Rupert Ortner

Accuracy of a P300 Speller for People with Motor Impairments: a Comparison

A Brain-Computer Interface (BCI) provides a completely new output pathway that can provide an additional option for a person to express himself/her self if he/she suffers a disorder like amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury or other diseases which impair the function of the common output pathways which are responsible for the control of muscles. For a P300 based BCI a matrix of randomly flashing characters is presented to the participant. To spell a character the person has to attend to it and to count how many times the character flashes. Although most BCIs are designed to help people with disabilities, they are mainly tested on healthy, young subjects who may achieve better results than people with impairments. In this study we compare measurements, performed on people suffering motor impairments, such as stroke or ALS, to measurements performed on healthy people. The overall accuracy of the persons with motor impairments reached 70.1% in comparison to 91% obtained for the group of healthy subjects. When looking at single subjects, one interesting example shows that under certain circumstances, when it is difficult for a patient to concentrate on one character for a longer period of time, the accuracy is higher when fewer flashes (i.e., stimuli) are presented. Furthermore, the influence of several tuning parameters is discussed as it shows that for some participants adaptations for achieving valuable spelling results are required. Finally, exclusion criteria for people who are not able to use the device are defined.

SSVEP based brain-computer interface for robot control

A brain computer interface (BCI) using steady state visual evoked potentials (SSVEP) is presented. EEG was derived from 3 subjects to test the suitability of SSVEPs for robot control. To calculate features and to classify the EEG data Minimum Energy and Fast Fourier Transformation (FFT) with linear discriminant analysis (LDA) were used. Finally the change rate (fluctuation of the classification result) and the majority weight of the analysis algorithms were calculated to increase the robustness and to provide a zero-class classification. The implementation was tested with a robot that was able to move forward, backward, to the left and to the right and to stop. A high accuracy was achieved for all commands. Of special interest is that the robot stopped with high reliability if the subject did not watch at the stimulation LEDs and therefore successfully zero-class recognition was implemented.

Human-Computer Confluence for Rehabilitation Purposes after Stroke

In this publication, we present a Motor Imagery (MI) based Brain-Computer Interface (BCI) for neurologic rehabilitation. The BCI is able to control two different feedback devices. The first one is a rehabilitation robot, moving the fingers of the affected hand according to the detected MI. The second one presents feedback via virtual reality (VR) to the subject. The latter one visualizes two hands that the user sees in a first perspective view, which open and close according to the detected MI. Four healthy users participated in tests with the rehabilitation robot, and eleven post stroke patients and eleven healthy users participated to tests with the VR system. We present all subjects’ control accuracy, including a comparison between healthy users and people who suffered stroke. Five of the stroke patients also agreed to participate in further sessions, and we explored possible improvements in accuracy due to training effects.

Performance of a tactile P300 speller for healthy people and severely disabled patients

P300 based Brain-Computer Interfaces (BCIs) for communication are well known since many years. Most of them use visual stimuli to elicit evoked potentials because it is easy to integrate a high number of different classes into the paradigm. Nevertheless, a BCI that depends on visual stimuli is sometimes not feasible due to the presence of visual impairment in patients with severe brain injuries. In this case, it could be possible to use auditory or somatosensory stimulation. In this publication a vibrotactile P300 based BCI is introduced. Two different approaches were tested: a first approach using two stimulators and a second one that utilizes three stimulators for emitting the stimuli. The two paradigms were tested on 16 users: A group of ten healthy users and a second group comprising of 6 patients suffering Locked-In Syndrome. The control accuracy was calculated for both groups and both approaches, proving the feasibility of the device, not only for healthy people but also in severely disabled patients. In a second step we evaluated the influence of the number of stimuli on the accuracy. It was shown that in many cases the maximum accuracy was already reached with a small number of stimuli, this could be used in future tests to speed up the Information transfer rate.

