The condition for dynamic stability in humans walking with feedback control.

The walking human body is mechanically unstable. Loss of stability and falling is more likely in certain groups of people, such as older adults or people with neuromotor impairments, as well as in certain situations, such as when experiencing conflicting or distracting sensory inputs. Stability during walking is often characterized biomechanically, by measures based on body dynamics and the base of support. Neural control of upright stability, on the other hand, does not factor into commonly used stability measures. Here we analyze stability of human walking accounting for both biomechanics and neural control, using a modeling approach. We define a walking system as a combination of biomechanics, using the well known inverted pendulum model, and neural control, using a proportional-derivative controller for foot placement based on the state of the center of mass at midstance. We analyze this system formally and show that for any choice of system parameters there is always one periodic orbit. We then determine when this periodic orbit is stable, i.e. how the neural control gain values have to be chosen for stable walking. Following the formal analysis, we use this model to make predictions about neural control gains and compare these predictions with the literature and existing experimental data. The model predicts that control gains should increase with decreasing cadence. This finding appears in agreement with literature showing stronger effects of visual or vestibular manipulations at different walking speeds.

Visual motion detection thresholds can be reliably measured during walking and standing.

Introduction: In upright standing and walking, the motion of the body relative to the environment is estimated from a combination of visual, vestibular, and somatosensory cues. Associations between vestibular or somatosensory impairments and balance problems are well established, but less is known whether visual motion detection thresholds affect upright balance control. Typically, visual motion threshold values are measured while sitting, with the head fixated to eliminate self-motion. In this study we investigated whether visual motion detection thresholds: (1) can be reliably measured during standing and walking in the presence of natural self-motion; and (2) differ during standing and walking. Methods: Twenty-nine subjects stood on and walked on a self-paced, instrumented treadmill inside a virtual visual environment projected on a large dome. Participants performed a two-alternative forced choice experiment in which they discriminated between a counterclockwise ("left") and clockwise ("right") rotation of a visual scene. A 6-down 1-up adaptive staircase algorithm was implemented to change the amplitude of the rotation. A psychometric fit to the participants' binary responses provided an estimate for the detection threshold. Results: We found strong correlations between the repeated measurements in both the walking (R = 0.84, p < 0.001) and the standing condition (R = 0.73, p < 0.001) as well as good agreement between the repeated measures with Bland-Altman plots. Average thresholds during walking (mean = 1.04°, SD = 0.43°) were significantly higher than during standing (mean = 0.73°, SD = 0.47°). Conclusion: Visual motion detection thresholds can be reliably measured during both walking and standing, and thresholds are higher during walking.

Subthreshold electrical noise alters walking balance control in individuals with cerebral palsy.

BACKGROUND: Sensory deficits in individuals with cerebral palsy (CP) play a critical role in balance control. However, there is a lack of effective interventions that address sensory facilitation to improve walking balance. Stochastic Resonance (SR) stimulation involves delivering sub threshold noise to improve balance in patients with sensory deficits by enhancing the detection of sensory input. RESEARCH QUESTION: To investigate the immediate effects of SR on walking balance in individuals with and without CP. METHODS: Thirty-four participants (17 CP, 17 age-and sex-matched typically developing controls or TD) between 8 and 24 years of age were recruited. SR stimulation was applied to the muscles and ligaments of ankle and hip joint. An optimal SR intensity during walking was determined for each subject. Participants walked on a self-paced treadmill for three trials of two minutes each using a random order of SR stimulation (SR) and no stimulation (noSR) control conditions. Our primary outcome measure was minimum lateral margin of stability (MOS). Secondary outcome measures include anterior MOS before heelstrike and spatiotemporal gait parameters. We performed two-way mixed ANOVAs with group (CP, TD) as between-subject and condition (noSR, SR) as within subject factors. RESULTS: Compared to walking without SR, there was a small but significant increase in the lateral and anterior MOS with SR stimulation, implying that a larger impulse was needed to become unstable, in turn implying higher stability. Step width and step ength decreased with SR for the CP group with SR stimulation. There were no significant effects for other spatiotemporal variables. SIGNIFICANCE: Sub threshold electrical noise can slightly improve walking balance control in individuals with CP. SR stimulation, through enhanced proprioception, may have improved the CP group's awareness of body motion during walking, thus leading them to adopt a more conservative stability strategy to prevent a potential fall.

