination are consistent with use-dependent learning.

Model-Based Estimation of Individual Muscle Force Based on Measurements of Muscle Activity in Forearm Muscles During Isometric Tasks.

OBJECTIVE: Several forward dynamics estimation approaches have been proposed to estimate individual muscle force. However, characterization of the estimation error that arises when measurements are available only from a subset of the muscles involved in the movement under analysis, as is the case of the forearm muscles, has been limited. Our objectives were: first, to quantify the accuracy of forward-dynamics muscle force estimators for forearm muscles; and second, to develop a muscle force estimator that is accurate even when measurements are available only from a subset of muscles acting on a given joint or segment. METHODS: We developed a neuromusculoskeletal (NMSK) estimator that integrates forward dynamics estimation with a neural model of muscle cocontraction to estimate individual muscle force during isometric contractions, suitable to operate when measurements are not available for all muscles. We developed a computational framework to assess the effect of physiological variability in muscle cocontraction, cross-talk, and measurement error on the estimator accuracy using a sensitivity analysis. We thus compared the performance of our estimator with that of a standard estimator that neglects the contribution of unmeasured muscles. RESULTS: The NMSK estimator reduces the estimation error by 25% in average noise conditions. Moreover, the NMSK estimator is robust against physiological variability in muscle cocontraction and outperforms the standard estimator even when the validity of the neural model is compromised. CONCLUSION AND SIGNIFICANCE: In isometric tasks, the NMSK estimator reduces muscle force estimation error compared to a standard estimator, and may enable future applications involving estimation of forearm muscle force during coordinated movements.

Training propulsion: Locomotor adaptation to accelerations of the trailing limb.

Many stroke survivors suffer from hemiparesis, a condition that results in impaired walking ability. Walking ability is commonly assessed by walking speed, which is dependent on propulsive force generation both in healthy and stroke populations. Propulsive force generation is determined by two factors: ankle moment and the posture of the trailing limb during push-off. Recent work has used robotic assistance strategies to modulate propulsive force with some success. However, robotic strategies are limited by their high cost and the technical difficulty of fitting and operating robotic devices in a clinical setting. Here we present a new paradigm for goal-oriented gait training that utilizes a split belt treadmill to train both components of propulsive force generation, achieved by accelerating the treadmill belt of the trailing limb during push off. Belt accelerations require subjects to produce greater propulsive force to maintain their position on the treadmill and increase trailing limb angle through increased velocity of the accelerated limb. We hypothesized that locomotor adaptation to belt accelerations would result in measurable after effects in the form of increased propulsive force generation. We tested our protocol on healthy subjects at two acceleration magnitudes. Our results show that 79% of subjects significantly increased propulsive force generation following training, and that larger accelerations translated to larger, more persistent behavioral gains.

MM-MRE: a new technique to quantify individual muscle forces during isometric tasks of the wrist using MR elastography.

Non-invasive in-vivo measurement of individual muscle force is limited by the infeasibility of placing force sensing elements in series with the musculo-tendon structures. While different methods based either on shear wave elastography or electromyography have been recently proposed to non-invasively estimate individual muscle forces, they can only be used to quantity forces in a limited set of superficial muscles. As such, they are not suitable to study the neuromuscular control of movements that require coordinated action of multiple muscles. In this work, we present multi-muscle magnetic resonance elastography (MM-MRE), a new technique capable of quantifying force for each muscle in the forearm, thus enabling the study of the neuromuscular control of wrist movements. To quantity individual muscle force, MM-MRE integrates measurements of joint torque provided by an MRI-compatible instrumented handle with muscle-specific measurements of shear wave speed obtained via MRE into a forward dynamic muscle force estimator based on a realistic musculoskeletal model of the forearm. A single-subject pilot experiment demonstrates the possibility of obtaining measurements from individual muscles and establishes that MM-MRE has sufficient sensitivity to detect changes in the muscle specific measurement of shear-wave speed following the application of isometric flexion and extension torques with self-selected intensity.

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.

Identifying the neural representation of fast and slow states in force field adaptation via fMRI.

Although neurorehabilitation is centered on motor learning and control processes, our understanding of how the brain learns to control movement is still limited. Motor adaptation is an error-driven motor learning process that is amenable to study in the laboratory setting. Behavioral studies of motor adaptation have coupled clever task design with computational modeling to study the control processes that underlie motor adaptation. These studies provide evidence of fast and slow learning states in the brain that combine to control neuromotor adaptation.Currently, the neural representation of these states remains unclear, especially for adaptation to changes in task dynamics, commonly studied using force fields imposed by a robotic device. Our group has developed the MR-SoftWrist, a robot capable of executing dynamic adaptation tasks during functional magnetic resonance imaging (fMRI) that can be used to localize these networks in the brain.We simulated an fMRI experiment to determine if signal arising from a switching force field adaptation task can localize the neural representations of fast and slow learning states in the brain. Our results show that our task produces reliable behavioral estimates of fast and slow learning states, and distinctly measurable fMRI activations associated with each state under realistic levels of behavioral and measurement noise. Execution of this protocol with the MR-SoftWrist will extend our knowledge of how the brain learns to control movement.

StretchfMRI: a novel technique to quantify the contribution of the reticular formation to long-latency responses via fMRI.

