Children show limited movement repertoire when learning a novel motor skill.

Examining age differences in motor learning using real-world tasks is often problematic due to task novelty and biomechanical confounds. Here, we investigated how children and adults acquire a novel motor skill in a virtual environment. Participants of three different age groups (9-year-olds, 12-year-olds, and adults) learned to use their upper body movements to control a cursor on a computer screen. Results showed that 9-year-old and 12-year-old children showed poorer ability to control the cursor at the end of practice. Critically, when we investigated the movement coordination, we found that the lower task performance of children was associated with limited exploration of their movement repertoire. These results reveal the critical role of motor exploration in understanding developmental differences in motor learning.

Learning new movements after paralysis: Results from a home-based study.

Body-machine interfaces (BMIs) decode upper-body motion for operating devices, such as computers and wheelchairs. We developed a low-cost portable BMI for survivors of cervical spinal cord injury and investigated it as a means to support personalized assistance and therapy within the home environment. Depending on the specific impairment of each participant, we modified the interface gains to restore a higher level of upper body mobility. The use of the BMI over one month led to increased range of motion and force at the shoulders in chronic survivors. Concurrently, subjects learned to reorganize their body motions as they practiced the control of a computer cursor to perform different tasks and games. The BMI allowed subjects to generate any movement of the cursor with different motions of their body. Through practice subjects demonstrated a tendency to increase the similarity between the body motions used to control the cursor in distinct tasks. Nevertheless, by the end of learning, some significant and persistent differences appeared to persist. This suggests the ability of the central nervous system to concurrently learn operating the BMI while exploiting the possibility to adapt the available mobility to the specific spatio-temporal requirements of each task.

Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept.

This study tested the use of a customized body-machine interface (BoMI) for enhancing functional capabilities in persons with cervical spinal cord injury (cSCI). The interface allows people with cSCI to operate external devices by reorganizing their residual movements. This was a proof-of-concept phase 0 interventional nonrandomized clinical trial. Eight cSCI participants wore a custom-made garment with motion sensors placed on the shoulders. Signals derived from the sensors controlled a computer cursor. A standard algorithm extracted the combinations of sensor signals that best captured each participant's capacity for controlling a computer cursor. Participants practiced with the BoMI for 24 sessions over 12 weeks performing 3 tasks: reaching, typing, and game playing. Learning and performance were evaluated by the evolution of movement time, errors, smoothness, and performance metrics specific to each task. Through practice, participants were able to reduce the movement time and the distance from the target at the 1-second mark in the reaching task. They also made straighter and smoother movements while reaching to different targets. All participants became faster in the typing task and more skilled in game playing, as the pong hit rate increased significantly with practice. The results provide proof-of-concept for the customized BoMI as a means for people with absent or severely impaired hand movements to control assistive devices that otherwise would be manually operated.

Static Versus Dynamic Decoding Algorithms in a Non-Invasive Body-Machine Interface.

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on six subjects with high-level SCI and eight controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI's continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use.

Body-Machine Interfaces after Spinal Cord Injury: Rehabilitation and Brain Plasticity.

The purpose of this study was to identify rehabilitative effects and changes in white matter microstructure in people with high-level spinal cord injury following bilateral upper-extremity motor skill training. Five subjects with high-level (C5-C6) spinal cord injury (SCI) performed five visuo-spatial motor training tasks over 12 sessions (2-3 sessions per week). Subjects controlled a two-dimensional cursor with bilateral simultaneous movements of the shoulders using a non-invasive inertial measurement unit-based body-machine interface. Subjects' upper-body ability was evaluated before the start, in the middle and a day after the completion of training. MR imaging data were acquired before the start and within two days of the completion of training. Subjects learned to use upper-body movements that survived the injury to control the body-machine interface and improved their performance with practice. Motor training increased Manual Muscle Test scores and the isometric force of subjects' shoulders and upper arms. Moreover, motor training increased fractional anisotropy (FA) values in the cingulum of the left hemisphere by 6.02% on average, indicating localized white matter microstructure changes induced by activity-dependent modulation of axon diameter, myelin thickness or axon number. This body-machine interface may serve as a platform to develop a new generation of assistive-rehabilitative devices that promote the use of, and that re-strengthen, the motor and sensory functions that survived the injury.

Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation.

The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.

Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user's residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional control commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control a power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control.

Remapping residual coordination for controlling assistive devices and recovering motor functions.