A novel method to quantify individual limb contributions to standing postural control.

BACKGROUND: Understanding individual limb contributions to standing postural control is valuable when evaluating populations with asymmetric function (e.g., stroke, amputations). We propose a method of quantifying three contributions to controlling the net anteroposterior center of pressure (CoP) during quiet standing: CoP moving under left and right limbs and weight shifting between the two limbs. RESEARCH QUESTION: Can these contributions to standing postural control be quantified from CoP trajectories in neurotypical adults? METHODS: Instantaneous contributions can be negative or larger than one, and integrated contributions sum to equal one. Proof-of-concept demonstrations validated these calculated contributions by restricting CoP motion under one or both feet. We evaluated these contributions in 30 neurotypical young adults who completed two (eyes opened; eyes closed) 30-s trials of bipedal standing. We evaluated the relationships between limb contributions, self-reported limb dominance, and between-limb weight distributions. RESULTS: All participants self-reported as right-limb dominant; however, a range of mean limb contributions were observed with eyes opened (Left: mean [range] = 0.52 [0.37-0.63]; Right: 0.48 [0.31-0.63]) and with eyes closed (Left: 0.51 [0.39-0.63]; Right: 0.49 [0.37-0.61]). Weight-shift contributions were small with eyes opened (0.00 [-0.01 to 0.01]) and eyes closed (0.00 [-0.01 to 0.02]). We did not identify any between-limb differences in contributions when grouped by self-reported limb dominance (p > 0.10, d < 0.31). Contributions did not significantly correlate with Waterloo Footedness scores (-0.22 < r < 0.21, p > 0.25) or between-limb weight distributions (0 < r < 0.24, p > 0.20). SIGNIFICANCE: Across neurotypical participants, we observed a notable range of limb contributions not related to self-reported limb dominance or between-limb weight distributions. With this tool, we can characterize differences in the amount of CoP motion and the underlying control strategies. Changes in limb contribution can be measured longitudinally (i.e., across rehabilitation programs, disease progression, aging) representative of limb function, which may be particularly useful in populations with asymmetric function.

High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model.

Humans can freely adopt gait parameters like walking speed, step length, or cadence on the fly when walking. Planned movement that can be updated online to account for changes in the environment rather than having to rely on habitual, reflexive control that is adapted over long timescales. Here we present a neuromechanical model that accounts for this flexibility by combining movement goals and motor plans on a kinematic task level with low-level spinal feedback loops. We show that the model can walk at a wide range of different gait patterns by choosing a small number of high-level control parameters representing a movement goal. A larger number of parameters governing the low-level reflex loops in the spinal cord, on the other hand, remain fixed. We also show that the model can generalize the learned behavior by recombining the high-level control parameters and walk with gait patterns that it had not encountered before. Furthermore, the model can transition between different gaits without the loss of balance by switching to a new set of control parameters in real time.

Individuals with cerebral palsy show altered responses to visual perturbations during walking.

