Brain-computer interfacing is a technology that has the potential to improve patient engagement in robot-assisted rehabilitation therapy. Here we investigated how ERD changed as a function of audio-visual stimuli, overt movement from the participant, and robotic assistance.
Children with dystonia are characterized by highly variable and seemingly uncontrolled movements. An important question for any rehabilitative effort is whether these children can learn and improve their performance. This study compared children with dystonia due to cerebral palsy, typically developing children, and healthy adults in their ability to acquire a novel sensorimotor skill.
In this study, we present a novel multi-class brain-computer interface (BCI) system for communication and control. In this system, the information processing is shared by the algorithm (computer) and the user (human). Specifically, an electro-tactile cycle was presented to the user, providing the choice (class) by delivering timely sensory input.
Objective assessment of detailed gait patterns after orthopaedic surgery is important for post-surgical follow-up and rehabilitation. The purpose of this paper is to assess the use of a single ear-worn sensor for clinical gait analysis.
This paper studied the amplitude-frequency characteristic of frontal steady-state visual evoked potential (SSVEP) and its feasibility as a control signal for brain computer interface (BCI). SSVEPs induced by different stimulation frequencies, from 13 ~ 31 Hz in 2 Hz steps, were measured in eight young subjects, eight elders and seven ALS patients.
Currently, most externally powered prostheses are controlled using electromyography (or EMG), which is the measure of the electrical signals that are produced when voluntary muscle is contracted. One of the major problems is that there are a limited number of muscular control sites that can be used, which limits the complexity of the hands that are controllable.
Functional reaching is impaired in dystonia. Here, we analyze upper extremity kinematics to quantify timing and coordination abnormalities during unimanual reach-to-grasp movements in individuals with childhood-onset unilateral wrist dystonia.
Lower limb amputees can use electrical activity from their residual muscles for myoelectric control of a powered prosthesis. The most common approach for myoelectric control is a finite state controller that identifies behavioral states and discrete changes in motor tasks.
This paper describes a control approach that provides walking and standing functionality for a powered ankle prosthesis, and demonstrates the efficacy of the approach in experiments with a unilateral transtibial amputee subject. Both controllers incorporate a finite-state structure that emulates healthy ankle joint behavior via a series of piecewise passive impedance functions.
This paper aimed to develop and evaluate an environment- aware locomotion mode recognition system for volitional control of powered artificial legs. A portable terrain recognition (TR) module, consisting of an inertia measurement unit and a laser distance meter, was built to identify the type of terrain in front of the wearer while walking. A decision tree was used to classify the terrain types and provide either coarse or refined information about the walking environment.