The dominant limb preferentially stabilizes posture in a bimanual task with physical coupling.

Humans are endowed with an ability to skillfully handle objects, like when holding a jar with the nondominant hand while opening the lid with the dominant hand. Dynamic dominance, a prevailing theory in handedness research, proposes that the nondominant hand is specialized for postural stability, which would explain why right-handed people hold the jar steady using the left hand. However, the underlying specialization of the nondominant hand has only been tested unimanually, or in a bimanual task where the two hands had different functions. Using a dedicated dual-wrist robotic interface, we tested the dynamic dominance hypothesis in a bimanual task where both hands carry out the same function. We examined how left- and right-handed subjects held onto a vibrating virtual object using their wrists, which were physically coupled by the object. Muscular activity of the wrist flexors and extensors revealed a preference for cocontracting the dominant hand during both holding and transport of the object, which suggests proficiency in the dominant hand for stabilization, contradicting the dynamic dominance hypothesis. While the reliance on the dominant hand was partially explained by its greater strength, the Edinburgh inventory was a better predictor of the difference in the cocontraction between the dominant and nondominant hands. When provided with redundancy to stabilize the task, the dominant hand preferentially cocontracts to absorb perturbing forces.NEW & NOTEWORTHY We found that subjects prefer to stabilize a bimanually held object by cocontracting their dominant limb, contradicting the established view that the nondominant limb is specialized toward stabilization.

Reference Trajectory Adaptation to Improve Human-Robot Interaction: A Database-Driven Approach.

Many robotic devices that are used for therapy or as assistive devices rely on pre-defined reference trajectories to assist the user's movements. Fixed pre-defined trajectories force the user to adapt to unnatural movement patterns which may be detrimental to rehabilitation outcomes. We propose a database-driven approach to adapt the reference trajectory of robotic training devices that rely on cyclic motion such as walking. Dynamic time warping is used to compare the measured pattern with a database of pre-approved safe trajectories; the best matching pattern is selected from the database and used for the next movement sequence. The proposed approach was evaluated in computer simulations and a bioinspired robotic test bench. Our proposed method reduced the RMS error between individual user trajectories and the supplied reference, even in the presence of measurement noise.

Movement therapy without moving - First results on isometric movement training for post-stroke rehabilitation of arm function.

This study explores the use of isometric movement training for arm rehabilitation after stroke. The aim of this approach is to enhance movement skill even when the person training is not moving. This is accomplished by deceptively displaying virtual motions, exploiting known cross-modal sensory interactions between vision and proprioception. This approach can be advantageous in situations where actual movement is prohibitive due to weakness, spasticity, instability, or unsafe conditions. We present early insights on usability of and tolerance to this training approach and quantitative results that can power future clinical trials.

Interpersonal strategies for disturbance attenuation during a rhythmic joint motor action.

Helping someone carry a table is fairly easy; however, our understanding of such joint motor actions is still poorly understood. We studied how pairs of human subjects (referred to as dyads) collaborate physically to attenuate external mechanical perturbations during a target tracking task. Subjects tracked a target moving in a slow and predictable way using wrist flexion/extension movements, with and without destabilizing torque perturbations. Dyad strategies were classified using interaction torques and muscular activity. During unperturbed interactions (baseline), the dyads tended to stabilize on a particular strategy. The baseline strategy was not the same in all dyads, suggesting that the solution to the task was not global but specific to each particular dyad. After several trials of unperturbed interactions, we introduced mechanical vibrations and analyzed the adaptation process. Dyads showed a tendency to counteract the external disturbances by first increasing co-contraction within each subject (independent co-contraction), and then raising the amount of opposing interaction torques (dyadic co-contraction) with increased perturbation amplitude. The introduction of perturbations impelled dyads to abandon their unperturbed baseline strategy and adopt a more common strategy across dyads, suggesting attractor solutions. Our results establish a framework for future human-human interaction studies, and have implications in human motor control as well as human-robot and robot-robot interactions.

Motor adaptation with passive machines: a first study on the effect of real and virtual stiffness.

Motor adaptation to novel force fields is considered as a key mechanism not only for the understanding of skills learning in healthy subjects but also for rehabilitation of neurological subjects. Several studies conducted over the last two decades used active robotic manipulanda to generate force fields capable of perturbing the baseline trajectories of both healthy and impaired subjects. Recent studies showed how motor adaptation to novel force fields can be induced also via virtual environments, whereas the effects of the force are projected onto a virtual hand, while the real hand remains constrained within a channel. This has great potentials of being translated into passive devices, rather than robotic ones, with clear benefits in terms of costs and availability of the devices. However, passive devices and virtual environments have received much less attention at least with regard to motor adaptation. This paper investigates the effects of both the real and virtual stiffness on motor adaptation. In particular, we tested 20 healthy subjects under two different real stiffness conditions (Stiff Channel vs Compliant Channel) and two different virtual conditions (Viscous vs Springy). Our main finding is that compliance of the channel favours a better adaptation featured with less lateral errors and longer retention of the after-effect. We posit that the physical compliance of the channel induces a proprioceptive feedback which is otherwise absent in a stiff condition.