Individuals with cerebral palsy (CP) have deficits in processing of somatosensory and proprioceptive information. To compensate for these deficits, they tend to rely on vision over proprioception in single plane upper and lower limb movements and in standing. It is not known whether this also applies to walking, an activity where the threat to balance is higher. Through this study, we used visual perturbations to understand how individuals with and without CP integrate visual input for walking balance control. Additionally, we probed the balance mechanisms driving the responses to the visual perturbations. More specifically, we investigated differences in the use of ankle roll response i.e., the use of ankle inversion, and the foot placement response, i.e., stepping in the direction of perceived fall. Thirty-four participants (17 CP, 17 age-and sex-matched typically developing controls or TD) were recruited. Participants walked on a self-paced treadmill in a virtual reality environment. Intermittently, the virtual scene was rotated in the frontal plane to induce the sensation of a sideways fall. Our results showed that compared to their TD peers, the overall body sway in response to the visual perturbations was magnified and delayed in CP group, implying that they were more affected by changes in visual cues and relied more so on visual information for walking balance control. Also, the CP group showed a lack of ankle response, through a significantly reduced ankle inversion on the affected side compared to the TD group. The CP group showed a higher foot placement response compared to the TD group immediately following the visual perturbations. Thus, individuals with CP showed a dominant proximal foot placement strategy and diminished ankle roll response, suggestive of a reliance on proximal over distal control of walking balance in individuals with CP.

A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements.

Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

Age differences in adaptation of medial-lateral gait parameters during split-belt treadmill walking.

The split-belt treadmill has been used to examine the adaptation of spatial and temporal gait parameters. Historically, similar studies have focused on anterior-posterior (AP) spatiotemporal gait parameters because this paradigm is primarily a perturbation in the AP direction, but it is important to understand whether and how medial-lateral (ML) control adapts in this scenario. The ML control of balance must be actively controlled and adapted in different walking environments. Furthermore, it is well established that older adults have balance difficulties. Therefore, we seek to determine whether ML balance adaptation differs in older age. We analyzed split belt induced changes in gait parameters including variables which inform us about ML balance control in younger and older adults. Our primary finding is that younger adults showed sustained asymmetric changes in these ML balance parameters during the split condition. Specifically, younger adults sustained a greater displacement between their fast stance foot and their upper body, relative to the slow stance foot, in the ML direction. This finding suggests that younger adults may be exploiting passive dynamics in the ML direction, which may be more metabolically efficient. Older adults did not display the same degree of asymmetry, suggesting older adults may be more concerned about maintaining a stable gait.

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.

Interdependence of balance mechanisms during bipedal locomotion.

Our main interest is to identify how humans maintain upright while walking. Balance during standing and walking is different, primarily due to a gait cycle which the nervous system must contend with a variety of body configurations and frequent perturbations (i.e., heel-strike). We have identified three mechanisms that healthy young adults use to respond to a visually perceived fall to the side. The lateral ankle mechanism and the foot placement mechanism are used to shift the center of pressure in the direction of the perceived fall, and the center of mass away from the perceived fall. The push-off mechanism, a systematic change in ankle plantarflexion angle in the trailing leg, results in fine adjustments to medial-lateral balance near the end of double stance. The focus here is to understand how the three basic balance mechanisms are coordinated to produce an overall balance response. The results indicate that lateral ankle and foot placement mechanisms are inversely related. Larger lateral ankle responses lead to smaller foot placement changes. Correlations involving the push-off mechanism, while significant, were weak. However, the consistency of the correlations across stimulus conditions suggest the push-off mechanism has the role of small adjustments to medial-lateral movement near the end of the balance response. This verifies that a fundamental feature of human bipedal gait is a highly flexible balance system that recruits and coordinates multiple mechanisms to maintain upright balance during walking to accommodate extreme changes in body configuration and frequent perturbations.

A process account of the uncontrolled manifold structure of joint space variance in pointing movements.