A tactile Brain-Computer Interface for severely disabled patients

Brain-Computer Interfaces (BCI) for communication purposes are usually controlled via a P300 paradigm. There, a high number of different classes is presented to the user, thus enhancing the information transfer rate in comparison to e.g. motor imagery based BCIs. During the last years several P300 speller, based on visual stimulation, were developed. For people with visual impairments another stimulation strategy needs to be used. In this publication a vibrotactile P300 based BCI is introduced. Two different approaches were tested: a first approach using three stimulators and a second one that utilizes eight stimulators for emitting the stimuli. The two paradigms were tested on 18 users: A group of twelve healthy users and a second group comprising of six patients suffering Locked-In Syndrome (LIS). The control accuracy was calculated for both groups, proving the feasibility of the device, not only for healthy people but also in severely disabled patients.

Improved method to perform FES&BCI based rehabilitation

Both, functional electrical stimulation (FES) systems and brain-computer interfaces (BCI) based rehabilitation are earning year by year more involvement within rehabilitation field. This paper presents the coupling of a motor imagery based BCI system with a multichannel neurostimulator in order to control each of the hands opening and lower limb knees extension in paralyzed people. The specialty of the proposed method is related to an extension of the common spatial patterns method, called “one versus the others” in order to discriminate between three motor imagery classes. The effectiveness of the proposed method has been proven during the laboratory tests.

recoveriX: A new BCI-based technology for persons with stroke

Brain-computer interface (BCI) systems have been used primarily to provide communication for persons with severe movement disabilities. This paper presents a new system that extends BCI technology to a new patient group: persons diagnosed with stroke. This system, called recoveriX, is designed to detect changes in motor imagery in real-time to help monitor compliance and provide closed-loop feedback during therapy. We describe recoveriX and present initial results from one patient.

Correlations between muscular contraction type and muscle electrical activity

Each activated motor unit produces an electrical signal. By summing the signals produced at the level of each activated motor unit we achieve an electrical signal that can be recorded as electrical waves. In this study we aimed to identify a correlation between different types of muscular contractions and the muscle electrical activity. 23 healthy persons aged between 19 and 52 years participated to this study. By recording the electrical activity of the triceps brachialis muscle during its contraction it has been found that the strongest electrical activity of the muscle was produced during isometric contractions, followed by eccentric contraction, contraction with weight in the hand, contraction against gravity and contraction without gravity. In other words, as the muscle load is higher the muscle electrical activity is more intense.

A BCI-Based Tool for Detection of Awareness and for Communication with Non-responsive Patients

Imagine being able to think, hear, and feel - but not move or communicate. Over 40% of patients diagnosed as vegetative are reclassified as (at least) minimally conscious when assessed by expert teams. This publication presents a device that uses BCI (Brain-Computer Interface) technology for quick and easy assessment of patients suffering a disorder of consciousness, and even provides basic communication with some of them. A BCI detects changes in brain activity induced by the user’s mental activity. The EEG is used to measure brain signals, which are automatically analyzed and classified on a standard laptop. As long as patients have enough cognitive functions to understand spoken messages, they can be trained to use different mental strategies to provide simple YES/NO answers to questions. The system combines three different BCI approaches within one tool: auditory P300, tactile P300, and motor imagery. These approaches work with patients who cannot see, and (in some cases) also cannot hear

Comparing the accuracy of a p300 speller for people with major physical disability

A Brain-Computer Interface (BCI) can provide an additional option for a person to express himself/herself if he/she suffers a disorder like amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury or other diseases affecting the motor pathway. For a P300 based BCI a matrix of randomly flashing characters is presented to the participant. To spell a character the person has to attend to it and to count how many times the character flashes. The aim of this study was to compare performance achieved by subjects suffering major motor impairments with that of healthy subjects. The overall accuracy of the persons with motor impairments reached 70.1% in comparison to 91% obtained for the group of healthy subjects. When looking at single subjects, one interesting example shows that under certain circumstances, when the patient finds difficult to concentrate on one character for a long period of time, reduce the number of flashes can increase the accuracy. Furthermore, the influence of several tuning parameters is discussed as it shows that for some participants adaptations for achieving valuable spelling results are required. Finally, exclusion criteria for people who are not able to use the device are defined.