Increased reticulospinal (RS) function has been observed to cause both positive and negative outcomes in the recovery of motor function after corticospinal lesions such as stroke. Current knowledge of RS function is limited by the lack of accurate, noninvasive methods for measuring RS function. Recent studies suggest that the RS tract may be involved in processing and generating Long Latency Responses (LLRs). As such, LLRs, elicited by applying precisely controlled perturbations, can thus act as a reliable stimulus to measure brainstem function using fMRI with high signal-to-noise ratio.In this paper, we present StretchfMRI, a novel technique that enables simultaneous recording of neural and muscular activity during motor responses conditioned by robotic perturbations, which allows direct investigation of the neural correlates of LLRs.Via preliminary validation experiments, we demonstrate that our technique can reliably elicit and identify LLRs in two wrist muscles-Flexor Carpi Radialis and Extensor Carpi Ulnaris. Moreover, via a single-subject pilot experiment, we show that the occurrence of an LLR in a flexor and extensor muscles modulates neural activity in distinct regions of the brainstem. The observed somatotopic organization is in agreement with the double reciprocal model of RS function observed in animal models, in which the right medullary and left pontine reticular formation are responsible for control of the motor activity in flexors and extensors, respectively.

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.

Model-Based Analysis of the Stiffness of the Wrist Joint in Active and Passive Conditions.

The control of joint stiffness is a fundamental mechanism used to control human movements. While many studies have observed how stiffness is modulated for tasks involving shoulder and elbow motion, a limited amount of knowledge is available for wrist movements, though the wrist plays a crucial role in manipulation. We have developed a computational framework based on a realistic musculoskeletal model, which allows one to calculate the passive and active components of the wrist joint stiffness. We first used the framework to validate the musculoskeletal model against experimental measurements of the wrist joint stiffness, and then to study the contribution of different muscle groups to the passive joint stiffness. We finally used the framework to study the effect of muscle cocontraction on the active joint stiffness. The results show that thumb and finger muscles play a crucial role in determining the passive wrist joint stiffness: in the neutral posture, the direction of maximum stiffness aligns with the experimental measurements, and the magnitude increases by 113% when they are included. Moreover, the analysis of the controllability of joint stiffness showed that muscle cocontraction positively correlates with the stiffness magnitude and negatively correlates with the variability of the stiffness orientation (p < 0.01 in both cases). Finally, an exhaustive search showed that with appropriate selection of a muscle activation strategy, the joint stiffness orientation can be arbitrarily modulated. This observation suggests the absence of biomechanical constraints on the controllability of the orientation of the wrist joint stiffness.

Quantitative Testing of fMRI-Compatibility of an Electrically Active Mechatronic Device for Robot-Assisted Sensorimotor Protocols.

OBJECTIVE: To develop a quantitative set of methods for testing the functional magnetic resonance imaging (fMRI) compatibility of an electrically-active mechatronic device developed to support sensorimotor protocols during fMRI. METHODS: The set of methods includes phantom and in vivo experiments to measure the effect of a progressively broader set of noise sources potentially introduced by the device. Phantom experiments measure the radio-frequency (RF) noise and temporal noise-to-signal ratio (tNSR) introduced by the device. The in vivo experiment assesses the effect of the device on measured brain activation for a human subject performing a representative sensorimotor task. The proposed protocol was validated via experiments using a 3T MRI scanner operated under nominal conditions and with the inclusion of an electrically-active mechatronic device - the MR-SoftWrist - as the equipment under test (EUT). RESULTS: Quantitative analysis of RF noise data allows detection of active RF noise sources both in controlled RF noise conditions, and in conditions resembling improper filtering of the EUT's electrical signals. In conditions where no RF noise was detectable, the presence and operation of the EUT did not introduce any significant increase in tNSR. A quantitative analysis conducted on in vivo measurements of the number of active voxels in visual and motor areas further showed no significant difference between EUT and baseline conditions. CONCLUSION AND SIGNIFICANCE: The proposed set of quantitative methods supports the development and troubleshooting of electrically-active mechatronic devices for use in sensorimotor protocols with fMRI, and may be used for future testing of such devices.

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.

Effects of Assist-As-Needed Upper Extremity Robotic Therapy after Incomplete Spinal Cord Injury: A Parallel-Group Controlled Trial.

BACKGROUND: Robotic rehabilitation of the upper limb following neurological injury has been supported through several large clinical studies for individuals with chronic stroke. The application of robotic rehabilitation to the treatment of other neurological injuries is less developed, despite indications that strategies successful for restoration of motor capability following stroke may benefit individuals with incomplete spinal cord injury (SCI) as well. Although recent studies suggest that robot-aided rehabilitation might be beneficial after incomplete SCI, it is still unclear what type of robot-aided intervention contributes to motor recovery. METHODS: We developed a novel assist-as-needed (AAN) robotic controller to adjust challenge and robotic assistance continuously during rehabilitation therapy delivered via an upper extremity exoskeleton, the MAHI Exo-II, to train independent elbow and wrist joint movements. We further enrolled seventeen patients with incomplete spinal cord injury (AIS C and D levels) in a parallel-group balanced controlled trial to test the efficacy of the AAN controller, compared to a subject-triggered (ST) controller that does not adjust assistance or challenge levels continuously during therapy. The conducted study is a stage two, development-of-concept pilot study. RESULTS: We validated the AAN controller in its capability of modulating assistance and challenge during therapy via analysis of longitudinal robotic metrics. For the selected primary outcome measure, the pre-post difference in ARAT score, no statistically significant change was measured in either group of subjects. Ancillary analysis of secondary outcome measures obtained via robotic testing indicates gradual improvement in movement quality during the therapy program in both groups, with the AAN controller affording greater increases in movement quality over the ST controller. CONCLUSION: The present study demonstrates feasibility of subject-adaptive robotic therapy after incomplete spinal cord injury, but does not demonstrate gains in arm function occurring as a result of the robot-assisted rehabilitation program, nor differential gains obtained as a result of the developed AAN controller. Further research is warranted to better quantify the recovery potential provided by AAN control strategies for robotic rehabilitation of the upper limb following incomplete SCI. ClinicalTrials.gov registration number: NCT02803255.