In many situations, the human movement system has more degrees of freedom than needed to achieve a given movement task. Martin et al. (Neural Comput 21(5):1371-1414, 2009) accounted for signatures of such redundancy like self-motion and motor equivalence in a process model in which a neural oscillator generated timed end-effector virtual trajectories that a neural dynamics transformed into joint virtual trajectories while decoupling task-relevant and task-irrelevant combinations of joint angles. Neural control of muscle activation and the biomechanical dynamics of the arm were taken into account. The model did not address the main signature of redundancy, however, the UCM structure of variance: Many experimental studies have shown that across repetitions, variance of joint configuration trajectories is structured. Combinations of joint angles that affect task variables (lying in the uncontrolled manifold, UCM) are much more variable than combinations of joint angles that do not. This finding has been robust across movement systems, age, and tasks and is often preserved in clinical populations as well. Here, we provide an account for the UCM structure of variance by adding four types of noise sources to the model of Martin et al. (Neural Comput 21(5):1371-1414, 2009). Comparing the model to human pointing movements and systematically examining the role of each noise source and mechanism, we identify three causes of the UCM effect, all of which, we argue, contribute: (1) the decoupling of motor commands across the task-relevant and task-irrelevant subspaces together with "neural" noise at the level of these motor commands; (2) "muscle noise" combined with imperfect control of the limb; (3) back-coupling of sensed joint configurations into the motor commands which then yield to the sensed joint configuration within the UCM.

Phase-Dependency of Medial-Lateral Balance Responses to Sensory Perturbations During Walking.

The human body is mechanically unstable during walking. Maintaining upright stability requires constant regulation of muscle force by the central nervous system to push against the ground and move the body mass in the desired way. Activation of muscles in the lower body in response to sensory or mechanical perturbations during walking is usually highly phase-dependent, because the effect any specific muscle force has on the body movement depends upon the body configuration. Yet the resulting movement patterns of the upper body after the same perturbations are largely phase-independent. This is puzzling, because any change of upper-body movement must be generated by parts of the lower body pushing against the ground. How do phase-dependent muscle activation patterns along the lower body generate phase-independent movement patterns of the upper body? We hypothesize that when a sensory system detects a deviation of the body in space from a desired state that indicates the onset of a fall, the nervous system generates a functional response by pushing against the ground in any way possible with the current body configuration. This predicts that the changes in the ground reaction force patterns following a balance perturbation should be phase-independent. Here we test this hypothesis by disturbing upright balance in the frontal plane using Galvanic vestibular stimulation at three different points in the gait cycle. We measure the resulting changes in whole-body center of mass movement and the location of the center of pressure of the ground reaction force. We find that the magnitude of the initial center of pressure shift in the direction of the perceived fall is larger for perturbations late in the gait cycle, while there is no statistically significant difference in onset time. These results contradict our hypothesis by showing that even the initial CoP shift in response to a balance perturbation depends upon the phase of the gait cycle. Contrary to expectation, we also find that the whole-body balance response is not phase-independent. Both the onset time and the magnitude of the whole-body center of mass shift depend on the phase of the perturbation. We conclude that the central nervous system recruits any available mechanism to generate a functional balance response by pushing against the ground as fast as possible in response to a perturbation, but that the different mechanisms available at different phases in the gait cycle are not equally strong, leading to phase-dependent differences in the overall response.

Walking Cadence Affects the Recruitment of the Medial-Lateral Balance Mechanisms.

We have previously identified three balance mechanisms that young healthy adults use to maintain balance while walking. The three mechanisms are: (1) The lateral ankle mechanism, an active modulation of ankle inversion/eversion in stance; (2) The foot placement mechanism, an active shift of the swing foot placement; and (3) The push-off mechanism, an active modulation of the ankle plantarflexion angle during double stance. Here we seek to determine whether there are changes in neural control of balance when walking at different cadences and speeds. Twenty-one healthy young adults walked on a self-paced treadmill while immersed in a 3D virtual reality cave, and periodically received balance perturbations (bipolar galvanic vestibular stimulation) eliciting a perceived fall to the side. Subjects were instructed to match two cadences specified by a metronome, 110 bpm (High) and 80 bpm (Low), which in this experiment, led to faster and slower gait speeds, respectively. The results indicate that subjects altered the use of the balance mechanisms at different cadences. The lateral ankle mechanism was used more in the Low condition, while the foot placement mechanism was used more in the High condition. There was no difference in the use of the push-off mechanism between cadence conditions. These results suggest that neural control of balance is altered when gait characteristics, such as cadence change, suggesting a flexible balance response that is sensitive to the constraints of the gait cycle. We speculate that the use of the balance mechanisms may be a factor resulting in well-known characteristics of gait in populations with compromised balance control, such as slower gait speed in older adults or higher cadence in people with Parkinson's disease.

