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.

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.

Using noise to shape motor learning.

Unlabelled: Each of our movements is selected from any number of alternative movements. Some studies have shown evidence that the central nervous system (CNS) chooses to make the specific movements that are least affected by motor noise. Previous results showing that the CNS has a natural tendency to minimize the effects of noise make the direct prediction that if the relationship between movements and noise were to change, the specific movements people learn to make would also change in a predictable manner.

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.

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.

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.

Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

The purpose of this study was to determine the effect of the addition of binary vibrotactile stimulation to continuous auditory feedback (vowel synthesis) for human-machine interface (HMI) control. Sixteen healthy participants controlled facial surface electromyography to achieve 2-D targets (vowels). Eight participants used only real-time auditory feedback to locate targets whereas the other eight participants were additionally alerted to having achieved targets with confirmatory vibrotactile stimulation at the index finger.

Comparison of nasal acceleration and nasalance across vowels.

Purpose: The purpose of this study was to determine the performance of normalized nasal acceleration (NNA) relative to nasalance as estimates of nasalized versus nonnasalized vowel and sentence productions.

Method: Participants were 18 healthy speakers of American English. NNA was measured using a custom sensor, and nasalance was measured using the KayPentax Nasometer II.

Normalization strategies for nasal acceleration to assess velopharyngeal function.

Velopharyngeal function is essential for intelligible speech production, but can often be impaired. Current clinical care could be improved with the use of reliable and objective methods of assessment appropriate for home use. This paper explores the use of a combined nasal acceleration and acoustic sensor to assess velopharyngeal function.