The concept of human motor redundancy attracted much attention since the early studies of motor control, as it highlights the ability of the motor system to generate a great variety of movements to achieve any well-defined goal. The abundance of degrees of freedom in the human body may be a fundamental resource in the learning and remapping problems that are encountered in human-machine interfaces (HMIs) developments. The HMI can act at different levels decoding brain signals or body signals to control an external device. The transformation from neural signals to device commands is the core of research on brain-machine interfaces (BMIs). However, while BMIs bypass completely the final path of the motor system, body-machine interfaces (BoMIs) take advantage of motor skills that are still available to the user and have the potential to enhance these skills through their consistent use. BoMIs empower people with severe motor disabilities with the possibility to control external devices, and they concurrently offer the opportunity to focus on achieving rehabilitative goals. In this study we describe a theoretical paradigm for the use of a BoMI in rehabilitation. The proposed BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer screen. This mapping is obtained by principal component analysis (PCA). We hypothesize that the BoMI can be specifically programmed to engage the users in functional exercises aimed at partial recovery of motor skills, while simultaneously controlling the cursor and carrying out functional tasks, e.g. playing games. Specifically, PCA allows us to select not only the subspace that is most comfortable for the user to act upon, but also the degrees of freedom and coordination patterns that the user has more difficulty engaging. In this article, we describe a family of map modifications that can be made to change the motor behavior of the user. Depending on the characteristics of the impairment of each high-level spinal cord injury (SCI) survivor, we can make modifications to restore a higher level of symmetric mobility (left versus right), or to increase the strength and range of motion of the upper body that was spared by the injury. Results showed that this approach restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom in the participants involved in the control of the interface. This is a proof of concept that our BoMI may be used concurrently to control assistive devices and reach specific rehabilitative goals. Engaging the users in functional and entertaining tasks while practicing the interface and changing the map in the proposed ways is a novel approach to rehabilitation treatments facilitated by portable and low-cost technologies.

Adaptation to visual feedback delay in a redundant motor task.

The goal of this study was to examine the reorganization of hand movements during adaptation to delayed visual feedback in a novel and redundant environment. In most natural behaviors, the brain must learn to invert a many-to-one map from high-dimensional joint movements and muscle forces to a low-dimensional goal. This spatial "inverse map" is learned by associating motor commands to their low-dimensional consequences. How is this map affected by the presence of temporal delays? A delay presents the brain with a new set of kinematic data, and, because of redundancy, the brain may use these data to form a new inverse map. We consider two possible responses to a novel visuomotor delay. In one case, the brain updates the previously learned spatial map, building a new association between motor commands and visual feedback of their effects. In the alternative case, the brain preserves the original map and learns to compensate the delay by a temporal shift of the motor commands. To test these alternative possibilities, we developed a virtual reality game in which subjects controlled the two-dimensional coordinates of a cursor by continuous hand gestures. Two groups of subjects tracked a target along predictable paths by wearing an instrumented data glove that recorded finger motions. The 19-dimensional glove signals controlled a cursor on a 2-dimensional computer display. The experiment was performed on 2 consecutive days. On the 1st day, subjects practiced tracking movements without delay. On the 2nd day, the test group performed the same task with a delay of 300 ms between the glove signals and the cursor display, whereas the control group continued practicing the nondelayed trials. We found evidence that to compensate for the delay, the test group relied on the coordination patterns established during the baseline, e.g., their hand-to-cursor inverse map was robust to the delay perturbation, which was counteracted by an anticipation of the motor command.

Assistive Robotic Manipulation through Shared Autonomy and a Body-Machine Interface.

Assistive robotic manipulators have the potential to improve the lives of people with motor impairments. They can enable individuals to perform activities such as pick-and-place tasks, opening doors, pushing buttons, and can even provide assistance in personal hygiene and feeding. However, robotic arms often have more degrees of freedom (DoF) than the dimensionality of their control interface, making them challenging to use-especially for those with impaired motor abilities. Our research focuses on enabling the control of high-DoF manipulators to motor-impaired individuals for performing daily tasks. We make use of an individual's residual motion capabilities, captured through a Body-Machine Interface (BMI), to generate control signals for the robotic arm. These low-dimensional controls are then utilized in a shared-control framework that shares control between the human user and robot autonomy. We evaluated the system by conducting a user study in which 6 participants performed 144 trials of a manipulation task using the BMI interface and the proposed shared-control framework. The 100% success rate on task performance demonstrates the effectiveness of the proposed system for individuals with motor impairments to control assistive robotic manipulators.

Body machine interfaces for neuromotor rehabilitation: a case study.

High-level spinal cord injury (SCI) survivors face every day two related problems: recovering motor skills and regaining functional independence. Body machine interfaces (BoMIs) empower people with sever motor disabilities with the ability to control an external device, but they also offer the opportunity to focus concurrently on achieving rehabilitative goals. In this study we developed a portable, and low-cost BoMI that addresses both problems. The BoMI remaps the user's residual upper body mobility to the two coordinates of a cursor on a computer monitor. By controlling the cursor, the user can perform functional tasks, such as entering text and playing games. This framework also allows the mapping between the body and the cursor space to be modified, gradually challenging the user to exercise more impaired movements. With this approach, we were able to change the behavior of our SCI subject, who initially used almost exclusively his less impaired degrees of freedom - on the left side - for controlling the BoMI. At the end of the few practice sessions he had restored symmetry between left and right side of the body, with an increase of mobility and strength of all the degrees of freedom involved in the control of the interface. This is the first proof of concept that our BoMI can be used to control assistive devices and reach specific rehabilitative goals simultaneously.

A body machine interface based on inertial sensors.

Spinal cord injury (SCI) survivors generally retain residual motor and sensory functions, which provide them with the means to control assistive devices. A body-machine interface (BoMI) establishes a mapping from these residual body movements to control commands for an external device. In this study, we designed a BoMI to smooth the way for operating computers, powered wheelchairs and other assistive technologies after cervical spinal cord injuries. The interface design included a comprehensive training paradigm with a range of diverse functional activities to enhance motor learning and retention. Two groups of SCI survivors and healthy control subjects participated in the study. The results indicate the effectiveness of the developed system as an alternative pathway for individuals with motor disabilities to control assistive devices while engaging in functional motor activity.