Neural Control of Balance During Walking.

Neural control of standing balance has been extensively studied. However, most falls occur during walking rather than standing, and findings from standing balance research do not necessarily carry over to walking. This is primarily due to the constraints of the gait cycle: Body configuration changes dramatically over the gait cycle, necessitating different responses as this configuration changes. Notably, certain responses can only be initiated at specific points in the gait cycle, leading to onset times ranging from 350 to 600 ms, much longer than what is observed during standing (50-200 ms). Here, we investigated the neural control of upright balance during walking. Specifically, how the brain transforms sensory information related to upright balance into corrective motor responses. We used visual disturbances of 20 healthy young subjects walking in a virtual reality cave to induce the perception of a fall to the side and analyzed the muscular responses, changes in ground reaction forces and body kinematics. Our results showed changes in swing leg foot placement and stance leg ankle roll that accelerate the body in the direction opposite of the visually induced fall stimulus, consistent with previous results. Surprisingly, ankle musculature activity changed rapidly in response to the stimulus, suggesting the presence of a direct reflexive pathway from the visual system to the spinal cord, similar to the vestibulospinal pathway. We also observed systematic modulation of the ankle push-off, indicating the discovery of a previously unobserved balance mechanism. Such modulation has implications not only for balance but plays a role in modulation of step width and length as well as cadence. These results indicated a temporally-coordinated series of balance responses over the gait cycle that insures flexible control of upright balance during walking.

Anticipatory coarticulation in non-speeded arm movements can be motor-equivalent, carry-over coarticulation always is.

In a sequence of arm movements, any given segment could be influenced by its predecessors (carry-over coarticulation) and by its successor (anticipatory coarticulation). To study the interdependence of movement segments, we asked participants to move an object from an initial position to a first and then on to a second target location. The task involved ten joint angles controlling the three-dimensional spatial path of the object and hand. We applied the principle of the uncontrolled manifold (UCM) to analyze the difference between joint trajectories that either affect (non-motor equivalent) or do not affect (motor equivalent) the hand's trajectory in space. We found evidence for anticipatory coarticulation that was distributed equally in the two directions in joint space. We also found strong carry-over coarticulation, which showed clear structure in joint space: More of the difference between joint configurations observed for different preceding movements lies in directions in joint space that leaves the hand's path in space invariant than in orthogonal directions in joint space that varies the hand's path in space. We argue that the findings are consistent with anticipatory coarticulation reflecting processes of movement planning that lie at the level of the hand's trajectory in space. Carry-over coarticulation may reflect primarily processes of motor control that are governed by the principle of the UCM, according to which changes that do not affect the hand's trajectory in space are not actively delimited. Two follow-up experiments zoomed in on anticipatory coarticulation. These experiments strengthened evidence for anticipatory coarticulation. Anticipatory coarticulation was motor-equivalent when visual information supported the steering of the object to its first target, but was not motor equivalent when that information was removed. The experiments showed that visual updating of the hand's path in space when the object approaches the first target only affected the component of the joint difference vector orthogonal to the UCM, consistent with the UCM principle.

A multi-joint model of quiet, upright stance accounts for the "uncontrolled manifold" structure of joint variance.