Upper limb functional assessment of children with cerebral palsy using a sorting box.

We investigated the use of a sorting box to obtain a quantitative assessment of upper limb motor function in children with cerebral palsy. In our study, children with and without cerebral palsy placed and removed geometrical objects of a sorting-box while their wrist position was monitored by a camera-based, motion-tracking system. We analyzed three different smoothness metrics (logarithmic dimensionless jerk, spectral arc-length and number of peaks) together with time to task completion. Our results suggest that smoothness metrics are an effective tool to distinguish between impaired and non-impaired subjects, as well as to quantify differences between the affected and less-affected sides in children with hemiparetic cerebral palsy.

Therapist recognition of impaired muscle groups in simulated multi-joint hypertonia.

It is common in today's clinical practice for a therapist to physically manipulate patients' limbs to assess hypertonic conditions (e.g. spasticity, rigidity, dystonia, among others). We present a study that evaluates the capabilities of expert therapists to correctly identify the location of a hypertonic impairment of an arm through standard manipulation. Therapists interacted with a hypertonic virtual arms rendered on a robotic device. Our results show that testing joints independently can cause misjudgment of the mechanical contributions of pluri-articular muscles to multi-joint impairment.

Haptic recognition of dystonia and spasticity in simulated multi-joint hypertonia.

This paper investigates the capability of naïve individuals to recognize dystonic- or spastic- like conditions through physical manipulation of a virtual arm. Subjects physically interact with a two-joint, six-muscle hypertonic arm model, rendered on a two degrees-of-freedom robotic manipulandum. This paradigm aims to identify the limitation of manual manipulation during diagnosis of hypertonia. Our results indicate that there are difficulties to discriminate between the two conditions at low to medium level of severity. We found that the sample entropy of the executed motion and the force experienced during physical manipulation, tended to be higher during incorrectly identified trials than in those correctly assessed.

Haptic perception of multi-joint hypertonia during simulated patient-therapist physical tele-interaction.

A potential solution to provide individualized physical therapy in remote areas is tele-interaction via robotic devices. To maintain stability during tele-interaction, transmission delay-compensation algorithms bound the impedance between the patient and the therapist. This can compromise the haptic perception of the patient being assessed, which can in turn lead to a bad diagnosis or intervention. We investigated how the perception of the severity of hypertonia (a common condition after neurological disorders) varied by modifying the connection impedance on a physical simulator. We found that assessing hypetonia using a low impedance connection may result in an overestimation of mild impairments.

An fMRI compatible wrist robotic interface to study brain development in neonates.

A comprehensive understanding of the mechanisms that underlie brain development in premature infants and newborns is crucial for the identification of interventional therapies and rehabilitative strategies. fMRI has the potential to identify such mechanisms, but standard techniques used in adults cannot be implemented in infant studies in a straightforward manner. We have developed an MR safe wrist stimulating robot to systematically investigate the functional brain activity related to both spontaneous and induced wrist movements in premature babies using fMRI. We present the technical aspects of this development and the results of validation experiments. Using the device, the cortical activity associated with both active and passive finger movements were reliably identified in a healthy adult subject. In two preterm infants, passive wrist movements induced a well localized positive BOLD response in the contralateral somatosensory cortex. Furthermore, in a single preterm infant, spontaneous wrist movements were found to be associated with an adjacent cluster of activity, at the level of the infant's primary motor cortex. The described device will allow detailed and objective fMRI studies of somatosensory and motor system development during early human life and following neonatal brain injury.

A robust and sensitive metric for quantifying movement smoothness.

The need for movement smoothness quantification to assess motor learning and recovery has resulted in various measures that look at different aspects of a movement's profile. This paper first shows that most of the previously published smoothness measures lack validity, consistency, sensitivity, or robustness. It then introduces and evaluates the spectral arc-length metric that uses a movement speed profile's Fourier magnitude spectrum to quantify movement smoothness. This new metric is systematically tested and compared to other smoothness metrics, using experimental data from stroke and healthy subjects as well as simulated movement data. The results indicate that the spectral arc-length metric is a valid and consistent measure of movement smoothness, which is both sensitive to modifications in motor behavior and robust to measurement noise. We hope that the systematic analysis of this paper is a step toward the standardization of the quantitative assessment of movement smoothness.

Classification of strategies for disturbance attenuation in human-human collaborative tasks.

Rigorous analyses of the mechanisms human-human physical interaction are only possible if corresponding means of systematically classifying dyad strategies are in place. Previous suggestions for classification of strategies neglect the high level of redundancy that is present when attenuation of external disturbances is required. To address this, we propose a quantitative classification system based on combined interaction force and EMG recordings of the flexion and extension activities of each partner in a given dyad.