Data_Sheet_1_Cortico-muscular coupling to control a hybrid brain-computer interface for upper limb motor rehabilitation: A pseudo-online study on stroke patients.docx

Brain-Computer Interface (BCI) systems for motor rehabilitation after stroke have proven their efficacy to enhance upper limb motor recovery by reinforcing motor related brain activity. Hybrid BCIs (h-BCIs) exploit both central and peripheral activation and are frequently used in assistive BCIs to improve classification performances. However, in a rehabilitative context, brain and muscular features should be extracted to promote a favorable motor outcome, reinforcing not only the volitional control in the central motor system, but also the effective projection of motor commands to target muscles, i.e., central-to-peripheral communication. For this reason, we considered cortico-muscular coupling (CMC) as a feature for a h-BCI devoted to post-stroke upper limb motor rehabilitation. In this study, we performed a pseudo-online analysis on 13 healthy participants (CTRL) and 12 stroke patients (EXP) during executed (CTRL, EXP unaffected arm) and attempted (EXP affected arm) hand grasping and extension to optimize the translation of CMC computation and CMC-based movement detection from offline to online. Results showed that updating the CMC computation every 125 ms (shift of the sliding window) and accumulating two predictions before a final classification decision were the best trade-off between accuracy and speed in movement classification, independently from the movement type. The pseudo-online analysis on stroke participants revealed that both attempted and executed grasping/extension can be classified through a CMC-based movement detection with high performances in terms of classification speed (mean delay between movement detection and EMG onset around 580 ms) and accuracy (hit rate around 85%). The results obtained by means of this analysis will ground the design of a novel non-invasive h-BCI in which the control feature is derived from a combined EEG and EMG connectivity pattern estimated during upper limb movement attempts.</p

Table_1_EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review.DOCX

BackgroundDisorders of Consciousness (DoC) are clinical conditions following a severe acquired brain injury (ABI) characterized by absent or reduced awareness, known as coma, Vegetative State (VS)/Unresponsive Wakefulness Syndrome (VS/UWS), and Minimally Conscious State (MCS). Misdiagnosis rate between VS/UWS and MCS is attested around 40% due to the clinical and behavioral fluctuations of the patients during bedside consciousness assessments. Given the large body of evidence that some patients with DoC possess “covert” awareness, revealed by neuroimaging and neurophysiological techniques, they are candidates for intervention with brain-computer interfaces (BCIs).ObjectivesThe aims of the present work are (i) to describe the characteristics of BCI systems based on electroencephalography (EEG) performed on DoC patients, in terms of control signals adopted to control the system, characteristics of the paradigm implemented, classification algorithms and applications (ii) to evaluate the performance of DoC patients with BCI.MethodsThe search was conducted on Pubmed, Web of Science, Scopus and Google Scholar. The PRISMA guidelines were followed in order to collect papers published in english, testing a BCI and including at least one DoC patient.ResultsAmong the 527 papers identified with the first run of the search, 27 papers were included in the systematic review. Characteristics of the sample of participants, behavioral assessment, control signals employed to control the BCI, the classification algorithms, the characteristics of the paradigm, the applications and performance of BCI were the data extracted from the study. Control signals employed to operate the BCI were: P300 (N = 19), P300 and Steady-State Visual Evoked Potentials (SSVEP; hybrid system, N = 4), sensorimotor rhythms (SMRs; N = 5) and brain rhythms elicited by an emotional task (N = 1), while assessment, communication, prognosis, and rehabilitation were the possible applications of BCI in DoC patients.ConclusionDespite the BCI is a promising tool in the management of DoC patients, supporting diagnosis and prognosis evaluation, results are still preliminary, and no definitive conclusions may be drawn; even though neurophysiological methods, such as BCI, are more sensitive to covert cognition, it is suggested to adopt a multimodal approach and a repeated assessment strategy.</p

“Grau-Gelb” (engl. “grey-yellow”) - a painting created with the Brain Painting application by a locked-in end user with amyotrophic lateral sclerosis (© J Thiele, with permission).

<p>“Grau-Gelb” (engl. “grey-yellow”) - a painting created with the Brain Painting application by a locked-in end user with amyotrophic lateral sclerosis (© J Thiele, with permission).</p

Summary of evaluation results.

1<p>4 sessions (copy spelling, free spelling, emailing, internet surfing).</p>2<p>data refer to the last of 5 free painting sessions.</p>3<p>Utility metric.</p>4<p>3 sessions (copy spelling with and without EMG correction, free spelling (sentence) and emailing).</p>5<p>ITR for BCI only; EMG correction not included.</p>6<p>6 sessions (screening, copy task and free mode playing).</p>7<p>the end-user stated “maybe”.</p>8<p>only 4 of 9 end-users were asked this question.</p><p>Summary of evaluation results.</p

Mean and range for all dimensions of workload and total score for each application averaged across tasks and end-users.

<p>The possible range of each subscale and the total score is 0 to 100.</p><p>Mean and range for all dimensions of workload and total score for each application averaged across tasks and end-users.</p

Transfer of the matrix based speller paradigm to the Qualilife software.

<p>Left: To adapt end-users to the flashing of dots, those were placed in each cell of the well familiar matrix. Instead of the letters those dots were flashed. Right: Screen shot of the Qualilife communication application. The now familiar red dots were assigned to each option of the Qualilife communication and control surface. Red dots appear randomly at each possible “button” to press. Attention needs to be focused on the specific button to be pressed by counting how often the red dot is appearing.</p

Evaluation metrics for each aspect of usability.

<p>NASA-TLX  =  NASA Task Load Index.</p><p>QUEST  =  Quebec User Evaluation of Satisfaction with Assistive Technology.</p><p>ATD-PA  =  Assistive Technology Device Predisposition Assessment.</p><p>VAS  =  visual analogue scale.</p><p>Evaluation metrics for each aspect of usability.</p

Principles and stages of the user-centered design (left column) and their transfer to BCI-controlled applications (right column).

<p>This iterative approach has been realized with the BCI controlled Brain Painting. Numbers in parentheses refer to the publication in which the corresponding steps were realized.</p><p>Principles and stages of the user-centered design (left column) and their transfer to BCI-controlled applications (right column).</p