The upright body in quiet stance is usually modeled as a single-link inverted pendulum. This agrees with most of the relevant sensory organs being at the far end of the pendulum, i.e., the eyes and the vestibular system in the head. Movement of the body in quiet stance has often been explained in terms of the "ankle strategy," where most movement is generated by the ankle musculature, while more proximal muscle groups are only rarely activated for faster movements or in response to perturbations, for instance, by flexing at the hips in what has been called the "hip strategy." Recent empirical evidence, however, shows that instead of being negligible in quiet stance, the movement in the knee and hip joints is even larger on average than the movement in the ankle joints (J Neurophysiol 97:3024-3035, 2007). Moreover, there is a strong pattern of covariation between movements in the ankle, knee and hip joints in a way that most of the observed movements leave the anterior-posterior position of the whole-body center of mass (CoM) invariant, i.e., only change the configuration of the different body parts around the CoM, instead of moving the body as a whole. It is unknown, however, where this covariation between joint angles during quiet stance originates from. In this paper, we aim to answer this question using a comprehensive model of the biomechanical, muscular and neural dynamics of a quietly standing human. We explore four different possible feedback laws for the control of this multi-link pendulum in upright stance that map sensory data to motor commands. We perform simulation studies to compare the generated inter-joint covariance patterns with experimental data. We find that control laws that actively coordinate muscle activation between the different joints generate correct variance patterns, while control laws that control each joint separately do not. Different specific forms of this coordination are compatible with the data.

Infant intralimb coordination and torque production: Influence of prematurity.

The purpose of this study is to investigate changes in leg joint coordination, intersegmental dynamics, and their relation in infants born preterm (PT) during the first months of life. Kicking actions were analyzed of 11 infants born PT at 6 and 15-weeks corrected age (CA) using three-dimensional kinematics and kinetics; results were compared to the kicking actions of 10 infants born full-term (FT). Both groups changed from a predominately in-phase coordination at 6-weeks CA to a less in-phase coordination at 15-weeks CA, however, at 6-weeks CA, infants born PT demonstrated less in-phase coordination of their ankle joints with their hip and knee joints. Between groups and across ages, both groups demonstrated consistent net and partitioned joint torque profiles, however, at 6-weeks CA infants born PT demonstrated more complex patterns of torque components. In both groups, less in-phase hip-knee coordination was associated with reduced active knee muscle torque and increased passive knee torques, however, passive knee torques had a greater influence on the kicks of infants born PT at 6-weeks CA. At 6-weeks CA, infants born PT, compared to FT, generated kicks with less in-phase hip-knee coordination, hip excursion, hip angular velocity, and hip muscle torque impulse. By 15-weeks CA, differences resolved in all variables except hip muscle torque impulse. These results highlight a different trajectory of leg joint coordination and torque production for infants born PT compared to FT.

Spatiotemporal gait changes with use of an arm swing cueing device in people with Parkinson's disease.

Impaired arm swing is a common motor symptom of Parkinson's disease (PD), and correlates with other gait impairments and increased risk of falls. Studies suggest that arm swing is not merely a passive consequence of trunk rotation during walking, but an active component of gait. Thus, techniques to enhance arm swing may improve gait characteristics. There is currently no portable device to measure arm swing and deliver immediate cues for larger movement. Here we test report pilot testing of such a device, ArmSense (patented), using a crossover repeated-measures design. Twelve people with PD walked in a video-recorded gym space at self-selected comfortable and fast speeds. After baseline, cues were given either visually using taped targets on the floor to increase step length or through vibrations at the wrist using ArmSense to increase arm swing amplitude. Uncued walking then followed, to assess retention. Subjects successfully reached cueing targets on >95% of steps. At a comfortable pace, step length increased during both visual cueing and ArmSense cueing. However, we observed increased medial-lateral trunk sway with visual cueing, possibly suggesting decreased gait stability. In contrast, no statistically significant changes in trunk sway were observed with ArmSense cues compared to baseline walking. At a fast pace, changes in gait parameters were less systematic. Even though ArmSense cues only specified changes in arm swing amplitude, we observed changes in multiple gait parameters, reflecting the active role arm swing plays in gait and suggesting a new therapeutic path to improve mobility in people with PD.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.